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densenet201-c1103571.pth
2018-11-23 21:25:08densenet201-c1103571.pth,pytorch预训练模型,densenet201 -
tensorflow使用DenseNet201迁移学习
2020-02-13 08:15:09from tensorflow.keras.applications import DenseNet201 with strategy.scope(): rnet = DenseNet201( input_shape=(IMAGE_SIZE[0], IMAGE_SIZE[1], 3), weights='imagenet', include...from tensorflow.keras.applications import DenseNet201
with strategy.scope(): rnet = DenseNet201( input_shape=(IMAGE_SIZE[0], IMAGE_SIZE[1], 3), weights='imagenet', include_top=False ) rnet.trainable = True model = tf.keras.Sequential([ rnet, tf.keras.layers.GlobalAveragePooling2D(), tf.keras.layers.Dense(len(CLASSES), activation='softmax') ]) model.compile( optimizer='adam', loss = 'sparse_categorical_crossentropy', metrics=['sparse_categorical_accuracy'] ) model.summary() models.append(model)
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keras中densenet201的权重和模型架构
2020-12-02 13:35:39https://github.com/keras-team/keras-applications/releases/download/densenet/densenet201_weights_tf_dim_ordering_tf_kernels.h5 ...https://github.com/keras-team/keras-applications/releases/download/densenet/densenet201_weights_tf_dim_ordering_tf_kernels.h5
https://github.com/keras-team/keras-applications/releases/download/densenet/densenet201_weights_tf_dim_ordering_tf_kernels_notop.h5
import keras.layers as KL import keras.models as KM import keras from keras.applications.densenet import DenseNet201 import os # os.environ['CUDA_DEVICES_VISIBLE'] = '1' print(keras.__version__) input_image = KL.Input(shape=[512, 512, 3], name="input_image") resnet50 = DenseNet201(input_tensor=input_image, include_top=True) # conv5_block1_1_conv x = resnet50.get_layer('fc1000').output # block5_pool max_pool conv5_block1_1_conv # resnet50.summery(0) inputs = [input_image] outputs = [x] model = KM.Model(inputs, outputs, name='ctpn') model.summary()
/home/hlx2/anaconda3/bin/python3.6 "/home/hlx2/OCR/keras-ctpn2 _1/densenet121/taste.py" /home/hlx2/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`. from ._conv import register_converters as _register_converters Using TensorFlow backend. 2.2.5 WARNING:tensorflow:From /home/hlx2/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:541: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead. WARNING:tensorflow:From /home/hlx2/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:66: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead. WARNING:tensorflow:From /home/hlx2/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:4432: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead. WARNING:tensorflow:From /home/hlx2/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:190: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead. WARNING:tensorflow:From /home/hlx2/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:197: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead. 2020-12-01 16:26:30.386109: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 AVX512F FMA 2020-12-01 16:26:30.394812: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3299990000 Hz 2020-12-01 16:26:30.396098: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5638ab3a9710 executing computations on platform Host. Devices: 2020-12-01 16:26:30.396134: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): <undefined>, <undefined> 2020-12-01 16:26:30.397649: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcuda.so.1 2020-12-01 16:26:30.618893: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties: name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.6575 pciBusID: 0000:17:00.0 2020-12-01 16:26:30.619314: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 1 with properties: name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.6575 pciBusID: 0000:65:00.0 2020-12-01 16:26:30.619554: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.1 2020-12-01 16:26:30.620749: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10 2020-12-01 16:26:30.621994: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcufft.so.10 2020-12-01 16:26:30.622271: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcurand.so.10 2020-12-01 16:26:30.623459: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusolver.so.10 2020-12-01 16:26:30.624025: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusparse.so.10 2020-12-01 16:26:30.626488: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7 2020-12-01 16:26:30.627917: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0, 1 2020-12-01 16:26:30.627951: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.1 2020-12-01 16:26:30.629021: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 edge matrix: 2020-12-01 16:26:30.629033: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187] 0 1 2020-12-01 16:26:30.629037: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0: N Y 2020-12-01 16:26:30.629040: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 1: Y N 2020-12-01 16:26:30.630607: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1326] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10479 MB memory) -> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:17:00.0, compute capability: 6.1) 2020-12-01 16:26:30.631557: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1326] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 6795 MB memory) -> physical GPU (device: 1, name: GeForce GTX 1080 Ti, pci bus id: 0000:65:00.0, compute capability: 6.1) 2020-12-01 16:26:30.633249: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x5638ac3f9c70 executing computations on platform CUDA. Devices: 2020-12-01 16:26:30.633263: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): GeForce GTX 1080 Ti, Compute Capability 6.1 2020-12-01 16:26:30.633266: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (1): GeForce GTX 1080 Ti, Compute Capability 6.1 WARNING:tensorflow:From /home/hlx2/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:2041: The name tf.nn.fused_batch_norm is deprecated. Please use tf.compat.v1.nn.fused_batch_norm instead. WARNING:tensorflow:From /home/hlx2/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:4267: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead. WARNING:tensorflow:From /home/hlx2/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:4271: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead. Model: "ctpn" __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== input_image (InputLayer) (None, 512, 512, 3) 0 __________________________________________________________________________________________________ zero_padding2d_1 (ZeroPadding2D (None, 518, 518, 3) 0 input_image[0][0] __________________________________________________________________________________________________ conv1/conv (Conv2D) (None, 256, 256, 64) 9408 zero_padding2d_1[0][0] __________________________________________________________________________________________________ conv1/bn (BatchNormalization) (None, 256, 256, 64) 256 conv1/conv[0][0] __________________________________________________________________________________________________ conv1/relu (Activation) (None, 256, 256, 64) 0 conv1/bn[0][0] __________________________________________________________________________________________________ zero_padding2d_2 (ZeroPadding2D (None, 258, 258, 64) 0 conv1/relu[0][0] __________________________________________________________________________________________________ pool1 (MaxPooling2D) (None, 128, 128, 64) 0 zero_padding2d_2[0][0] __________________________________________________________________________________________________ conv2_block1_0_bn (BatchNormali (None, 128, 128, 64) 256 pool1[0][0] __________________________________________________________________________________________________ conv2_block1_0_relu (Activation (None, 128, 128, 64) 0 conv2_block1_0_bn[0][0] __________________________________________________________________________________________________ conv2_block1_1_conv (Conv2D) (None, 128, 128, 128 8192 conv2_block1_0_relu[0][0] __________________________________________________________________________________________________ conv2_block1_1_bn (BatchNormali (None, 128, 128, 128 512 conv2_block1_1_conv[0][0] __________________________________________________________________________________________________ conv2_block1_1_relu (Activation (None, 128, 128, 128 0 conv2_block1_1_bn[0][0] __________________________________________________________________________________________________ conv2_block1_2_conv (Conv2D) (None, 128, 128, 32) 36864 conv2_block1_1_relu[0][0] __________________________________________________________________________________________________ conv2_block1_concat (Concatenat (None, 128, 128, 96) 0 pool1[0][0] conv2_block1_2_conv[0][0] __________________________________________________________________________________________________ conv2_block2_0_bn (BatchNormali (None, 128, 128, 96) 384 conv2_block1_concat[0][0] __________________________________________________________________________________________________ conv2_block2_0_relu (Activation (None, 128, 128, 96) 0 conv2_block2_0_bn[0][0] __________________________________________________________________________________________________ conv2_block2_1_conv (Conv2D) (None, 128, 128, 128 12288 conv2_block2_0_relu[0][0] __________________________________________________________________________________________________ conv2_block2_1_bn (BatchNormali (None, 128, 128, 128 512 conv2_block2_1_conv[0][0] __________________________________________________________________________________________________ conv2_block2_1_relu (Activation (None, 128, 128, 128 0 conv2_block2_1_bn[0][0] __________________________________________________________________________________________________ conv2_block2_2_conv (Conv2D) (None, 128, 128, 32) 36864 conv2_block2_1_relu[0][0] __________________________________________________________________________________________________ conv2_block2_concat (Concatenat (None, 128, 128, 128 0 conv2_block1_concat[0][0] conv2_block2_2_conv[0][0] __________________________________________________________________________________________________ conv2_block3_0_bn (BatchNormali (None, 128, 128, 128 512 conv2_block2_concat[0][0] __________________________________________________________________________________________________ conv2_block3_0_relu (Activation (None, 128, 128, 128 0 conv2_block3_0_bn[0][0] __________________________________________________________________________________________________ conv2_block3_1_conv (Conv2D) (None, 128, 128, 128 16384 conv2_block3_0_relu[0][0] __________________________________________________________________________________________________ conv2_block3_1_bn (BatchNormali (None, 128, 128, 128 512 conv2_block3_1_conv[0][0] __________________________________________________________________________________________________ conv2_block3_1_relu (Activation (None, 128, 128, 128 0 conv2_block3_1_bn[0][0] __________________________________________________________________________________________________ conv2_block3_2_conv (Conv2D) (None, 128, 128, 32) 36864 conv2_block3_1_relu[0][0] __________________________________________________________________________________________________ conv2_block3_concat (Concatenat (None, 128, 128, 160 0 conv2_block2_concat[0][0] conv2_block3_2_conv[0][0] __________________________________________________________________________________________________ conv2_block4_0_bn (BatchNormali (None, 128, 128, 160 640 conv2_block3_concat[0][0] __________________________________________________________________________________________________ conv2_block4_0_relu (Activation (None, 128, 128, 160 0 conv2_block4_0_bn[0][0] __________________________________________________________________________________________________ conv2_block4_1_conv (Conv2D) (None, 128, 128, 128 20480 conv2_block4_0_relu[0][0] __________________________________________________________________________________________________ conv2_block4_1_bn (BatchNormali (None, 128, 128, 128 512 conv2_block4_1_conv[0][0] __________________________________________________________________________________________________ conv2_block4_1_relu (Activation (None, 128, 128, 128 0 conv2_block4_1_bn[0][0] __________________________________________________________________________________________________ conv2_block4_2_conv (Conv2D) (None, 128, 128, 32) 36864 conv2_block4_1_relu[0][0] __________________________________________________________________________________________________ conv2_block4_concat (Concatenat (None, 128, 128, 192 0 conv2_block3_concat[0][0] conv2_block4_2_conv[0][0] __________________________________________________________________________________________________ conv2_block5_0_bn (BatchNormali (None, 128, 128, 192 768 conv2_block4_concat[0][0] __________________________________________________________________________________________________ conv2_block5_0_relu (Activation (None, 128, 128, 192 0 conv2_block5_0_bn[0][0] __________________________________________________________________________________________________ conv2_block5_1_conv (Conv2D) (None, 128, 128, 128 24576 conv2_block5_0_relu[0][0] __________________________________________________________________________________________________ conv2_block5_1_bn (BatchNormali (None, 128, 128, 128 512 conv2_block5_1_conv[0][0] __________________________________________________________________________________________________ conv2_block5_1_relu (Activation (None, 128, 128, 128 0 conv2_block5_1_bn[0][0] __________________________________________________________________________________________________ conv2_block5_2_conv (Conv2D) (None, 128, 128, 32) 36864 conv2_block5_1_relu[0][0] __________________________________________________________________________________________________ conv2_block5_concat (Concatenat (None, 128, 128, 224 0 conv2_block4_concat[0][0] conv2_block5_2_conv[0][0] __________________________________________________________________________________________________ conv2_block6_0_bn (BatchNormali (None, 128, 128, 224 896 conv2_block5_concat[0][0] __________________________________________________________________________________________________ conv2_block6_0_relu (Activation (None, 128, 128, 224 0 conv2_block6_0_bn[0][0] __________________________________________________________________________________________________ conv2_block6_1_conv (Conv2D) (None, 128, 128, 128 28672 conv2_block6_0_relu[0][0] __________________________________________________________________________________________________ conv2_block6_1_bn (BatchNormali (None, 128, 128, 128 512 conv2_block6_1_conv[0][0] __________________________________________________________________________________________________ conv2_block6_1_relu (Activation (None, 128, 128, 128 0 conv2_block6_1_bn[0][0] __________________________________________________________________________________________________ conv2_block6_2_conv (Conv2D) (None, 128, 128, 32) 36864 conv2_block6_1_relu[0][0] __________________________________________________________________________________________________ conv2_block6_concat (Concatenat (None, 128, 128, 256 0 conv2_block5_concat[0][0] conv2_block6_2_conv[0][0] __________________________________________________________________________________________________ pool2_bn (BatchNormalization) (None, 128, 128, 256 1024 conv2_block6_concat[0][0] __________________________________________________________________________________________________ pool2_relu (Activation) (None, 128, 128, 256 0 pool2_bn[0][0] __________________________________________________________________________________________________ pool2_conv (Conv2D) (None, 128, 128, 128 32768 pool2_relu[0][0] __________________________________________________________________________________________________ pool2_pool (AveragePooling2D) (None, 64, 64, 128) 0 pool2_conv[0][0] __________________________________________________________________________________________________ conv3_block1_0_bn (BatchNormali (None, 64, 64, 128) 512 pool2_pool[0][0] __________________________________________________________________________________________________ conv3_block1_0_relu (Activation (None, 64, 64, 128) 0 conv3_block1_0_bn[0][0] __________________________________________________________________________________________________ conv3_block1_1_conv (Conv2D) (None, 64, 64, 128) 16384 conv3_block1_0_relu[0][0] __________________________________________________________________________________________________ conv3_block1_1_bn (BatchNormali (None, 64, 64, 128) 512 conv3_block1_1_conv[0][0] __________________________________________________________________________________________________ conv3_block1_1_relu (Activation (None, 64, 64, 128) 0 conv3_block1_1_bn[0][0] __________________________________________________________________________________________________ conv3_block1_2_conv (Conv2D) (None, 64, 64, 32) 36864 conv3_block1_1_relu[0][0] __________________________________________________________________________________________________ conv3_block1_concat (Concatenat (None, 64, 64, 160) 0 pool2_pool[0][0] conv3_block1_2_conv[0][0] __________________________________________________________________________________________________ conv3_block2_0_bn (BatchNormali (None, 64, 64, 160) 640 conv3_block1_concat[0][0] __________________________________________________________________________________________________ conv3_block2_0_relu (Activation (None, 64, 64, 160) 0 conv3_block2_0_bn[0][0] __________________________________________________________________________________________________ conv3_block2_1_conv (Conv2D) (None, 64, 64, 128) 20480 conv3_block2_0_relu[0][0] __________________________________________________________________________________________________ conv3_block2_1_bn (BatchNormali (None, 64, 64, 128) 512 conv3_block2_1_conv[0][0] __________________________________________________________________________________________________ conv3_block2_1_relu (Activation (None, 64, 64, 128) 0 