Can't reach the performance reported in project. about pose-residual-network HOT 4 CLOSED

I found some difference between code and paper:

1. Missing Hidden layer
2. • Paper:
     "We trained the model with the person instances which has more than 2 keypoints"
   • code:

          if ann['iscrowd'] == 0 and ann['num_keypoints'] > 4:
              anns.append(ann) # ann

from pose-residual-network.

Hi! when I retrain this code ,I placed the annotations in ./data/annotations. Could you tell me which path should the COCO images be placed? thank you very much @DouYishun

from pose-residual-network.

@ZhongXiaoFang Only annotation is needed, for both the input and output are heatmap.

from pose-residual-network.

Thank you for your reply. it means I just need to put the annotation files of COCO dataset in the path of ./data/annotations. and then run the command (python main.py) to train? I have installed all the requirements following the README.md. but meet this error when start training with command: python3 main.py .

loading annotations into memory...
Done (t=6.83s)
creating index...
index created!
loading annotations into memory...
Done (t=0.27s)
creating index...
index created!
Traceback (most recent call last):
File "main.py", line 45, in
main(option)
File "main.py", line 24, in main
model = PRN_Seperate(option.coeff28,option.coeff18, option.node_count)
File "/home/zhong/pose-residual-network-master/src/model.py", line 33, in PRN_Seperate
o = Activation('softmax')(o)
File "/usr/local/lib/python3.5/dist-packages/keras/engine/base_layer.py", line 457, in call
output = self.call(inputs, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/keras/layers/core.py", line 299, in call
return self.activation(inputs)
File "/usr/local/lib/python3.5/dist-packages/keras/activations.py", line 31, in softmax
return K.softmax(x)
File "/usr/local/lib/python3.5/dist-packages/keras/backend/tensorflow_backend.py", line 3231, in softmax
return tf.nn.softmax(x, axis=axis)
TypeError: softmax() got an unexpected keyword argument 'axis'
@DouYishun

from pose-residual-network.