The pruning ratio is very low, as shown below:
When I retrain the pruned model, its file size is the same as before pruned,the trainable parameters are as follows:
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) (None, 3, 1168, 720) 0
__________________________________________________________________________________________________
conv1 (Conv2D) (None, 64, 584, 360) 9472 input_1[0][0]
__________________________________________________________________________________________________
bn_conv1 (BatchNormalization) (None, 64, 584, 360) 256 conv1[0][0]
__________________________________________________________________________________________________
activation_1 (Activation) (None, 64, 584, 360) 0 bn_conv1[0][0]
__________________________________________________________________________________________________
block_1a_conv_1 (Conv2D) (None, 64, 292, 180) 36928 activation_1[0][0]
__________________________________________________________________________________________________
block_1a_bn_1 (BatchNormalizati (None, 64, 292, 180) 256 block_1a_conv_1[0][0]
__________________________________________________________________________________________________
block_1a_relu_1 (Activation) (None, 64, 292, 180) 0 block_1a_bn_1[0][0]
__________________________________________________________________________________________________
block_1a_conv_2 (Conv2D) (None, 64, 292, 180) 36928 block_1a_relu_1[0][0]
__________________________________________________________________________________________________
block_1a_conv_shortcut (Conv2D) (None, 64, 292, 180) 4160 activation_1[0][0]
__________________________________________________________________________________________________
block_1a_bn_2 (BatchNormalizati (None, 64, 292, 180) 256 block_1a_conv_2[0][0]
__________________________________________________________________________________________________
block_1a_bn_shortcut (BatchNorm (None, 64, 292, 180) 256 block_1a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_1 (Add) (None, 64, 292, 180) 0 block_1a_bn_2[0][0]
block_1a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_1a_relu (Activation) (None, 64, 292, 180) 0 add_1[0][0]
__________________________________________________________________________________________________
block_1b_conv_1 (Conv2D) (None, 64, 292, 180) 36928 block_1a_relu[0][0]
__________________________________________________________________________________________________
block_1b_bn_1 (BatchNormalizati (None, 64, 292, 180) 256 block_1b_conv_1[0][0]
__________________________________________________________________________________________________
block_1b_relu_1 (Activation) (None, 64, 292, 180) 0 block_1b_bn_1[0][0]
__________________________________________________________________________________________________
block_1b_conv_2 (Conv2D) (None, 64, 292, 180) 36928 block_1b_relu_1[0][0]
__________________________________________________________________________________________________
block_1b_bn_2 (BatchNormalizati (None, 64, 292, 180) 256 block_1b_conv_2[0][0]
__________________________________________________________________________________________________
add_2 (Add) (None, 64, 292, 180) 0 block_1b_bn_2[0][0]
block_1a_relu[0][0]
__________________________________________________________________________________________________
block_1b_relu (Activation) (None, 64, 292, 180) 0 add_2[0][0]
__________________________________________________________________________________________________
block_2a_conv_1 (Conv2D) (None, 128, 146, 90) 73856 block_1b_relu[0][0]
__________________________________________________________________________________________________
block_2a_bn_1 (BatchNormalizati (None, 128, 146, 90) 512 block_2a_conv_1[0][0]
__________________________________________________________________________________________________
block_2a_relu_1 (Activation) (None, 128, 146, 90) 0 block_2a_bn_1[0][0]
__________________________________________________________________________________________________
block_2a_conv_2 (Conv2D) (None, 128, 146, 90) 147584 block_2a_relu_1[0][0]
__________________________________________________________________________________________________
block_2a_conv_shortcut (Conv2D) (None, 128, 146, 90) 8320 block_1b_relu[0][0]
__________________________________________________________________________________________________
block_2a_bn_2 (BatchNormalizati (None, 128, 146, 90) 512 block_2a_conv_2[0][0]
__________________________________________________________________________________________________
block_2a_bn_shortcut (BatchNorm (None, 128, 146, 90) 512 block_2a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_3 (Add) (None, 128, 146, 90) 0 block_2a_bn_2[0][0]
block_2a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_2a_relu (Activation) (None, 128, 146, 90) 0 add_3[0][0]
__________________________________________________________________________________________________
block_2b_conv_1 (Conv2D) (None, 128, 146, 90) 147584 block_2a_relu[0][0]
__________________________________________________________________________________________________
block_2b_bn_1 (BatchNormalizati (None, 128, 146, 90) 512 block_2b_conv_1[0][0]
__________________________________________________________________________________________________
block_2b_relu_1 (Activation) (None, 128, 146, 90) 0 block_2b_bn_1[0][0]
__________________________________________________________________________________________________
block_2b_conv_2 (Conv2D) (None, 128, 146, 90) 147584 block_2b_relu_1[0][0]
__________________________________________________________________________________________________
block_2b_bn_2 (BatchNormalizati (None, 128, 146, 90) 512 block_2b_conv_2[0][0]
__________________________________________________________________________________________________
add_4 (Add) (None, 128, 146, 90) 0 block_2b_bn_2[0][0]
block_2a_relu[0][0]
__________________________________________________________________________________________________
block_2b_relu (Activation) (None, 128, 146, 90) 0 add_4[0][0]