conv3_block2_1_bn[0][0] __________________________________________________________________________________________________ conv3_block2_2_conv (Conv2D) (None, 64, 64, 32) 36864 conv3_block2_1_relu[0][0] __________________________________________________________________________________________________ conv3_block2_concat (Concatenat (None, 64, 64, 192) 0 conv3_block1_concat[0][0] conv3_block2_2_conv[0][0] __________________________________________________________________________________________________ conv3_block3_0_bn (BatchNormali (None, 64, 64, 192) 768 conv3_block2_concat[0][0] __________________________________________________________________________________________________ conv3_block3_0_relu (Activation (None, 64, 64, 192) 0 conv3_block3_0_bn[0][0] __________________________________________________________________________________________________ conv3_block3_1_conv (Conv2D) (None, 64, 64, 128) 24576 conv3_block3_0_relu[0][0] __________________________________________________________________________________________________ conv3_block3_1_bn (BatchNormali (None, 64, 64, 128) 512 conv3_block3_1_conv[0][0] __________________________________________________________________________________________________ conv3_block3_1_relu (Activation (None, 64, 64, 128) 0 conv3_block3_1_bn[0][0] __________________________________________________________________________________________________ conv3_block3_2_conv (Conv2D) (None, 64, 64, 32) 36864 conv3_block3_1_relu[0][0] __________________________________________________________________________________________________ conv3_block3_concat (Concatenat (None, 64, 64, 224) 0 conv3_block2_concat[0][0] conv3_block3_2_conv[0][0] __________________________________________________________________________________________________ conv3_block4_0_bn (BatchNormali (None, 64, 64, 224) 896 conv3_block3_concat[0][0] __________________________________________________________________________________________________ conv3_block4_0_relu (Activation (None, 64, 64, 224) 0 conv3_block4_0_bn[0][0] __________________________________________________________________________________________________ conv3_block4_1_conv (Conv2D) (None, 64, 64, 128) 28672 conv3_block4_0_relu[0][0] __________________________________________________________________________________________________ conv3_block4_1_bn (BatchNormali (None, 64, 64, 128) 512 conv3_block4_1_conv[0][0] __________________________________________________________________________________________________ conv3_block4_1_relu (Activation (None, 64, 64, 128) 0 conv3_block4_1_bn[0][0] __________________________________________________________________________________________________ conv3_block4_2_conv (Conv2D) (None, 64, 64, 32) 36864 conv3_block4_1_relu[0][0] __________________________________________________________________________________________________ conv3_block4_concat (Concatenat (None, 64, 64, 256) 0 conv3_block3_concat[0][0] conv3_block4_2_conv[0][0] __________________________________________________________________________________________________ conv3_block5_0_bn (BatchNormali (None, 64, 64, 256) 1024 conv3_block4_concat[0][0] __________________________________________________________________________________________________ conv3_block5_0_relu (Activation (None, 64, 64, 256) 0 conv3_block5_0_bn[0][0] __________________________________________________________________________________________________ conv3_block5_1_conv (Conv2D) (None, 64, 64, 128) 32768 conv3_block5_0_relu[0][0] __________________________________________________________________________________________________ conv3_block5_1_bn (BatchNormali (None, 64, 64, 128) 512 conv3_block5_1_conv[0][0] __________________________________________________________________________________________________ conv3_block5_1_relu (Activation (None, 64, 64, 128) 0 conv3_block5_1_bn[0][0] __________________________________________________________________________________________________ conv3_block5_2_conv (Conv2D) (None, 64, 64, 32) 36864 conv3_block5_1_relu[0][0] __________________________________________________________________________________________________ conv3_block5_concat (Concatenat (None, 64, 64, 288) 0 conv3_block4_concat[0][0] conv3_block5_2_conv[0][0] __________________________________________________________________________________________________ conv3_block6_0_bn (BatchNormali (None, 64, 64, 288) 1152 conv3_block5_concat[0][0] __________________________________________________________________________________________________ conv3_block6_0_relu (Activation (None, 64, 64, 288) 0 conv3_block6_0_bn[0][0] __________________________________________________________________________________________________ conv3_block6_1_conv (Conv2D) (None, 64, 64, 128) 36864 conv3_block6_0_relu[0][0] __________________________________________________________________________________________________ conv3_block6_1_bn (BatchNormali (None, 64, 64, 128) 512 conv3_block6_1_conv[0][0] __________________________________________________________________________________________________ conv3_block6_1_relu (Activation (None, 64, 64, 128) 0 conv3_block6_1_bn[0][0] __________________________________________________________________________________________________ conv3_block6_2_conv (Conv2D) (None, 64, 64, 32) 36864 conv3_block6_1_relu[0][0] __________________________________________________________________________________________________ conv3_block6_concat (Concatenat (None, 64, 64, 320) 0 conv3_block5_concat[0][0] conv3_block6_2_conv[0][0] __________________________________________________________________________________________________ conv3_block7_0_bn (BatchNormali (None, 64, 64, 320) 1280 conv3_block6_concat[0][0] __________________________________________________________________________________________________ conv3_block7_0_relu (Activation (None, 64, 64, 320) 0 conv3_block7_0_bn[0][0] __________________________________________________________________________________________________ conv3_block7_1_conv (Conv2D) (None, 64, 64, 128) 40960 conv3_block7_0_relu[0][0] __________________________________________________________________________________________________ conv3_block7_1_bn (BatchNormali (None, 64, 64, 128) 512 conv3_block7_1_conv[0][0] __________________________________________________________________________________________________ conv3_block7_1_relu (Activation (None, 64, 64, 128) 0 conv3_block7_1_bn[0][0] __________________________________________________________________________________________________ conv3_block7_2_conv (Conv2D) (None, 64, 64, 32) 36864 conv3_block7_1_relu[0][0] __________________________________________________________________________________________________ conv3_block7_concat (Concatenat (None, 64, 64, 352) 0 conv3_block6_concat[0][0] conv3_block7_2_conv[0][0] __________________________________________________________________________________________________ conv3_block8_0_bn (BatchNormali (None, 64, 64, 352) 1408 conv3_block7_concat[0][0] __________________________________________________________________________________________________ conv3_block8_0_relu (Activation (None, 64, 64, 352) 0 conv3_block8_0_bn[0][0] __________________________________________________________________________________________________ conv3_block8_1_conv (Conv2D) (None, 64, 64, 128) 45056 conv3_block8_0_relu[0][0] __________________________________________________________________________________________________ conv3_block8_1_bn (BatchNormali (None, 64, 64, 128) 512 conv3_block8_1_conv[0][0] __________________________________________________________________________________________________ conv3_block8_1_relu (Activation (None, 64, 64, 128) 0 conv3_block8_1_bn[0][0] __________________________________________________________________________________________________ conv3_block8_2_conv (Conv2D) (None, 64, 64, 32) 36864 conv3_block8_1_relu[0][0] __________________________________________________________________________________________________ conv3_block8_concat (Concatenat (None, 64, 64, 384) 0 conv3_block7_concat[0][0] conv3_block8_2_conv[0][0] __________________________________________________________________________________________________ conv3_block9_0_bn (BatchNormali (None, 64, 64, 384) 1536 conv3_block8_concat[0][0] __________________________________________________________________________________________________ conv3_block9_0_relu (Activation (None, 64, 64, 384) 0 conv3_block9_0_bn[0][0] __________________________________________________________________________________________________ conv3_block9_1_conv (Conv2D) (None, 64, 64, 128) 49152 conv3_block9_0_relu[0][0] __________________________________________________________________________________________________ conv3_block9_1_bn (BatchNormali (None, 64, 64, 128) 512 conv3_block9_1_conv[0][0] __________________________________________________________________________________________________ conv3_block9_1_relu (Activation (None, 64, 64, 128) 0 conv3_block9_1_bn[0][0] __________________________________________________________________________________________________ conv3_block9_2_conv (Conv2D) (None, 64, 64, 32) 36864 conv3_block9_1_relu[0][0] __________________________________________________________________________________________________ conv3_block9_concat (Concatenat (None, 64, 64, 416) 0 conv3_block8_concat[0][0] conv3_block9_2_conv[0][0] __________________________________________________________________________________________________ conv3_block10_0_bn (BatchNormal (None, 64, 64, 416) 1664 conv3_block9_concat[0][0] __________________________________________________________________________________________________ conv3_block10_0_relu (Activatio (None, 64, 64, 416) 0 conv3_block10_0_bn[0][0] __________________________________________________________________________________________________ conv3_block10_1_conv (Conv2D) (None, 64, 64, 128) 53248 conv3_block10_0_relu[0][0] __________________________________________________________________________________________________ conv3_block10_1_bn (BatchNormal (None, 64, 64, 128) 512 conv3_block10_1_conv[0][0] __________________________________________________________________________________________________ conv3_block10_1_relu (Activatio (None, 64, 64, 128) 0 conv3_block10_1_bn[0][0] __________________________________________________________________________________________________ conv3_block10_2_conv (Conv2D) (None, 64, 64, 32) 36864 conv3_block10_1_relu[0][0] __________________________________________________________________________________________________ conv3_block10_concat (Concatena (None, 64, 64, 448) 0 conv3_block9_concat[0][0] conv3_block10_2_conv[0][0] __________________________________________________________________________________________________ conv3_block11_0_bn (BatchNormal (None, 64, 64, 448) 1792 conv3_block10_concat[0][0] __________________________________________________________________________________________________ conv3_block11_0_relu (Activatio (None, 64, 64, 448) 0 conv3_block11_0_bn[0][0] __________________________________________________________________________________________________ conv3_block11_1_conv (Conv2D) (None, 64, 64, 128) 57344 conv3_block11_0_relu[0][0] __________________________________________________________________________________________________ conv3_block11_1_bn (BatchNormal (None, 64, 64, 128) 512 conv3_block11_1_conv[0][0] __________________________________________________________________________________________________ conv3_block11_1_relu (Activatio (None, 64, 64, 128) 0 conv3_block11_1_bn[0][0] __________________________________________________________________________________________________ conv3_block11_2_conv (Conv2D) (None, 64, 64, 32) 36864 conv3_block11_1_relu[0][0] __________________________________________________________________________________________________ conv3_block11_concat (Concatena (None, 64, 64, 480) 0 conv3_block10_concat[0][0] conv3_block11_2_conv[0][0] __________________________________________________________________________________________________ conv3_block12_0_bn (BatchNormal (None, 64, 64, 480) 1920 conv3_block11_concat[0][0] __________________________________________________________________________________________________ conv3_block12_0_relu (Activatio (None, 64, 64, 480) 0 conv3_block12_0_bn[0][0] __________________________________________________________________________________________________ conv3_block12_1_conv (Conv2D) (None, 64, 64, 128) 61440 conv3_block12_0_relu[0][0] __________________________________________________________________________________________________ conv3_block12_1_bn (BatchNormal (None, 64, 64, 128) 512 conv3_block12_1_conv[0][0] __________________________________________________________________________________________________ conv3_block12_1_relu (Activatio (None, 64, 64, 128) 0 conv3_block12_1_bn[0][0] __________________________________________________________________________________________________ conv3_block12_2_conv (Conv2D) (None, 64, 64, 32) 36864 conv3_block12_1_relu[0][0] __________________________________________________________________________________________________ conv3_block12_concat (Concatena (None, 64, 64, 512) 0 conv3_block11_concat[0][0] conv3_block12_2_conv[0][0] __________________________________________________________________________________________________ pool3_bn (BatchNormalization) (None, 64, 64, 512) 2048 conv3_block12_concat[0][0] __________________________________________________________________________________________________ pool3_relu (Activation) (None, 64, 64, 512) 0 pool3_bn[0][0] __________________________________________________________________________________________________ pool3_conv (Conv2D) (None, 64, 64, 256) 131072 pool3_relu[0][0] __________________________________________________________________________________________________ pool3_pool (AveragePooling2D) (None, 32, 32, 256) 0 pool3_conv[0][0] __________________________________________________________________________________________________ conv4_block1_0_bn (BatchNormali (None, 32, 32, 256) 1024 pool3_pool[0][0] __________________________________________________________________________________________________ conv4_block1_0_relu (Activation (None, 32, 32, 256) 0 conv4_block1_0_bn[0][0] __________________________________________________________________________________________________ conv4_block1_1_conv (Conv2D) (None, 32, 32, 128) 32768 conv4_block1_0_relu[0][0] __________________________________________________________________________________________________ conv4_block1_1_bn (BatchNormali (None, 32, 32, 128) 512 conv4_block1_1_conv[0][0] __________________________________________________________________________________________________ conv4_block1_1_relu (Activation (None, 32, 32, 128) 0 conv4_block1_1_bn[0][0] __________________________________________________________________________________________________ conv4_block1_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block1_1_relu[0][0] __________________________________________________________________________________________________ conv4_block1_concat (Concatenat (None, 32, 32, 288) 0 pool3_pool[0][0] conv4_block1_2_conv[0][0] __________________________________________________________________________________________________ conv4_block2_0_bn (BatchNormali (None, 32, 32, 288) 1152 conv4_block1_concat[0][0] __________________________________________________________________________________________________ conv4_block2_0_relu (Activation (None, 32, 32, 288) 0 conv4_block2_0_bn[0][0] __________________________________________________________________________________________________ conv4_block2_1_conv (Conv2D) (None, 32, 32, 128) 36864 conv4_block2_0_relu[0][0] __________________________________________________________________________________________________ conv4_block2_1_bn (BatchNormali (None, 32, 32, 128) 512 conv4_block2_1_conv[0][0] __________________________________________________________________________________________________ conv4_block2_1_relu (Activation (None, 32, 32, 128) 0 conv4_block2_1_bn[0][0] __________________________________________________________________________________________________ conv4_block2_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block2_1_relu[0][0] __________________________________________________________________________________________________ conv4_block2_concat (Concatenat (None, 32, 32, 320) 0 conv4_block1_concat[0][0] conv4_block2_2_conv[0][0] __________________________________________________________________________________________________ conv4_block3_0_bn (BatchNormali (None, 32, 32, 320) 1280 conv4_block2_concat[0][0] __________________________________________________________________________________________________ conv4_block3_0_relu (Activation (None, 32, 32, 320) 0 conv4_block3_0_bn[0][0] __________________________________________________________________________________________________ conv4_block3_1_conv (Conv2D) (None, 32, 32, 128) 40960 conv4_block3_0_relu[0][0] __________________________________________________________________________________________________ conv4_block3_1_bn (BatchNormali (None, 32, 32, 128) 512 conv4_block3_1_conv[0][0] __________________________________________________________________________________________________ conv4_block3_1_relu (Activation (None, 32, 32, 128) 0 conv4_block3_1_bn[0][0] __________________________________________________________________________________________________ conv4_block3_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block3_1_relu[0][0] __________________________________________________________________________________________________ conv4_block3_concat (Concatenat (None, 32, 32, 352) 0 conv4_block2_concat[0][0] conv4_block3_2_conv[0][0] __________________________________________________________________________________________________ conv4_block4_0_bn (BatchNormali (None, 32, 32, 352) 1408 conv4_block3_concat[0][0] __________________________________________________________________________________________________ conv4_block4_0_relu (Activation (None, 32, 32, 