Traceback (most recent call last):


 "neural_style_transfer.py", line 143, in <module>

weights='imagenet', include_top=False)


 "C:\Users\Seppe\Anaconda3\lib\site-packages\keras_applications\vgg19.py", line 116, in VGG19

name='block1_conv1')(img_input)


 "C:\Users\Seppe\Anaconda3\lib\site-packages\keras\engine\base_layer.py", line 457, in __call__

output = self.call(inputs, **kwargs)


 "C:\Users\Seppe\Anaconda3\lib\site-packages\keras\layers\convolutional.py", line 168, in call

dilation_rate=self.dilation_rate)


 "C:\Users\Seppe\Anaconda3\lib\site-packages\keras\backend\cntk_backend.py", line 1526, in conv2d

padding])


 "C:\Users\Seppe\Anaconda3\lib\site-packages\cntk\internal\swig_helper.py", line 69, in wrapper

result = f(*args, **kwds)


 "C:\Users\Seppe\Anaconda3\lib\site-packages\cntk\ops\__init__.py", line 356, in convolution

reduction_rank, groups, max_temp_mem_size_in_samples, sequential, name)
ValueError: Convolution operation requires that kernel dim 64 <= input dim 3.

Traceback (most recent call last):


 "./tools/train_net.py", line 112, in <module>

max_iters=args.max_iters)


 "/home/data2/clxia1120/software/py-R-FCN/tools/../lib/fast_rcnn/train.py", line 207, in train_net

model_paths = sw.train_model(max_iters)


 "/home/data2/clxia1120/software/py-R-FCN/tools/../lib/fast_rcnn/train.py", line 155, in train_model

model_paths.append(self.snapshot())


 "/home/data2/clxia1120/software/py-R-FCN/tools/../lib/fast_rcnn/train.py", line 112, in snapshot

np.repeat(self.bbox_stds, repeat).reshape((orig_1.shape[0], 1, 1, 1)))
ValueError: total size of new array must be unchanged