__________________________________________________________________________________________________
block_3a_conv_1 (Conv2D) (None, 256, 73, 45) 295168 block_2b_relu[0][0]
__________________________________________________________________________________________________
block_3a_bn_1 (BatchNormalizati (None, 256, 73, 45) 1024 block_3a_conv_1[0][0]
__________________________________________________________________________________________________
block_3a_relu_1 (Activation) (None, 256, 73, 45) 0 block_3a_bn_1[0][0]
__________________________________________________________________________________________________
block_3a_conv_2 (Conv2D) (None, 256, 73, 45) 590080 block_3a_relu_1[0][0]
__________________________________________________________________________________________________
block_3a_conv_shortcut (Conv2D) (None, 256, 73, 45) 33024 block_2b_relu[0][0]
__________________________________________________________________________________________________
block_3a_bn_2 (BatchNormalizati (None, 256, 73, 45) 1024 block_3a_conv_2[0][0]
__________________________________________________________________________________________________
block_3a_bn_shortcut (BatchNorm (None, 256, 73, 45) 1024 block_3a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_5 (Add) (None, 256, 73, 45) 0 block_3a_bn_2[0][0]
block_3a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_3a_relu (Activation) (None, 256, 73, 45) 0 add_5[0][0]
__________________________________________________________________________________________________
block_3b_conv_1 (Conv2D) (None, 256, 73, 45) 590080 block_3a_relu[0][0]
__________________________________________________________________________________________________
block_3b_bn_1 (BatchNormalizati (None, 256, 73, 45) 1024 block_3b_conv_1[0][0]
__________________________________________________________________________________________________
block_3b_relu_1 (Activation) (None, 256, 73, 45) 0 block_3b_bn_1[0][0]
__________________________________________________________________________________________________
block_3b_conv_2 (Conv2D) (None, 256, 73, 45) 590080 block_3b_relu_1[0][0]
__________________________________________________________________________________________________
block_3b_bn_2 (BatchNormalizati (None, 256, 73, 45) 1024 block_3b_conv_2[0][0]
__________________________________________________________________________________________________
add_6 (Add) (None, 256, 73, 45) 0 block_3b_bn_2[0][0]
block_3a_relu[0][0]
__________________________________________________________________________________________________
block_3b_relu (Activation) (None, 256, 73, 45) 0 add_6[0][0]
__________________________________________________________________________________________________
block_4a_conv_1 (Conv2D) (None, 512, 73, 45) 1180160 block_3b_relu[0][0]
__________________________________________________________________________________________________
block_4a_bn_1 (BatchNormalizati (None, 512, 73, 45) 2048 block_4a_conv_1[0][0]
__________________________________________________________________________________________________
block_4a_relu_1 (Activation) (None, 512, 73, 45) 0 block_4a_bn_1[0][0]
__________________________________________________________________________________________________
block_4a_conv_2 (Conv2D) (None, 512, 73, 45) 2359808 block_4a_relu_1[0][0]
__________________________________________________________________________________________________
block_4a_conv_shortcut (Conv2D) (None, 512, 73, 45) 131584 block_3b_relu[0][0]
__________________________________________________________________________________________________
block_4a_bn_2 (BatchNormalizati (None, 512, 73, 45) 2048 block_4a_conv_2[0][0]
__________________________________________________________________________________________________
block_4a_bn_shortcut (BatchNorm (None, 512, 73, 45) 2048 block_4a_conv_shortcut[0][0]
__________________________________________________________________________________________________
add_7 (Add) (None, 512, 73, 45) 0 block_4a_bn_2[0][0]
block_4a_bn_shortcut[0][0]
__________________________________________________________________________________________________
block_4a_relu (Activation) (None, 512, 73, 45) 0 add_7[0][0]
__________________________________________________________________________________________________
block_4b_conv_1 (Conv2D) (None, 512, 73, 45) 2359808 block_4a_relu[0][0]
__________________________________________________________________________________________________
block_4b_bn_1 (BatchNormalizati (None, 512, 73, 45) 2048 block_4b_conv_1[0][0]
__________________________________________________________________________________________________
block_4b_relu_1 (Activation) (None, 512, 73, 45) 0 block_4b_bn_1[0][0]
__________________________________________________________________________________________________
block_4b_conv_2 (Conv2D) (None, 512, 73, 45) 2359808 block_4b_relu_1[0][0]
__________________________________________________________________________________________________
block_4b_bn_2 (BatchNormalizati (None, 512, 73, 45) 2048 block_4b_conv_2[0][0]
__________________________________________________________________________________________________
add_8 (Add) (None, 512, 73, 45) 0 block_4b_bn_2[0][0]
block_4a_relu[0][0]
__________________________________________________________________________________________________
block_4b_relu (Activation) (None, 512, 73, 45) 0 add_8[0][0]
__________________________________________________________________________________________________
output_bbox (Conv2D) (None, 4, 73, 45) 2052 block_4b_relu[0][0]
__________________________________________________________________________________________________
output_cov (Conv2D) (None, 1, 73, 45) 513 block_4b_relu[0][0]
==================================================================================================
Total params: 11,197,893
Trainable params: 11,188,165
Non-trainable params: 9,728