352) 0 conv4_block4_0_bn[0][0] __________________________________________________________________________________________________ conv4_block4_1_conv (Conv2D) (None, 32, 32, 128) 45056 conv4_block4_0_relu[0][0] __________________________________________________________________________________________________ conv4_block4_1_bn (BatchNormali (None, 32, 32, 128) 512 conv4_block4_1_conv[0][0] __________________________________________________________________________________________________ conv4_block4_1_relu (Activation (None, 32, 32, 128) 0 conv4_block4_1_bn[0][0] __________________________________________________________________________________________________ conv4_block4_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block4_1_relu[0][0] __________________________________________________________________________________________________ conv4_block4_concat (Concatenat (None, 32, 32, 384) 0 conv4_block3_concat[0][0] conv4_block4_2_conv[0][0] __________________________________________________________________________________________________ conv4_block5_0_bn (BatchNormali (None, 32, 32, 384) 1536 conv4_block4_concat[0][0] __________________________________________________________________________________________________ conv4_block5_0_relu (Activation (None, 32, 32, 384) 0 conv4_block5_0_bn[0][0] __________________________________________________________________________________________________ conv4_block5_1_conv (Conv2D) (None, 32, 32, 128) 49152 conv4_block5_0_relu[0][0] __________________________________________________________________________________________________ conv4_block5_1_bn (BatchNormali (None, 32, 32, 128) 512 conv4_block5_1_conv[0][0] __________________________________________________________________________________________________ conv4_block5_1_relu (Activation (None, 32, 32, 128) 0 conv4_block5_1_bn[0][0] __________________________________________________________________________________________________ conv4_block5_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block5_1_relu[0][0] __________________________________________________________________________________________________ conv4_block5_concat (Concatenat (None, 32, 32, 416) 0 conv4_block4_concat[0][0] conv4_block5_2_conv[0][0] __________________________________________________________________________________________________ conv4_block6_0_bn (BatchNormali (None, 32, 32, 416) 1664 conv4_block5_concat[0][0] __________________________________________________________________________________________________ conv4_block6_0_relu (Activation (None, 32, 32, 416) 0 conv4_block6_0_bn[0][0] __________________________________________________________________________________________________ conv4_block6_1_conv (Conv2D) (None, 32, 32, 128) 53248 conv4_block6_0_relu[0][0] __________________________________________________________________________________________________ conv4_block6_1_bn (BatchNormali (None, 32, 32, 128) 512 conv4_block6_1_conv[0][0] __________________________________________________________________________________________________ conv4_block6_1_relu (Activation (None, 32, 32, 128) 0 conv4_block6_1_bn[0][0] __________________________________________________________________________________________________ conv4_block6_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block6_1_relu[0][0] __________________________________________________________________________________________________ conv4_block6_concat (Concatenat (None, 32, 32, 448) 0 conv4_block5_concat[0][0] conv4_block6_2_conv[0][0] __________________________________________________________________________________________________ conv4_block7_0_bn (BatchNormali (None, 32, 32, 448) 1792 conv4_block6_concat[0][0] __________________________________________________________________________________________________ conv4_block7_0_relu (Activation (None, 32, 32, 448) 0 conv4_block7_0_bn[0][0] __________________________________________________________________________________________________ conv4_block7_1_conv (Conv2D) (None, 32, 32, 128) 57344 conv4_block7_0_relu[0][0] __________________________________________________________________________________________________ conv4_block7_1_bn (BatchNormali (None, 32, 32, 128) 512 conv4_block7_1_conv[0][0] __________________________________________________________________________________________________ conv4_block7_1_relu (Activation (None, 32, 32, 128) 0 conv4_block7_1_bn[0][0] __________________________________________________________________________________________________ conv4_block7_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block7_1_relu[0][0] __________________________________________________________________________________________________ conv4_block7_concat (Concatenat (None, 32, 32, 480) 0 conv4_block6_concat[0][0] conv4_block7_2_conv[0][0] __________________________________________________________________________________________________ conv4_block8_0_bn (BatchNormali (None, 32, 32, 480) 1920 conv4_block7_concat[0][0] __________________________________________________________________________________________________ conv4_block8_0_relu (Activation (None, 32, 32, 480) 0 conv4_block8_0_bn[0][0] __________________________________________________________________________________________________ conv4_block8_1_conv (Conv2D) (None, 32, 32, 128) 61440 conv4_block8_0_relu[0][0] __________________________________________________________________________________________________ conv4_block8_1_bn (BatchNormali (None, 32, 32, 128) 512 conv4_block8_1_conv[0][0] __________________________________________________________________________________________________ conv4_block8_1_relu (Activation (None, 32, 32, 128) 0 conv4_block8_1_bn[0][0] __________________________________________________________________________________________________ conv4_block8_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block8_1_relu[0][0] __________________________________________________________________________________________________ conv4_block8_concat (Concatenat (None, 32, 32, 512) 0 conv4_block7_concat[0][0] conv4_block8_2_conv[0][0] __________________________________________________________________________________________________ conv4_block9_0_bn (BatchNormali (None, 32, 32, 512) 2048 conv4_block8_concat[0][0] __________________________________________________________________________________________________ conv4_block9_0_relu (Activation (None, 32, 32, 512) 0 conv4_block9_0_bn[0][0] __________________________________________________________________________________________________ conv4_block9_1_conv (Conv2D) (None, 32, 32, 128) 65536 conv4_block9_0_relu[0][0] __________________________________________________________________________________________________ conv4_block9_1_bn (BatchNormali (None, 32, 32, 128) 512 conv4_block9_1_conv[0][0] __________________________________________________________________________________________________ conv4_block9_1_relu (Activation (None, 32, 32, 128) 0 conv4_block9_1_bn[0][0] __________________________________________________________________________________________________ conv4_block9_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block9_1_relu[0][0] __________________________________________________________________________________________________ conv4_block9_concat (Concatenat (None, 32, 32, 544) 0 conv4_block8_concat[0][0] conv4_block9_2_conv[0][0] __________________________________________________________________________________________________ conv4_block10_0_bn (BatchNormal (None, 32, 32, 544) 2176 conv4_block9_concat[0][0] __________________________________________________________________________________________________ conv4_block10_0_relu (Activatio (None, 32, 32, 544) 0 conv4_block10_0_bn[0][0] __________________________________________________________________________________________________ conv4_block10_1_conv (Conv2D) (None, 32, 32, 128) 69632 conv4_block10_0_relu[0][0] __________________________________________________________________________________________________ conv4_block10_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block10_1_conv[0][0] __________________________________________________________________________________________________ conv4_block10_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block10_1_bn[0][0] __________________________________________________________________________________________________ conv4_block10_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block10_1_relu[0][0] __________________________________________________________________________________________________ conv4_block10_concat (Concatena (None, 32, 32, 576) 0 conv4_block9_concat[0][0] conv4_block10_2_conv[0][0] __________________________________________________________________________________________________ conv4_block11_0_bn (BatchNormal (None, 32, 32, 576) 2304 conv4_block10_concat[0][0] __________________________________________________________________________________________________ conv4_block11_0_relu (Activatio (None, 32, 32, 576) 0 conv4_block11_0_bn[0][0] __________________________________________________________________________________________________ conv4_block11_1_conv (Conv2D) (None, 32, 32, 128) 73728 conv4_block11_0_relu[0][0] __________________________________________________________________________________________________ conv4_block11_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block11_1_conv[0][0] __________________________________________________________________________________________________ conv4_block11_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block11_1_bn[0][0] __________________________________________________________________________________________________ conv4_block11_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block11_1_relu[0][0] __________________________________________________________________________________________________ conv4_block11_concat (Concatena (None, 32, 32, 608) 0 conv4_block10_concat[0][0] conv4_block11_2_conv[0][0] __________________________________________________________________________________________________ conv4_block12_0_bn (BatchNormal (None, 32, 32, 608) 2432 conv4_block11_concat[0][0] __________________________________________________________________________________________________ conv4_block12_0_relu (Activatio (None, 32, 32, 608) 0 conv4_block12_0_bn[0][0] __________________________________________________________________________________________________ conv4_block12_1_conv (Conv2D) (None, 32, 32, 128) 77824 conv4_block12_0_relu[0][0] __________________________________________________________________________________________________ conv4_block12_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block12_1_conv[0][0] __________________________________________________________________________________________________ conv4_block12_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block12_1_bn[0][0] __________________________________________________________________________________________________ conv4_block12_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block12_1_relu[0][0] __________________________________________________________________________________________________ conv4_block12_concat (Concatena (None, 32, 32, 640) 0 conv4_block11_concat[0][0] conv4_block12_2_conv[0][0] __________________________________________________________________________________________________ conv4_block13_0_bn (BatchNormal (None, 32, 32, 640) 2560 conv4_block12_concat[0][0] __________________________________________________________________________________________________ conv4_block13_0_relu (Activatio (None, 32, 32, 640) 0 conv4_block13_0_bn[0][0] __________________________________________________________________________________________________ conv4_block13_1_conv (Conv2D) (None, 32, 32, 128) 81920 conv4_block13_0_relu[0][0] __________________________________________________________________________________________________ conv4_block13_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block13_1_conv[0][0] __________________________________________________________________________________________________ conv4_block13_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block13_1_bn[0][0] __________________________________________________________________________________________________ conv4_block13_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block13_1_relu[0][0] __________________________________________________________________________________________________ conv4_block13_concat (Concatena (None, 32, 32, 672) 0 conv4_block12_concat[0][0] conv4_block13_2_conv[0][0] __________________________________________________________________________________________________ conv4_block14_0_bn (BatchNormal (None, 32, 32, 672) 2688 conv4_block13_concat[0][0] __________________________________________________________________________________________________ conv4_block14_0_relu (Activatio (None, 32, 32, 672) 0 conv4_block14_0_bn[0][0] __________________________________________________________________________________________________ conv4_block14_1_conv (Conv2D) (None, 32, 32, 128) 86016 conv4_block14_0_relu[0][0] __________________________________________________________________________________________________ conv4_block14_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block14_1_conv[0][0] __________________________________________________________________________________________________ conv4_block14_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block14_1_bn[0][0] __________________________________________________________________________________________________ conv4_block14_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block14_1_relu[0][0] __________________________________________________________________________________________________ conv4_block14_concat (Concatena (None, 32, 32, 704) 0 conv4_block13_concat[0][0] conv4_block14_2_conv[0][0] __________________________________________________________________________________________________ conv4_block15_0_bn (BatchNormal (None, 32, 32, 704) 2816 conv4_block14_concat[0][0] __________________________________________________________________________________________________ conv4_block15_0_relu (Activatio (None, 32, 32, 704) 0 conv4_block15_0_bn[0][0] __________________________________________________________________________________________________ conv4_block15_1_conv (Conv2D) (None, 32, 32, 128) 90112 conv4_block15_0_relu[0][0] __________________________________________________________________________________________________ conv4_block15_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block15_1_conv[0][0] __________________________________________________________________________________________________ conv4_block15_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block15_1_bn[0][0] __________________________________________________________________________________________________ conv4_block15_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block15_1_relu[0][0] __________________________________________________________________________________________________ conv4_block15_concat (Concatena (None, 32, 32, 736) 0 conv4_block14_concat[0][0] conv4_block15_2_conv[0][0] __________________________________________________________________________________________________ conv4_block16_0_bn (BatchNormal (None, 32, 32, 736) 2944 conv4_block15_concat[0][0] __________________________________________________________________________________________________ conv4_block16_0_relu (Activatio (None, 32, 32, 736) 0 conv4_block16_0_bn[0][0] __________________________________________________________________________________________________ conv4_block16_1_conv (Conv2D) (None, 32, 32, 128) 94208 conv4_block16_0_relu[0][0] __________________________________________________________________________________________________ conv4_block16_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block16_1_conv[0][0] __________________________________________________________________________________________________ conv4_block16_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block16_1_bn[0][0] __________________________________________________________________________________________________ conv4_block16_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block16_1_relu[0][0] __________________________________________________________________________________________________ conv4_block16_concat (Concatena (None, 32, 32, 768) 0 conv4_block15_concat[0][0] conv4_block16_2_conv[0][0] __________________________________________________________________________________________________ conv4_block17_0_bn (BatchNormal (None, 32, 32, 768) 3072 conv4_block16_concat[0][0] __________________________________________________________________________________________________ conv4_block17_0_relu (Activatio (None, 32, 32, 768) 0 conv4_block17_0_bn[0][0] __________________________________________________________________________________________________ conv4_block17_1_conv (Conv2D) (None, 32, 32, 128) 98304 conv4_block17_0_relu[0][0] __________________________________________________________________________________________________ conv4_block17_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block17_1_conv[0][0] __________________________________________________________________________________________________ conv4_block17_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block17_1_bn[0][0] __________________________________________________________________________________________________ conv4_block17_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block17_1_relu[0][0] __________________________________________________________________________________________________ conv4_block17_concat (Concatena (None, 32, 32, 800) 0 conv4_block16_concat[0][0] conv4_block17_2_conv[0][0] __________________________________________________________________________________________________ conv4_block18_0_bn (BatchNormal (None, 32, 32, 800) 3200 