Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).
File "train.py", line 101, in main(args)
File "train.py", line 70, in main
anchors = config['model']['anchors'])
File "C:\Users\vcvis\Desktop\yolo experiment\keras-yolo2-master\frontend.py", line 60, in init
features = self.feature_extractor.extract(input_image)
File "C:\Users\vcvis\Desktop\yolo experiment\keras-yolo2-master\backend.py", line 34, in extract
return self.feature_extractor(input_image)
File "C:\Users\vcvis\AppData\Roaming\Python\Python36\site-packages\keras\engine\base_layer.py", line 457, in call
output = self.call(inputs, kwargs)
File "C:\Users\vcvis\AppData\Roaming\Python\Python36\site-packages\keras\engine\network.py", line 564, in call
outputtensors, , _ = self.run_internal_graph(inputs, masks)
File "C:\Users\vcvis\AppData\Roaming\Python\Python36\site-packages\keras\engine\network.py", line 721, in run_internal_graph
layer.call(computed_tensor, kwargs))
File "C:\Users\vcvis\AppData\Roaming\Python\Python36\site-packages\keras\layers\convolutional.py", line 171, in call
dilation_rate=self.dilation_rate)
File "C:\Users\vcvis\AppData\Roaming\Python\Python36\site-packages\keras\backend\tensorflow_backend.py", line 3650, in conv2d
data_format=tf_data_format)
File "D:\miniconda\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 779, in convolution
data_format=data_format)
File "D:\miniconda\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 839, in init
filter_shape[num_spatial_dims]))
ValueError: number of input channels does not match corresponding dimension of filter, 3 != 1
i changed the code in backend.py
i got this error
File "train.py", line 101, in
main(args)
File "train.py", line 70, in main
anchors = config['model']['anchors'])
File "C:\Users\vcvis\Desktop\yolo experiment\keras-yolo2-master\frontend.py", line 60, in init
features = self.feature_extractor.extract(input_image)
File "C:\Users\vcvis\Desktop\yolo experiment\keras-yolo2-master\backend.py", line 34, in extract
return self.feature_extractor(input_image)
File "C:\Users\vcvis\AppData\Roaming\Python\Python36\site-packages\keras\engine\base_layer.py", line 457, in call
output = self.call(inputs, kwargs)
File "C:\Users\vcvis\AppData\Roaming\Python\Python36\site-packages\keras\engine\network.py", line 564, in call
outputtensors, , _ = self.run_internal_graph(inputs, masks)
File "C:\Users\vcvis\AppData\Roaming\Python\Python36\site-packages\keras\engine\network.py", line 721, in run_internal_graph
layer.call(computed_tensor, kwargs))
File "C:\Users\vcvis\AppData\Roaming\Python\Python36\site-packages\keras\layers\convolutional.py", line 171, in call
dilation_rate=self.dilation_rate)
File "C:\Users\vcvis\AppData\Roaming\Python\Python36\site-packages\keras\backend\tensorflow_backend.py", line 3650, in conv2d
data_format=tf_data_format)
File "D:\miniconda\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 779, in convolution
data_format=data_format)
File "D:\miniconda\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 839, in init
filter_shape[num_spatial_dims]))
ValueError: number of input channels does not match corresponding dimension of filter, 3 != 1
guide me thank you