conv4_block17_concat[0][0] __________________________________________________________________________________________________ conv4_block18_0_relu (Activatio (None, 32, 32, 800) 0 conv4_block18_0_bn[0][0] __________________________________________________________________________________________________ conv4_block18_1_conv (Conv2D) (None, 32, 32, 128) 102400 conv4_block18_0_relu[0][0] __________________________________________________________________________________________________ conv4_block18_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block18_1_conv[0][0] __________________________________________________________________________________________________ conv4_block18_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block18_1_bn[0][0] __________________________________________________________________________________________________ conv4_block18_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block18_1_relu[0][0] __________________________________________________________________________________________________ conv4_block18_concat (Concatena (None, 32, 32, 832) 0 conv4_block17_concat[0][0] conv4_block18_2_conv[0][0] __________________________________________________________________________________________________ conv4_block19_0_bn (BatchNormal (None, 32, 32, 832) 3328 conv4_block18_concat[0][0] __________________________________________________________________________________________________ conv4_block19_0_relu (Activatio (None, 32, 32, 832) 0 conv4_block19_0_bn[0][0] __________________________________________________________________________________________________ conv4_block19_1_conv (Conv2D) (None, 32, 32, 128) 106496 conv4_block19_0_relu[0][0] __________________________________________________________________________________________________ conv4_block19_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block19_1_conv[0][0] __________________________________________________________________________________________________ conv4_block19_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block19_1_bn[0][0] __________________________________________________________________________________________________ conv4_block19_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block19_1_relu[0][0] __________________________________________________________________________________________________ conv4_block19_concat (Concatena (None, 32, 32, 864) 0 conv4_block18_concat[0][0] conv4_block19_2_conv[0][0] __________________________________________________________________________________________________ conv4_block20_0_bn (BatchNormal (None, 32, 32, 864) 3456 conv4_block19_concat[0][0] __________________________________________________________________________________________________ conv4_block20_0_relu (Activatio (None, 32, 32, 864) 0 conv4_block20_0_bn[0][0] __________________________________________________________________________________________________ conv4_block20_1_conv (Conv2D) (None, 32, 32, 128) 110592 conv4_block20_0_relu[0][0] __________________________________________________________________________________________________ conv4_block20_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block20_1_conv[0][0] __________________________________________________________________________________________________ conv4_block20_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block20_1_bn[0][0] __________________________________________________________________________________________________ conv4_block20_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block20_1_relu[0][0] __________________________________________________________________________________________________ conv4_block20_concat (Concatena (None, 32, 32, 896) 0 conv4_block19_concat[0][0] conv4_block20_2_conv[0][0] __________________________________________________________________________________________________ conv4_block21_0_bn (BatchNormal (None, 32, 32, 896) 3584 conv4_block20_concat[0][0] __________________________________________________________________________________________________ conv4_block21_0_relu (Activatio (None, 32, 32, 896) 0 conv4_block21_0_bn[0][0] __________________________________________________________________________________________________ conv4_block21_1_conv (Conv2D) (None, 32, 32, 128) 114688 conv4_block21_0_relu[0][0] __________________________________________________________________________________________________ conv4_block21_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block21_1_conv[0][0] __________________________________________________________________________________________________ conv4_block21_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block21_1_bn[0][0] __________________________________________________________________________________________________ conv4_block21_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block21_1_relu[0][0] __________________________________________________________________________________________________ conv4_block21_concat (Concatena (None, 32, 32, 928) 0 conv4_block20_concat[0][0] conv4_block21_2_conv[0][0] __________________________________________________________________________________________________ conv4_block22_0_bn (BatchNormal (None, 32, 32, 928) 3712 conv4_block21_concat[0][0] __________________________________________________________________________________________________ conv4_block22_0_relu (Activatio (None, 32, 32, 928) 0 conv4_block22_0_bn[0][0] __________________________________________________________________________________________________ conv4_block22_1_conv (Conv2D) (None, 32, 32, 128) 118784 conv4_block22_0_relu[0][0] __________________________________________________________________________________________________ conv4_block22_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block22_1_conv[0][0] __________________________________________________________________________________________________ conv4_block22_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block22_1_bn[0][0] __________________________________________________________________________________________________ conv4_block22_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block22_1_relu[0][0] __________________________________________________________________________________________________ conv4_block22_concat (Concatena (None, 32, 32, 960) 0 conv4_block21_concat[0][0] conv4_block22_2_conv[0][0] __________________________________________________________________________________________________ conv4_block23_0_bn (BatchNormal (None, 32, 32, 960) 3840 conv4_block22_concat[0][0] __________________________________________________________________________________________________ conv4_block23_0_relu (Activatio (None, 32, 32, 960) 0 conv4_block23_0_bn[0][0] __________________________________________________________________________________________________ conv4_block23_1_conv (Conv2D) (None, 32, 32, 128) 122880 conv4_block23_0_relu[0][0] __________________________________________________________________________________________________ conv4_block23_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block23_1_conv[0][0] __________________________________________________________________________________________________ conv4_block23_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block23_1_bn[0][0] __________________________________________________________________________________________________ conv4_block23_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block23_1_relu[0][0] __________________________________________________________________________________________________ conv4_block23_concat (Concatena (None, 32, 32, 992) 0 conv4_block22_concat[0][0] conv4_block23_2_conv[0][0] __________________________________________________________________________________________________ conv4_block24_0_bn (BatchNormal (None, 32, 32, 992) 3968 conv4_block23_concat[0][0] __________________________________________________________________________________________________ conv4_block24_0_relu (Activatio (None, 32, 32, 992) 0 conv4_block24_0_bn[0][0] __________________________________________________________________________________________________ conv4_block24_1_conv (Conv2D) (None, 32, 32, 128) 126976 conv4_block24_0_relu[0][0] __________________________________________________________________________________________________ conv4_block24_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block24_1_conv[0][0] __________________________________________________________________________________________________ conv4_block24_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block24_1_bn[0][0] __________________________________________________________________________________________________ conv4_block24_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block24_1_relu[0][0] __________________________________________________________________________________________________ conv4_block24_concat (Concatena (None, 32, 32, 1024) 0 conv4_block23_concat[0][0] conv4_block24_2_conv[0][0] __________________________________________________________________________________________________ conv4_block25_0_bn (BatchNormal (None, 32, 32, 1024) 4096 conv4_block24_concat[0][0] __________________________________________________________________________________________________ conv4_block25_0_relu (Activatio (None, 32, 32, 1024) 0 conv4_block25_0_bn[0][0] __________________________________________________________________________________________________ conv4_block25_1_conv (Conv2D) (None, 32, 32, 128) 131072 conv4_block25_0_relu[0][0] __________________________________________________________________________________________________ conv4_block25_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block25_1_conv[0][0] __________________________________________________________________________________________________ conv4_block25_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block25_1_bn[0][0] __________________________________________________________________________________________________ conv4_block25_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block25_1_relu[0][0] __________________________________________________________________________________________________ conv4_block25_concat (Concatena (None, 32, 32, 1056) 0 conv4_block24_concat[0][0] conv4_block25_2_conv[0][0] __________________________________________________________________________________________________ conv4_block26_0_bn (BatchNormal (None, 32, 32, 1056) 4224 conv4_block25_concat[0][0] __________________________________________________________________________________________________ conv4_block26_0_relu (Activatio (None, 32, 32, 1056) 0 conv4_block26_0_bn[0][0] __________________________________________________________________________________________________ conv4_block26_1_conv (Conv2D) (None, 32, 32, 128) 135168 conv4_block26_0_relu[0][0] __________________________________________________________________________________________________ conv4_block26_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block26_1_conv[0][0] __________________________________________________________________________________________________ conv4_block26_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block26_1_bn[0][0] __________________________________________________________________________________________________ conv4_block26_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block26_1_relu[0][0] __________________________________________________________________________________________________ conv4_block26_concat (Concatena (None, 32, 32, 1088) 0 conv4_block25_concat[0][0] conv4_block26_2_conv[0][0] __________________________________________________________________________________________________ conv4_block27_0_bn (BatchNormal (None, 32, 32, 1088) 4352 conv4_block26_concat[0][0] __________________________________________________________________________________________________ conv4_block27_0_relu (Activatio (None, 32, 32, 1088) 0 conv4_block27_0_bn[0][0] __________________________________________________________________________________________________ conv4_block27_1_conv (Conv2D) (None, 32, 32, 128) 139264 conv4_block27_0_relu[0][0] __________________________________________________________________________________________________ conv4_block27_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block27_1_conv[0][0] __________________________________________________________________________________________________ conv4_block27_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block27_1_bn[0][0] __________________________________________________________________________________________________ conv4_block27_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block27_1_relu[0][0] __________________________________________________________________________________________________ conv4_block27_concat (Concatena (None, 32, 32, 1120) 0 conv4_block26_concat[0][0] conv4_block27_2_conv[0][0] __________________________________________________________________________________________________ conv4_block28_0_bn (BatchNormal (None, 32, 32, 1120) 4480 conv4_block27_concat[0][0] __________________________________________________________________________________________________ conv4_block28_0_relu (Activatio (None, 32, 32, 1120) 0 conv4_block28_0_bn[0][0] __________________________________________________________________________________________________ conv4_block28_1_conv (Conv2D) (None, 32, 32, 128) 143360 conv4_block28_0_relu[0][0] __________________________________________________________________________________________________ conv4_block28_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block28_1_conv[0][0] __________________________________________________________________________________________________ conv4_block28_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block28_1_bn[0][0] __________________________________________________________________________________________________ conv4_block28_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block28_1_relu[0][0] __________________________________________________________________________________________________ conv4_block28_concat (Concatena (None, 32, 32, 1152) 0 conv4_block27_concat[0][0] conv4_block28_2_conv[0][0] __________________________________________________________________________________________________ conv4_block29_0_bn (BatchNormal (None, 32, 32, 1152) 4608 conv4_block28_concat[0][0] __________________________________________________________________________________________________ conv4_block29_0_relu (Activatio (None, 32, 32, 1152) 0 conv4_block29_0_bn[0][0] __________________________________________________________________________________________________ conv4_block29_1_conv (Conv2D) (None, 32, 32, 128) 147456 conv4_block29_0_relu[0][0] __________________________________________________________________________________________________ conv4_block29_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block29_1_conv[0][0] __________________________________________________________________________________________________ conv4_block29_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block29_1_bn[0][0] __________________________________________________________________________________________________ conv4_block29_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block29_1_relu[0][0] __________________________________________________________________________________________________ conv4_block29_concat (Concatena (None, 32, 32, 1184) 0 conv4_block28_concat[0][0] conv4_block29_2_conv[0][0] __________________________________________________________________________________________________ conv4_block30_0_bn (BatchNormal (None, 32, 32, 1184) 4736 conv4_block29_concat[0][0] __________________________________________________________________________________________________ conv4_block30_0_relu (Activatio (None, 32, 32, 1184) 0 conv4_block30_0_bn[0][0] __________________________________________________________________________________________________ conv4_block30_1_conv (Conv2D) (None, 32, 32, 128) 151552 conv4_block30_0_relu[0][0] __________________________________________________________________________________________________ conv4_block30_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block30_1_conv[0][0] __________________________________________________________________________________________________ conv4_block30_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block30_1_bn[0][0] __________________________________________________________________________________________________ conv4_block30_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block30_1_relu[0][0] __________________________________________________________________________________________________ conv4_block30_concat (Concatena (None, 32, 32, 1216) 0 conv4_block29_concat[0][0] conv4_block30_2_conv[0][0] __________________________________________________________________________________________________ conv4_block31_0_bn (BatchNormal (None, 32, 32, 1216) 4864 conv4_block30_concat[0][0] __________________________________________________________________________________________________ conv4_block31_0_relu (Activatio (None, 32, 32, 1216) 0 conv4_block31_0_bn[0][0] __________________________________________________________________________________________________ conv4_block31_1_conv (Conv2D) (None, 32, 32, 128) 155648 conv4_block31_0_relu[0][0] __________________________________________________________________________________________________ conv4_block31_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block31_1_conv[0][0] __________________________________________________________________________________________________ conv4_block31_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block31_1_bn[0][0] __________________________________________________________________________________________________ conv4_block31_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block31_1_relu[0][0] __________________________________________________________________________________________________ conv4_block31_concat (Concatena (None, 32, 32, 1248) 0 conv4_block30_concat[0][0] conv4_block31_2_conv[0][0] __________________________________________________________________________________________________ conv4_block32_0_bn (BatchNormal (None, 32, 32, 1248) 4992 conv4_block31_concat[0][0] __________________________________________________________________________________________________ conv4_block32_0_relu (Activatio (None, 32, 32, 1248) 0 conv4_block32_0_bn[0][0] __________________________________________________________________________________________________ conv4_block32_1_conv (Conv2D) (None, 32, 32, 128) 159744 conv4_block32_0_relu[0][0] __________________________________________________________________________________________________ conv4_block32_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block32_1_conv[0][0] __________________________________________________________________________________________________ conv4_block32_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block32_1_bn[0][0] __________________________________________________________________________________________________ conv4_block32_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block32_1_relu[0][0] __________________________________________________________________________________________________ conv4_block32_concat (Concatena (None, 32, 32, 1280) 0 conv4_block31_concat[0][0] conv4_block32_2_conv[0][0] __________________________________________________________________________________________________ conv4_block33_0_bn (BatchNormal (None, 32, 32, 1280) 5120 conv4_block32_concat[0][0] __________________________________________________________________________________________________ conv4_block33_0_relu (Activatio (None, 32, 32, 1280) 0 conv4_block33_0_bn[0][0] __________________________________________________________________________________________________ conv4_block33_1_conv (Conv2D) (None, 32, 32, 128) 163840 conv4_block33_0_relu[0][0] __________________________________________________________________________________________________ conv4_block33_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block33_1_conv[0][0] __________________________________________________________________________________________________ conv4_block33_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block33_1_bn[0][0] __________________________________________________________________________________________________ conv4_block33_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block33_1_relu[0][0] __________________________________________________________________________________________________ conv4_block33_concat (Concatena (None, 32, 32, 1312) 0 conv4_block32_concat[0][0] conv4_block33_2_conv[0][0] __________________________________________________________________________________________________ conv4_block34_0_bn (BatchNormal (None, 32, 32, 1312) 5248 conv4_block33_concat[0][0] __________________________________________________________________________________________________ conv4_block34_0_relu (Activatio (None, 32, 32, 1312) 0 conv4_block34_0_bn[0][0] __________________________________________________________________________________________________ conv4_block34_1_conv (Conv2D) (None, 32, 32, 128) 167936 conv4_block34_0_relu[0][0] __________________________________________________________________________________________________ conv4_block34_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block34_1_conv[0][0] __________________________________________________________________________________________________ conv4_block34_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block34_1_bn[0][0] __________________________________________________________________________________________________ conv4_block34_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block34_1_relu[0][0] __________________________________________________________________________________________________ conv4_block34_concat (Concatena (None, 32, 32, 1344) 0 conv4_block33_concat[0][0] conv4_block34_2_conv[0][0] __________________________________________________________________________________________________ conv4_block35_0_bn (BatchNormal (None, 32, 32, 1344) 5376 conv4_block34_concat[0][0] __________________________________________________________________________________________________ conv4_block35_0_relu (Activatio (None, 32, 32, 1344) 0 conv4_block35_0_bn[0][0] __________________________________________________________________________________________________ conv4_block35_1_conv (Conv2D) (None, 32, 32, 128) 172032 conv4_block35_0_relu[0][0] __________________________________________________________________________________________________ conv4_block35_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block35_1_conv[0][0] __________________________________________________________________________________________________ conv4_block35_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block35_1_bn[0][0] __________________________________________________________________________________________________ conv4_block35_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block35_1_relu[0][0] __________________________________________________________________________________________________ conv4_block35_concat (Concatena (None, 32, 32, 1376) 0 conv4_block34_concat[0][0] conv4_block35_2_conv[0][0] __________________________________________________________________________________________________ conv4_block36_0_bn (BatchNormal (None, 32, 32, 1376) 5504 conv4_block35_concat[0][0] __________________________________________________________________________________________________ conv4_block36_0_relu (Activatio (None, 32, 32, 1376) 0 conv4_block36_0_bn[0][0] __________________________________________________________________________________________________ conv4_block36_1_conv (Conv2D) (None, 32, 32, 128) 176128 conv4_block36_0_relu[0][0] __________________________________________________________________________________________________ conv4_block36_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block36_1_conv[0][0] __________________________________________________________________________________________________ conv4_block36_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block36_1_bn[0][0] __________________________________________________________________________________________________ conv4_block36_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block36_1_relu[0][0] __________________________________________________________________________________________________ conv4_block36_concat (Concatena (None, 32, 32, 1408) 0 conv4_block35_concat[0][0] conv4_block36_2_conv[0][0] __________________________________________________________________________________________________ conv4_block37_0_bn (BatchNormal (None, 32, 32, 1408) 5632 conv4_block36_concat[0][0] __________________________________________________________________________________________________ conv4_block37_0_relu (Activatio (None, 32, 32, 1408) 0 conv4_block37_0_bn[0][0] __________________________________________________________________________________________________ conv4_block37_1_conv (Conv2D) (None, 32, 32, 128) 180224 conv4_block37_0_relu[0][0] __________________________________________________________________________________________________ conv4_block37_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block37_1_conv[0][0] __________________________________________________________________________________________________ conv4_block37_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block37_1_bn[0][0] __________________________________________________________________________________________________ conv4_block37_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block37_1_relu[0][0] __________________________________________________________________________________________________ conv4_block37_concat (Concatena (None, 32, 32, 1440) 0 conv4_block36_concat[0][0] conv4_block37_2_conv[0][0] __________________________________________________________________________________________________ conv4_block38_0_bn (BatchNormal (None, 32, 32, 1440) 5760 conv4_block37_concat[0][0] __________________________________________________________________________________________________ conv4_block38_0_relu (Activatio (None, 32, 32, 1440) 0 conv4_block38_0_bn[0][0] __________________________________________________________________________________________________ conv4_block38_1_conv (Conv2D) (None, 32, 32, 128) 184320 conv4_block38_0_relu[0][0] __________________________________________________________________________________________________ conv4_block38_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block38_1_conv[0][0] __________________________________________________________________________________________________ conv4_block38_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block38_1_bn[0][0] __________________________________________________________________________________________________ conv4_block38_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block38_1_relu[0][0] __________________________________________________________________________________________________ conv4_block38_concat (Concatena (None, 32, 32, 1472) 0 conv4_block37_concat[0][0] conv4_block38_2_conv[0][0] __________________________________________________________________________________________________ conv4_block39_0_bn (BatchNormal (None, 32, 32, 1472) 5888 conv4_block38_concat[0][0] __________________________________________________________________________________________________ conv4_block39_0_relu (Activatio (None, 32, 32, 1472) 0 conv4_block39_0_bn[0][0] __________________________________________________________________________________________________ conv4_block39_1_conv (Conv2D) (None, 32, 32, 128) 188416 conv4_block39_0_relu[0][0] __________________________________________________________________________________________________ conv4_block39_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block39_1_conv[0][0] __________________________________________________________________________________________________ conv4_block39_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block39_1_bn[0][0] __________________________________________________________________________________________________ conv4_block39_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block39_1_relu[0][0] __________________________________________________________________________________________________ conv4_block39_concat (Concatena (None, 32, 32, 1504) 0 conv4_block38_concat[0][0] conv4_block39_2_conv[0][0] __________________________________________________________________________________________________ conv4_block40_0_bn (BatchNormal (None, 32, 32, 1504) 6016 conv4_block39_concat[0][0] __________________________________________________________________________________________________ conv4_block40_0_relu (Activatio (None, 32, 32, 1504) 0 conv4_block40_0_bn[0][0] __________________________________________________________________________________________________ conv4_block40_1_conv (Conv2D) (None, 32, 32, 128) 192512 conv4_block40_0_relu[0][0] __________________________________________________________________________________________________ conv4_block40_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block40_1_conv[0][0] __________________________________________________________________________________________________ conv4_block40_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block40_1_bn[0][0] __________________________________________________________________________________________________ conv4_block40_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block40_1_relu[0][0] __________________________________________________________________________________________________ conv4_block40_concat (Concatena (None, 32, 32, 1536) 0 conv4_block39_concat[0][0] conv4_block40_2_conv[0][0] __________________________________________________________________________________________________ conv4_block41_0_bn (BatchNormal (None, 32, 32, 1536) 6144 conv4_block40_concat[0][0] __________________________________________________________________________________________________ conv4_block41_0_relu (Activatio (None, 32, 32, 1536) 0 conv4_block41_0_bn[0][0] __________________________________________________________________________________________________ conv4_block41_1_conv (Conv2D) (None, 32, 32, 128) 196608 conv4_block41_0_relu[0][0] __________________________________________________________________________________________________ conv4_block41_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block41_1_conv[0][0] __________________________________________________________________________________________________ conv4_block41_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block41_1_bn[0][0] __________________________________________________________________________________________________ conv4_block41_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block41_1_relu[0][0] __________________________________________________________________________________________________ conv4_block41_concat (Concatena (None, 32, 32, 1568) 0 conv4_block40_concat[0][0] conv4_block41_2_conv[0][0] __________________________________________________________________________________________________ conv4_block42_0_bn (BatchNormal (None, 32, 32, 1568) 6272 conv4_block41_concat[0][0] __________________________________________________________________________________________________ conv4_block42_0_relu (Activatio (None, 32, 32, 1568) 0 conv4_block42_0_bn[0][0] __________________________________________________________________________________________________ conv4_block42_1_conv (Conv2D) (None, 32, 32, 128) 200704 conv4_block42_0_relu[0][0] __________________________________________________________________________________________________ conv4_block42_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block42_1_conv[0][0] __________________________________________________________________________________________________ conv4_block42_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block42_1_bn[0][0] __________________________________________________________________________________________________ conv4_block42_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block42_1_relu[0][0] __________________________________________________________________________________________________ conv4_block42_concat (Concatena (None, 32, 32, 1600) 0 conv4_block41_concat[0][0] conv4_block42_2_conv[0][0] __________________________________________________________________________________________________ conv4_block43_0_bn (BatchNormal (None, 32, 32, 1600) 6400 conv4_block42_concat[0][0] __________________________________________________________________________________________________ conv4_block43_0_relu (Activatio (None, 32, 32, 1600) 0 conv4_block43_0_bn[0][0] __________________________________________________________________________________________________ conv4_block43_1_conv (Conv2D) (None, 32, 32, 128) 204800 conv4_block43_0_relu[0][0] __________________________________________________________________________________________________ conv4_block43_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block43_1_conv[0][0] __________________________________________________________________________________________________ conv4_block43_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block43_1_bn[0][0] __________________________________________________________________________________________________ conv4_block43_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block43_1_relu[0][0] __________________________________________________________________________________________________ conv4_block43_concat (Concatena (None, 32, 32, 1632) 0 conv4_block42_concat[0][0] conv4_block43_2_conv[0][0] __________________________________________________________________________________________________ conv4_block44_0_bn (BatchNormal (None, 32, 32, 1632) 6528 conv4_block43_concat[0][0] __________________________________________________________________________________________________ conv4_block44_0_relu (Activatio (None, 32, 32, 1632) 0 conv4_block44_0_bn[0][0] __________________________________________________________________________________________________ conv4_block44_1_conv (Conv2D) (None, 32, 32, 128) 208896 conv4_block44_0_relu[0][0] __________________________________________________________________________________________________ conv4_block44_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block44_1_conv[0][0] __________________________________________________________________________________________________ conv4_block44_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block44_1_bn[0][0] __________________________________________________________________________________________________ conv4_block44_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block44_1_relu[0][0] __________________________________________________________________________________________________ conv4_block44_concat (Concatena (None, 32, 32, 1664) 0 conv4_block43_concat[0][0] conv4_block44_2_conv[0][0] __________________________________________________________________________________________________ conv4_block45_0_bn (BatchNormal (None, 32, 32, 1664) 6656 conv4_block44_concat[0][0] __________________________________________________________________________________________________ conv4_block45_0_relu (Activatio (None, 32, 32, 1664) 0 conv4_block45_0_bn[0][0] __________________________________________________________________________________________________ conv4_block45_1_conv (Conv2D) (None, 32, 32, 128) 212992 conv4_block45_0_relu[0][0] __________________________________________________________________________________________________ conv4_block45_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block45_1_conv[0][0] __________________________________________________________________________________________________ conv4_block45_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block45_1_bn[0][0] __________________________________________________________________________________________________ conv4_block45_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block45_1_relu[0][0] __________________________________________________________________________________________________ conv4_block45_concat (Concatena (None, 32, 32, 1696) 0 conv4_block44_concat[0][0] conv4_block45_2_conv[0][0] __________________________________________________________________________________________________ conv4_block46_0_bn (BatchNormal (None, 32, 32, 1696) 6784 conv4_block45_concat[0][0] __________________________________________________________________________________________________ conv4_block46_0_relu (Activatio (None, 32, 32, 1696) 0 conv4_block46_0_bn[0][0] __________________________________________________________________________________________________ conv4_block46_1_conv (Conv2D) (None, 32, 32, 128) 217088 conv4_block46_0_relu[0][0] __________________________________________________________________________________________________ conv4_block46_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block46_1_conv[0][0] __________________________________________________________________________________________________ conv4_block46_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block46_1_bn[0][0] __________________________________________________________________________________________________ conv4_block46_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block46_1_relu[0][0] __________________________________________________________________________________________________ conv4_block46_concat (Concatena (None, 32, 32, 1728) 0 conv4_block45_concat[0][0] conv4_block46_2_conv[0][0] __________________________________________________________________________________________________ conv4_block47_0_bn (BatchNormal (None, 32, 32, 1728) 6912 conv4_block46_concat[0][0] __________________________________________________________________________________________________ conv4_block47_0_relu (Activatio (None, 32, 32, 1728) 0 conv4_block47_0_bn[0][0] __________________________________________________________________________________________________ conv4_block47_1_conv (Conv2D) (None, 32, 32, 128) 221184 conv4_block47_0_relu[0][0] __________________________________________________________________________________________________ conv4_block47_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block47_1_conv[0][0] __________________________________________________________________________________________________ conv4_block47_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block47_1_bn[0][0] __________________________________________________________________________________________________ conv4_block47_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block47_1_relu[0][0] __________________________________________________________________________________________________ conv4_block47_concat (Concatena (None, 32, 32, 1760) 0 conv4_block46_concat[0][0] conv4_block47_2_conv[0][0] __________________________________________________________________________________________________ conv4_block48_0_bn (BatchNormal (None, 32, 32, 1760) 7040 conv4_block47_concat[0][0] __________________________________________________________________________________________________ conv4_block48_0_relu (Activatio (None, 32, 32, 1760) 0 conv4_block48_0_bn[0][0] __________________________________________________________________________________________________ conv4_block48_1_conv (Conv2D) (None, 32, 32, 128) 225280 conv4_block48_0_relu[0][0] __________________________________________________________________________________________________ conv4_block48_1_bn (BatchNormal (None, 32, 32, 128) 512 conv4_block48_1_conv[0][0] __________________________________________________________________________________________________ conv4_block48_1_relu (Activatio (None, 32, 32, 128) 0 conv4_block48_1_bn[0][0] __________________________________________________________________________________________________ conv4_block48_2_conv (Conv2D) (None, 32, 32, 32) 36864 conv4_block48_1_relu[0][0] __________________________________________________________________________________________________ conv4_block48_concat (Concatena (None, 32, 32, 1792) 0 conv4_block47_concat[0][0] conv4_block48_2_conv[0][0] __________________________________________________________________________________________________ pool4_bn (BatchNormalization) (None, 32, 32, 1792) 7168 conv4_block48_concat[0][0] __________________________________________________________________________________________________ pool4_relu (Activation) (None, 32, 32, 1792) 0 pool4_bn[0][0] __________________________________________________________________________________________________ pool4_conv (Conv2D) (None, 32, 32, 896) 1605632 pool4_relu[0][0] __________________________________________________________________________________________________ pool4_pool (AveragePooling2D) (None, 16, 16, 896) 0 pool4_conv[0][0] __________________________________________________________________________________________________ conv5_block1_0_bn (BatchNormali (None, 16, 16, 896) 3584 pool4_pool[0][0] __________________________________________________________________________________________________ conv5_block1_0_relu (Activation (None, 16, 16, 896) 0 conv5_block1_0_bn[0][0] __________________________________________________________________________________________________ conv5_block1_1_conv (Conv2D) (None, 16, 16, 128) 114688 conv5_block1_0_relu[0][0] __________________________________________________________________________________________________ conv5_block1_1_bn (BatchNormali (None, 16, 16, 128) 512 conv5_block1_1_conv[0][0] __________________________________________________________________________________________________ conv5_block1_1_relu (Activation (None, 16, 16, 128) 0 conv5_block1_1_bn[0][0] __________________________________________________________________________________________________ conv5_block1_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block1_1_relu[0][0] __________________________________________________________________________________________________ conv5_block1_concat (Concatenat (None, 16, 16, 928) 0 pool4_pool[0][0] conv5_block1_2_conv[0][0] __________________________________________________________________________________________________ conv5_block2_0_bn (BatchNormali (None, 16, 16, 928) 3712 conv5_block1_concat[0][0] __________________________________________________________________________________________________ conv5_block2_0_relu (Activation (None, 16, 16, 928) 0 conv5_block2_0_bn[0][0] __________________________________________________________________________________________________ conv5_block2_1_conv (Conv2D) (None, 16, 16, 128) 118784 conv5_block2_0_relu[0][0] __________________________________________________________________________________________________ conv5_block2_1_bn (BatchNormali (None, 16, 16, 128) 512 conv5_block2_1_conv[0][0] __________________________________________________________________________________________________ conv5_block2_1_relu (Activation (None, 16, 16, 128) 0 conv5_block2_1_bn[0][0] __________________________________________________________________________________________________ conv5_block2_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block2_1_relu[0][0] __________________________________________________________________________________________________ conv5_block2_concat (Concatenat (None, 16, 16, 960) 0 conv5_block1_concat[0][0] conv5_block2_2_conv[0][0] __________________________________________________________________________________________________ conv5_block3_0_bn (BatchNormali (None, 16, 16, 960) 3840 conv5_block2_concat[0][0] __________________________________________________________________________________________________ conv5_block3_0_relu (Activation (None, 16, 16, 960) 0 conv5_block3_0_bn[0][0] __________________________________________________________________________________________________ conv5_block3_1_conv (Conv2D) (None, 16, 16, 128) 122880 conv5_block3_0_relu[0][0] __________________________________________________________________________________________________ conv5_block3_1_bn (BatchNormali (None, 16, 16, 128) 512 conv5_block3_1_conv[0][0] __________________________________________________________________________________________________ conv5_block3_1_relu (Activation (None, 16, 16, 128) 0 conv5_block3_1_bn[0][0] __________________________________________________________________________________________________ conv5_block3_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block3_1_relu[0][0] __________________________________________________________________________________________________ conv5_block3_concat (Concatenat (None, 16, 16, 992) 0 conv5_block2_concat[0][0] conv5_block3_2_conv[0][0] __________________________________________________________________________________________________ conv5_block4_0_bn (BatchNormali (None, 16, 16, 992) 3968 conv5_block3_concat[0][0] __________________________________________________________________________________________________ conv5_block4_0_relu (Activation (None, 16, 16, 992) 0 conv5_block4_0_bn[0][0] __________________________________________________________________________________________________ conv5_block4_1_conv (Conv2D) (None, 16, 16, 128) 126976 conv5_block4_0_relu[0][0] __________________________________________________________________________________________________ conv5_block4_1_bn (BatchNormali (None, 16, 16, 128) 512 conv5_block4_1_conv[0][0] __________________________________________________________________________________________________ conv5_block4_1_relu (Activation (None, 16, 16, 128) 0 conv5_block4_1_bn[0][0] __________________________________________________________________________________________________ conv5_block4_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block4_1_relu[0][0] __________________________________________________________________________________________________ conv5_block4_concat (Concatenat (None, 16, 16, 1024) 0 conv5_block3_concat[0][0] conv5_block4_2_conv[0][0] __________________________________________________________________________________________________ conv5_block5_0_bn (BatchNormali (None, 16, 16, 1024) 4096 conv5_block4_concat[0][0] __________________________________________________________________________________________________ conv5_block5_0_relu (Activation (None, 16, 16, 1024) 0 conv5_block5_0_bn[0][0] __________________________________________________________________________________________________ conv5_block5_1_conv (Conv2D) (None, 16, 16, 128) 131072 conv5_block5_0_relu[0][0] __________________________________________________________________________________________________ conv5_block5_1_bn (BatchNormali (None, 16, 16, 128) 512 conv5_block5_1_conv[0][0] __________________________________________________________________________________________________ conv5_block5_1_relu (Activation (None, 16, 16, 128) 0 conv5_block5_1_bn[0][0] __________________________________________________________________________________________________ conv5_block5_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block5_1_relu[0][0] __________________________________________________________________________________________________ conv5_block5_concat (Concatenat (None, 16, 16, 1056) 0 conv5_block4_concat[0][0] conv5_block5_2_conv[0][0] __________________________________________________________________________________________________ conv5_block6_0_bn (BatchNormali (None, 16, 16, 1056) 4224 conv5_block5_concat[0][0] __________________________________________________________________________________________________ conv5_block6_0_relu (Activation (None, 16, 16, 1056) 0 conv5_block6_0_bn[0][0] __________________________________________________________________________________________________ conv5_block6_1_conv (Conv2D) (None, 16, 16, 128) 135168 conv5_block6_0_relu[0][0] __________________________________________________________________________________________________ conv5_block6_1_bn (BatchNormali (None, 16, 16, 128) 512 conv5_block6_1_conv[0][0] __________________________________________________________________________________________________ conv5_block6_1_relu (Activation (None, 16, 16, 128) 0 conv5_block6_1_bn[0][0] __________________________________________________________________________________________________ conv5_block6_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block6_1_relu[0][0] __________________________________________________________________________________________________ conv5_block6_concat (Concatenat (None, 16, 16, 1088) 0 conv5_block5_concat[0][0] conv5_block6_2_conv[0][0] __________________________________________________________________________________________________ conv5_block7_0_bn (BatchNormali (None, 16, 16, 1088) 4352 conv5_block6_concat[0][0] __________________________________________________________________________________________________ conv5_block7_0_relu (Activation (None, 16, 16, 1088) 0 conv5_block7_0_bn[0][0] __________________________________________________________________________________________________ conv5_block7_1_conv (Conv2D) (None, 16, 16, 128) 139264 conv5_block7_0_relu[0][0] __________________________________________________________________________________________________ conv5_block7_1_bn (BatchNormali (None, 16, 16, 128) 512 conv5_block7_1_conv[0][0] __________________________________________________________________________________________________ conv5_block7_1_relu (Activation (None, 16, 16, 128) 0 conv5_block7_1_bn[0][0] __________________________________________________________________________________________________ conv5_block7_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block7_1_relu[0][0] __________________________________________________________________________________________________ conv5_block7_concat (Concatenat (None, 16, 16, 1120) 0 conv5_block6_concat[0][0] conv5_block7_2_conv[0][0] __________________________________________________________________________________________________ conv5_block8_0_bn (BatchNormali (None, 16, 16, 1120) 4480 conv5_block7_concat[0][0] __________________________________________________________________________________________________ conv5_block8_0_relu (Activation (None, 16, 16, 1120) 0 conv5_block8_0_bn[0][0] __________________________________________________________________________________________________ conv5_block8_1_conv (Conv2D) (None, 16, 16, 128) 143360 conv5_block8_0_relu[0][0] __________________________________________________________________________________________________ conv5_block8_1_bn (BatchNormali (None, 16, 16, 128) 512 conv5_block8_1_conv[0][0] __________________________________________________________________________________________________ conv5_block8_1_relu (Activation (None, 16, 16, 128) 0 conv5_block8_1_bn[0][0] __________________________________________________________________________________________________ conv5_block8_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block8_1_relu[0][0] __________________________________________________________________________________________________ conv5_block8_concat (Concatenat (None, 16, 16, 1152) 0 conv5_block7_concat[0][0] conv5_block8_2_conv[0][0] __________________________________________________________________________________________________ conv5_block9_0_bn (BatchNormali (None, 16, 16, 1152) 4608 conv5_block8_concat[0][0] __________________________________________________________________________________________________ conv5_block9_0_relu (Activation (None, 16, 16, 1152) 0 conv5_block9_0_bn[0][0] __________________________________________________________________________________________________ conv5_block9_1_conv (Conv2D) (None, 16, 16, 128) 147456 conv5_block9_0_relu[0][0] __________________________________________________________________________________________________ conv5_block9_1_bn (BatchNormali (None, 16, 16, 128) 512 conv5_block9_1_conv[0][0] __________________________________________________________________________________________________ conv5_block9_1_relu (Activation (None, 16, 16, 128) 0 conv5_block9_1_bn[0][0] __________________________________________________________________________________________________ conv5_block9_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block9_1_relu[0][0] __________________________________________________________________________________________________ conv5_block9_concat (Concatenat (None, 16, 16, 1184) 0 conv5_block8_concat[0][0] conv5_block9_2_conv[0][0] __________________________________________________________________________________________________ conv5_block10_0_bn (BatchNormal (None, 16, 16, 1184) 4736 conv5_block9_concat[0][0] __________________________________________________________________________________________________ conv5_block10_0_relu (Activatio (None, 16, 16, 1184) 0 conv5_block10_0_bn[0][0] __________________________________________________________________________________________________ conv5_block10_1_conv (Conv2D) (None, 16, 16, 128) 151552 conv5_block10_0_relu[0][0] __________________________________________________________________________________________________ conv5_block10_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block10_1_conv[0][0] __________________________________________________________________________________________________ conv5_block10_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block10_1_bn[0][0] __________________________________________________________________________________________________ conv5_block10_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block10_1_relu[0][0] __________________________________________________________________________________________________ conv5_block10_concat (Concatena (None, 16, 16, 1216) 0 conv5_block9_concat[0][0] conv5_block10_2_conv[0][0] __________________________________________________________________________________________________ conv5_block11_0_bn (BatchNormal (None, 16, 16, 1216) 4864 conv5_block10_concat[0][0] __________________________________________________________________________________________________ conv5_block11_0_relu (Activatio (None, 16, 16, 1216) 0 conv5_block11_0_bn[0][0] __________________________________________________________________________________________________ conv5_block11_1_conv (Conv2D) (None, 16, 16, 128) 155648 conv5_block11_0_relu[0][0] __________________________________________________________________________________________________ conv5_block11_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block11_1_conv[0][0] __________________________________________________________________________________________________ conv5_block11_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block11_1_bn[0][0] __________________________________________________________________________________________________ conv5_block11_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block11_1_relu[0][0] __________________________________________________________________________________________________ conv5_block11_concat (Concatena (None, 16, 16, 1248) 0 conv5_block10_concat[0][0] conv5_block11_2_conv[0][0] __________________________________________________________________________________________________ conv5_block12_0_bn (BatchNormal (None, 16, 16, 1248) 4992 conv5_block11_concat[0][0] __________________________________________________________________________________________________ conv5_block12_0_relu (Activatio (None, 16, 16, 1248) 0 conv5_block12_0_bn[0][0] __________________________________________________________________________________________________ conv5_block12_1_conv (Conv2D) (None, 16, 16, 128) 159744 conv5_block12_0_relu[0][0] __________________________________________________________________________________________________ conv5_block12_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block12_1_conv[0][0] __________________________________________________________________________________________________ conv5_block12_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block12_1_bn[0][0] __________________________________________________________________________________________________ conv5_block12_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block12_1_relu[0][0] __________________________________________________________________________________________________ conv5_block12_concat (Concatena (None, 16, 16, 1280) 0 conv5_block11_concat[0][0] conv5_block12_2_conv[0][0] __________________________________________________________________________________________________ conv5_block13_0_bn (BatchNormal (None, 16, 16, 1280) 5120 conv5_block12_concat[0][0] __________________________________________________________________________________________________ conv5_block13_0_relu (Activatio (None, 16, 16, 1280) 0 conv5_block13_0_bn[0][0] __________________________________________________________________________________________________ conv5_block13_1_conv (Conv2D) (None, 16, 16, 128) 163840 conv5_block13_0_relu[0][0] __________________________________________________________________________________________________ conv5_block13_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block13_1_conv[0][0] __________________________________________________________________________________________________ conv5_block13_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block13_1_bn[0][0] __________________________________________________________________________________________________ conv5_block13_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block13_1_relu[0][0] __________________________________________________________________________________________________ conv5_block13_concat (Concatena (None, 16, 16, 1312) 0 conv5_block12_concat[0][0] conv5_block13_2_conv[0][0] __________________________________________________________________________________________________ conv5_block14_0_bn (BatchNormal (None, 16, 16, 1312) 5248 conv5_block13_concat[0][0] __________________________________________________________________________________________________ conv5_block14_0_relu (Activatio (None, 16, 16, 1312) 0 conv5_block14_0_bn[0][0] __________________________________________________________________________________________________ conv5_block14_1_conv (Conv2D) (None, 16, 16, 128) 167936 conv5_block14_0_relu[0][0] __________________________________________________________________________________________________ conv5_block14_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block14_1_conv[0][0] __________________________________________________________________________________________________ conv5_block14_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block14_1_bn[0][0] __________________________________________________________________________________________________ conv5_block14_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block14_1_relu[0][0] __________________________________________________________________________________________________ conv5_block14_concat (Concatena (None, 16, 16, 1344) 0 conv5_block13_concat[0][0] conv5_block14_2_conv[0][0] __________________________________________________________________________________________________ conv5_block15_0_bn (BatchNormal (None, 16, 16, 1344) 5376 conv5_block14_concat[0][0] __________________________________________________________________________________________________ conv5_block15_0_relu (Activatio (None, 16, 16, 1344) 0 conv5_block15_0_bn[0][0] __________________________________________________________________________________________________ conv5_block15_1_conv (Conv2D) (None, 16, 16, 128) 172032 conv5_block15_0_relu[0][0] __________________________________________________________________________________________________ conv5_block15_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block15_1_conv[0][0] __________________________________________________________________________________________________ conv5_block15_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block15_1_bn[0][0] __________________________________________________________________________________________________ conv5_block15_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block15_1_relu[0][0] __________________________________________________________________________________________________ conv5_block15_concat (Concatena (None, 16, 16, 1376) 0 conv5_block14_concat[0][0] conv5_block15_2_conv[0][0] __________________________________________________________________________________________________ conv5_block16_0_bn (BatchNormal (None, 16, 16, 1376) 5504 conv5_block15_concat[0][0] __________________________________________________________________________________________________ conv5_block16_0_relu (Activatio (None, 16, 16, 1376) 0 conv5_block16_0_bn[0][0] __________________________________________________________________________________________________ conv5_block16_1_conv (Conv2D) (None, 16, 16, 128) 176128 conv5_block16_0_relu[0][0] __________________________________________________________________________________________________ conv5_block16_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block16_1_conv[0][0] __________________________________________________________________________________________________ conv5_block16_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block16_1_bn[0][0] __________________________________________________________________________________________________ conv5_block16_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block16_1_relu[0][0] __________________________________________________________________________________________________ conv5_block16_concat (Concatena (None, 16, 16, 1408) 0 conv5_block15_concat[0][0] conv5_block16_2_conv[0][0] __________________________________________________________________________________________________ conv5_block17_0_bn (BatchNormal (None, 16, 16, 1408) 5632 conv5_block16_concat[0][0] __________________________________________________________________________________________________ conv5_block17_0_relu (Activatio (None, 16, 16, 1408) 0 conv5_block17_0_bn[0][0] __________________________________________________________________________________________________ conv5_block17_1_conv (Conv2D) (None, 16, 16, 128) 180224 conv5_block17_0_relu[0][0] __________________________________________________________________________________________________ conv5_block17_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block17_1_conv[0][0] __________________________________________________________________________________________________ conv5_block17_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block17_1_bn[0][0] __________________________________________________________________________________________________ conv5_block17_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block17_1_relu[0][0] __________________________________________________________________________________________________ conv5_block17_concat (Concatena (None, 16, 16, 1440) 0 conv5_block16_concat[0][0] conv5_block17_2_conv[0][0] __________________________________________________________________________________________________ conv5_block18_0_bn (BatchNormal (None, 16, 16, 1440) 5760 conv5_block17_concat[0][0] __________________________________________________________________________________________________ conv5_block18_0_relu (Activatio (None, 16, 16, 1440) 0 conv5_block18_0_bn[0][0] __________________________________________________________________________________________________ conv5_block18_1_conv (Conv2D) (None, 16, 16, 128) 184320 conv5_block18_0_relu[0][0] __________________________________________________________________________________________________ conv5_block18_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block18_1_conv[0][0] __________________________________________________________________________________________________ conv5_block18_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block18_1_bn[0][0] __________________________________________________________________________________________________ conv5_block18_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block18_1_relu[0][0] __________________________________________________________________________________________________ conv5_block18_concat (Concatena (None, 16, 16, 1472) 0 conv5_block17_concat[0][0] conv5_block18_2_conv[0][0] __________________________________________________________________________________________________ conv5_block19_0_bn (BatchNormal (None, 16, 16, 1472) 5888 conv5_block18_concat[0][0] __________________________________________________________________________________________________ conv5_block19_0_relu (Activatio (None, 16, 16, 1472) 0 conv5_block19_0_bn[0][0] __________________________________________________________________________________________________ conv5_block19_1_conv (Conv2D) (None, 16, 16, 128) 188416 conv5_block19_0_relu[0][0] __________________________________________________________________________________________________ conv5_block19_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block19_1_conv[0][0] __________________________________________________________________________________________________ conv5_block19_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block19_1_bn[0][0] __________________________________________________________________________________________________ conv5_block19_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block19_1_relu[0][0] __________________________________________________________________________________________________ conv5_block19_concat (Concatena (None, 16, 16, 1504) 0 conv5_block18_concat[0][0] conv5_block19_2_conv[0][0] __________________________________________________________________________________________________ conv5_block20_0_bn (BatchNormal (None, 16, 16, 1504) 6016 conv5_block19_concat[0][0] __________________________________________________________________________________________________ conv5_block20_0_relu (Activatio (None, 16, 16, 1504) 0 conv5_block20_0_bn[0][0] __________________________________________________________________________________________________ conv5_block20_1_conv (Conv2D) (None, 16, 16, 128) 192512 conv5_block20_0_relu[0][0] __________________________________________________________________________________________________ conv5_block20_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block20_1_conv[0][0] __________________________________________________________________________________________________ conv5_block20_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block20_1_bn[0][0] __________________________________________________________________________________________________ conv5_block20_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block20_1_relu[0][0] __________________________________________________________________________________________________ conv5_block20_concat (Concatena (None, 16, 16, 1536) 0 conv5_block19_concat[0][0] conv5_block20_2_conv[0][0] __________________________________________________________________________________________________ conv5_block21_0_bn (BatchNormal (None, 16, 16, 1536) 6144 conv5_block20_concat[0][0] __________________________________________________________________________________________________ conv5_block21_0_relu (Activatio (None, 16, 16, 1536) 0 conv5_block21_0_bn[0][0] __________________________________________________________________________________________________ conv5_block21_1_conv (Conv2D) (None, 16, 16, 128) 196608 conv5_block21_0_relu[0][0] __________________________________________________________________________________________________ conv5_block21_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block21_1_conv[0][0] __________________________________________________________________________________________________ conv5_block21_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block21_1_bn[0][0] __________________________________________________________________________________________________ conv5_block21_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block21_1_relu[0][0] __________________________________________________________________________________________________ conv5_block21_concat (Concatena (None, 16, 16, 1568) 0 conv5_block20_concat[0][0] conv5_block21_2_conv[0][0] __________________________________________________________________________________________________ conv5_block22_0_bn (BatchNormal (None, 16, 16, 1568) 6272 conv5_block21_concat[0][0] __________________________________________________________________________________________________ conv5_block22_0_relu (Activatio (None, 16, 16, 1568) 0 conv5_block22_0_bn[0][0] __________________________________________________________________________________________________ conv5_block22_1_conv (Conv2D) (None, 16, 16, 128) 200704 conv5_block22_0_relu[0][0] __________________________________________________________________________________________________ conv5_block22_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block22_1_conv[0][0] __________________________________________________________________________________________________ conv5_block22_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block22_1_bn[0][0] __________________________________________________________________________________________________ conv5_block22_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block22_1_relu[0][0] __________________________________________________________________________________________________ conv5_block22_concat (Concatena (None, 16, 16, 1600) 0 conv5_block21_concat[0][0] conv5_block22_2_conv[0][0] __________________________________________________________________________________________________ conv5_block23_0_bn (BatchNormal (None, 16, 16, 1600) 6400 conv5_block22_concat[0][0] __________________________________________________________________________________________________ conv5_block23_0_relu (Activatio (None, 16, 16, 1600) 0 conv5_block23_0_bn[0][0] __________________________________________________________________________________________________ conv5_block23_1_conv (Conv2D) (None, 16, 16, 128) 204800 conv5_block23_0_relu[0][0] __________________________________________________________________________________________________ conv5_block23_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block23_1_conv[0][0] __________________________________________________________________________________________________ conv5_block23_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block23_1_bn[0][0] __________________________________________________________________________________________________ conv5_block23_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block23_1_relu[0][0] __________________________________________________________________________________________________ conv5_block23_concat (Concatena (None, 16, 16, 1632) 0 conv5_block22_concat[0][0] conv5_block23_2_conv[0][0] __________________________________________________________________________________________________ conv5_block24_0_bn (BatchNormal (None, 16, 16, 1632) 6528 conv5_block23_concat[0][0] __________________________________________________________________________________________________ conv5_block24_0_relu (Activatio (None, 16, 16, 1632) 0 conv5_block24_0_bn[0][0] __________________________________________________________________________________________________ conv5_block24_1_conv (Conv2D) (None, 16, 16, 128) 208896 conv5_block24_0_relu[0][0] __________________________________________________________________________________________________ conv5_block24_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block24_1_conv[0][0] __________________________________________________________________________________________________ conv5_block24_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block24_1_bn[0][0] __________________________________________________________________________________________________ conv5_block24_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block24_1_relu[0][0] __________________________________________________________________________________________________ conv5_block24_concat (Concatena (None, 16, 16, 1664) 0 conv5_block23_concat[0][0] conv5_block24_2_conv[0][0] __________________________________________________________________________________________________ conv5_block25_0_bn (BatchNormal (None, 16, 16, 1664) 6656 conv5_block24_concat[0][0] __________________________________________________________________________________________________ conv5_block25_0_relu (Activatio (None, 16, 16, 1664) 0 conv5_block25_0_bn[0][0] __________________________________________________________________________________________________ conv5_block25_1_conv (Conv2D) (None, 16, 16, 128) 212992 conv5_block25_0_relu[0][0] __________________________________________________________________________________________________ conv5_block25_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block25_1_conv[0][0] __________________________________________________________________________________________________ conv5_block25_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block25_1_bn[0][0] __________________________________________________________________________________________________ conv5_block25_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block25_1_relu[0][0] __________________________________________________________________________________________________ conv5_block25_concat (Concatena (None, 16, 16, 1696) 0 conv5_block24_concat[0][0] conv5_block25_2_conv[0][0] __________________________________________________________________________________________________ conv5_block26_0_bn (BatchNormal (None, 16, 16, 1696) 6784 conv5_block25_concat[0][0] __________________________________________________________________________________________________ conv5_block26_0_relu (Activatio (None, 16, 16, 1696) 0 conv5_block26_0_bn[0][0] __________________________________________________________________________________________________ conv5_block26_1_conv (Conv2D) (None, 16, 16, 128) 217088 conv5_block26_0_relu[0][0] __________________________________________________________________________________________________ conv5_block26_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block26_1_conv[0][0] __________________________________________________________________________________________________ conv5_block26_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block26_1_bn[0][0] __________________________________________________________________________________________________ conv5_block26_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block26_1_relu[0][0] __________________________________________________________________________________________________ conv5_block26_concat (Concatena (None, 16, 16, 1728) 0 conv5_block25_concat[0][0] conv5_block26_2_conv[0][0] __________________________________________________________________________________________________ conv5_block27_0_bn (BatchNormal (None, 16, 16, 1728) 6912 conv5_block26_concat[0][0] __________________________________________________________________________________________________ conv5_block27_0_relu (Activatio (None, 16, 16, 1728) 0 conv5_block27_0_bn[0][0] __________________________________________________________________________________________________ conv5_block27_1_conv (Conv2D) (None, 16, 16, 128) 221184 conv5_block27_0_relu[0][0] __________________________________________________________________________________________________ conv5_block27_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block27_1_conv[0][0] __________________________________________________________________________________________________ conv5_block27_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block27_1_bn[0][0] __________________________________________________________________________________________________ conv5_block27_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block27_1_relu[0][0] __________________________________________________________________________________________________ conv5_block27_concat (Concatena (None, 16, 16, 1760) 0 conv5_block26_concat[0][0] conv5_block27_2_conv[0][0] __________________________________________________________________________________________________ conv5_block28_0_bn (BatchNormal (None, 16, 16, 1760) 7040 conv5_block27_concat[0][0] __________________________________________________________________________________________________ conv5_block28_0_relu (Activatio (None, 16, 16, 1760) 0 conv5_block28_0_bn[0][0] __________________________________________________________________________________________________ conv5_block28_1_conv (Conv2D) (None, 16, 16, 128) 225280 conv5_block28_0_relu[0][0] __________________________________________________________________________________________________ conv5_block28_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block28_1_conv[0][0] __________________________________________________________________________________________________ conv5_block28_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block28_1_bn[0][0] __________________________________________________________________________________________________ conv5_block28_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block28_1_relu[0][0] __________________________________________________________________________________________________ conv5_block28_concat (Concatena (None, 16, 16, 1792) 0 conv5_block27_concat[0][0] conv5_block28_2_conv[0][0] __________________________________________________________________________________________________ conv5_block29_0_bn (BatchNormal (None, 16, 16, 1792) 7168 conv5_block28_concat[0][0] __________________________________________________________________________________________________ conv5_block29_0_relu (Activatio (None, 16, 16, 1792) 0 conv5_block29_0_bn[0][0] __________________________________________________________________________________________________ conv5_block29_1_conv (Conv2D) (None, 16, 16, 128) 229376 conv5_block29_0_relu[0][0] __________________________________________________________________________________________________ conv5_block29_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block29_1_conv[0][0] __________________________________________________________________________________________________ conv5_block29_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block29_1_bn[0][0] __________________________________________________________________________________________________ conv5_block29_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block29_1_relu[0][0] __________________________________________________________________________________________________ conv5_block29_concat (Concatena (None, 16, 16, 1824) 0 conv5_block28_concat[0][0] conv5_block29_2_conv[0][0] __________________________________________________________________________________________________ conv5_block30_0_bn (BatchNormal (None, 16, 16, 1824) 7296 conv5_block29_concat[0][0] __________________________________________________________________________________________________ conv5_block30_0_relu (Activatio (None, 16, 16, 1824) 0 conv5_block30_0_bn[0][0] __________________________________________________________________________________________________ conv5_block30_1_conv (Conv2D) (None, 16, 16, 128) 233472 conv5_block30_0_relu[0][0] __________________________________________________________________________________________________ conv5_block30_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block30_1_conv[0][0] __________________________________________________________________________________________________ conv5_block30_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block30_1_bn[0][0] __________________________________________________________________________________________________ conv5_block30_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block30_1_relu[0][0] __________________________________________________________________________________________________ conv5_block30_concat (Concatena (None, 16, 16, 1856) 0 conv5_block29_concat[0][0] conv5_block30_2_conv[0][0] __________________________________________________________________________________________________ conv5_block31_0_bn (BatchNormal (None, 16, 16, 1856) 7424 conv5_block30_concat[0][0] __________________________________________________________________________________________________ conv5_block31_0_relu (Activatio (None, 16, 16, 1856) 0 conv5_block31_0_bn[0][0] __________________________________________________________________________________________________ conv5_block31_1_conv (Conv2D) (None, 16, 16, 128) 237568 conv5_block31_0_relu[0][0] __________________________________________________________________________________________________ conv5_block31_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block31_1_conv[0][0] __________________________________________________________________________________________________ conv5_block31_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block31_1_bn[0][0] __________________________________________________________________________________________________ conv5_block31_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block31_1_relu[0][0] __________________________________________________________________________________________________ conv5_block31_concat (Concatena (None, 16, 16, 1888) 0 conv5_block30_concat[0][0] conv5_block31_2_conv[0][0] __________________________________________________________________________________________________ conv5_block32_0_bn (BatchNormal (None, 16, 16, 1888) 7552 conv5_block31_concat[0][0] __________________________________________________________________________________________________ conv5_block32_0_relu (Activatio (None, 16, 16, 1888) 0 conv5_block32_0_bn[0][0] __________________________________________________________________________________________________ conv5_block32_1_conv (Conv2D) (None, 16, 16, 128) 241664 conv5_block32_0_relu[0][0] __________________________________________________________________________________________________ conv5_block32_1_bn (BatchNormal (None, 16, 16, 128) 512 conv5_block32_1_conv[0][0] __________________________________________________________________________________________________ conv5_block32_1_relu (Activatio (None, 16, 16, 128) 0 conv5_block32_1_bn[0][0] __________________________________________________________________________________________________ conv5_block32_2_conv (Conv2D) (None, 16, 16, 32) 36864 conv5_block32_1_relu[0][0] __________________________________________________________________________________________________ conv5_block32_concat (Concatena (None, 16, 16, 1920) 0 conv5_block31_concat[0][0] conv5_block32_2_conv[0][0] __________________________________________________________________________________________________ bn (BatchNormalization) (None, 16, 16, 1920) 7680 conv5_block32_concat[0][0] __________________________________________________________________________________________________ relu (Activation) (None, 16, 16, 1920) 0 bn[0][0] __________________________________________________________________________________________________ avg_pool (GlobalAveragePooling2 (None, 1920) 0 relu[0][0] __________________________________________________________________________________________________ fc1000 (Dense) (None, 1000) 1921000 avg_pool[0][0] ================================================================================================== Total params: 20,242,984 Trainable params: 20,013,928 Non-trainable params: 229,056 __________________________________________________________________________________________________ Process finished with exit code 0
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densenet 201 weights
2018-12-02 12:31:53DenseNet在ResNet的基础上(ResNet介绍),进一步扩展网络连接,对于网络的任意一层,该层前面所有层的feature map都是这层的输入,该层的feature map是后面所有层的输入。优点:减轻了梯度消失问题(vanishing-... -
densenet201_weights_tf_dim_ordering_tf_kernels_notop.h5
2018-11-23 21:46:36densenet201_weights_tf_dim_ordering_tf_kernels_notop.h5, keras预训练模型,densenet201 -
densenet201.mlpkginstall
2020-11-03 12:45:08迁移学习(Transfer Learning):Matlab预训练模型的原始安装程序,用于特征提取、表达、目标识别等诸多任务 -
tensorflow+keras+densenet201问题-解决办法
2021-03-21 17:18:40Tensor(“conv1/conv/kernel:0”, shape=(7, 7, 3, 64), dtype=float32_ref) must be from the same graph as Tensor(“densenet201/zero_padding2d_1/Pad:0”, shape=(?, 230, 230, 3), dtype=float32). 这个bug...Tensor(“conv1/conv/kernel:0”, shape=(7, 7, 3, 64), dtype=float32_ref) must be from the same graph as Tensor(“densenet201/zero_padding2d_1/Pad:0”, shape=(?, 230, 230, 3), dtype=float32).
这个bug已经卡了我好几天了,网上查找解决办法,好多都没啥用,列几个对我比较有帮助的参考博客。
- https://blog.csdn.net/llsplsp/article/details/105420453
- https://blog.csdn.net/weixin_39326879/article/details/108832107?utm_medium=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-9.control&dist_request_id=&depth_1-utm_source=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-9.control
看了些文章,都是说计算图的问题,现在解决了这个问题,由冒出了另外的问题,OMG才疏浅学啊,到处都是BUG。
千万不要随便乱升级pip,现在我pip出大问题了,一团糟呜呜。
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PermissionError: [Errno 13] Permission denied: ‘/home/user/.torch/models/densenet201-c1103571.pth
2021-04-13 15:25:32运行 haze_class = models.densenet201(pretrained=True)时出现以下错误: PermissionError: [Errno 13] Permission denied: '/home/user/.torch/models/densenet201-c1103571.pth' 在网上搜了一下原因可能是这个...运行 haze_class = models.densenet201(pretrained=True)时出现以下错误:
PermissionError: [Errno 13] Permission denied: '/home/user/.torch/models/densenet201-c1103571.pth'
在网上搜了一下原因可能是这个文件夹可能不存在,亦或者路径错了
但修改路径后仍有这种错误
试了一下运行python时前面加sudo 问题解决 -
densenet201_weights_tf_dim_ordering_tf_kernels.h5
2020-02-26 20:57:36model weight in this repo https://github.com/fchollet/deep-learning-models Keras提供的预训练权重 -
细粒度车型识别项目(基于DenseNet201, 数据集Stanfordcars-196,准确率:94.13%)
2020-11-25 11:00:23之前做的一个细粒度车型识别项目, 数据集:斯坦福大学公开细粒度车型识别数据集,196类; 测试准确率达到94.13%。 深度学习框架:pytorch ...下面是部分代码文件,有需要的联系我:wx:... -
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DenseNet-201 (k=32) 22.5 Download (161.8MB) DenseNet-161 (k=48) 22.2 Download (230.8MB) Models in the tech report More accurate models trained with the memory efficient implementation in the ...
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Densenet.rar
2020-06-02 17:56:17Densnet121,Densenet169,Densenet201,预训练模型,适合Keras库,包括有notop的和无notop的。CSDN上传最大只能480M,后续的模型将陆续上传,GitHub限速,搬的好累,搬了好几天。放到CSDN上,方便大家快速下载。 -
DenseNet的Keras代码实现
2020-04-02 13:30:19下面代码显示了如何使用keras实现DenseNet网络 DenseNet121 : dense_block == [6, 12, 24, 16] ...DenseNet201 : dense_block == [6, 12, 48, 32] 下面举了一个DenseNet201 的例子 import os from... -
DenseNet-caffe
2019-08-07 15:46:41https://github.com/shicai/DenseNet-Caffe DenseNet_161.prototxt DenseNet_121.prototxt DenseNet_169.prototxt DenseNet_201.prototxt -
Problem to train densenet and mobilenet models
2021-01-10 12:36:40densenet201 --epochs=1 --steps=1 --no-weights coco /home/manuelvazquezenriquez2/keras-retinanet-test-data/coco loading annotations into memory... Done (t=0.00s) creating index... index ... -
[pytorch源码解读]之DenseNet的源码解读
2020-04-24 17:39:24所以DenseNet一共有DenseNet-121,DenseNet-169,DenseNet-201和DenseNet-264 四种实现方式。 拿DenseNet-121为例,121表示的是卷积层和全连接层加起来的数目(一共120个卷积层,1个全连接层) ... -
AI实战:pytorch、 tensorflow 对比之推理时性能、GPU占用对比(一):DenseNet
2020-06-21 08:14:26DenseNet定义 论文链接:Densely Connected Convolutional Networks 参考:深度/机器学习基础知识要点:CNN、ResNet、DenseNet DenseNet参数 参数情况 flops 对比DensetNet201在pytorch、tensorflow的情况 ... -
Dense Layers
2020-12-08 23:04:18<p>In training DenseNet Model: Q1) there is a parameter --depth, if it is set to "--depth 201", does it also mean it will have 201 layers? if depth=201, stages= [6, 12, 48, 32], what... -
DenseNet201 224 77.320 93.620 20.2M 18.3M [paper] [torch] NASNetLarge 331 82.498 96.004 93.5M 84.9M [paper] [tf-models] NASNetMobile 224 74.366 91.854 7.7M 4.3M [paper] [tf-models] ...
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Pytorch预训练模型
2019-07-22 16:44:52Pytorch预训练模型 Pytorch支持预训练的模型如下 Fromtorchvisionpackage: ResNet (resnet18,resnet34,resnet50,resnet101,... DenseNet (densenet121,densenet169,densenet201,densenet161) Inception v3 (in... -
keras 输出网络结构_keras查看网络结构
2020-12-24 16:10:13最近想使用DenseNet做特征提取,但是不知道DenseNet具体...# -*- coding: utf-8 -*-from keras.applications.densenet import DenseNet201,preprocess_inputfrom keras.models import Model,load_modelimport nump... -
kaggle项目TPUs调试记录
2020-11-16 15:21:52from tensorflow.keras.applications import DenseNet201 def get_model(): with strategy.scope(): rnet = DenseNet201( input_shape=(IMAGE_SIZE[0], IMAGE_SIZE[1], 3), weights='imagenet', include_top=... -
keras查看网络结构
2019-03-18 11:45:19最近想使用DenseNet做特征提取,但是不知道DenseNet具体结构,... # -*- coding: utf-8 -*- """ Created on Tue Feb 19 13:35:11 2019 ...from keras.applications.densenet import DenseNet201,pre... -
darknet-yolov3中python接口测试过程(从图片到网络再到返回结果)
2019-07-17 15:40:34首先从darknet.py中main函数出发,如下: if __name__ == "__... #net = load_net("cfg/densenet201.cfg", "/home/pjreddie/trained/densenet201.weights", 0) #im = load_image("data/wolf.jpg", 0, 0) #met... -
darknet 可视化yolo损失曲线
2018-04-17 12:55:45保存日志命令:/darknet detector train my/mot/person.data my/mot/densenet201_yolo.cfg backup/mot/densenet201_yolo_final.weights >> log/mot-ramdon.logpython可视化代码:#plot.py import ... -
Tensorflow2 使用经典的模型
2020-02-04 12:11:39import tensorflow as tf from tensorflow.keras import applications """ keras.applications 中共有以下模型 DenseNet121(...) ...DenseNet201(...) InceptionResNetV2(...) InceptionV3(...) MobileNet... -
【医学+深度论文:F25】2018 CVPR Enhanced Optic Disk and Cup Segmentation with Glaucoma Screening ...
2019-07-31 10:50:5625 2018 CVPR Enhanced Optic Disk and Cup Segmentation with Glaucoma Screening from Fundus Images using Position encoded CNNs Method : 分割 + 分类 ...Architecture : Unet(DenseNet)+ DenseNet201/ResN... -
ReID Baseline
2019-05-10 19:30:25大佬的Baseline 新加densenet201作为backbone top1:0.922209 top5:0.956354 top10:0.967933 mAP:0.868049
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