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so I have a dataset in the form of a grayscale image, that means one channel right? I changed input_shape to 64.64.1 from this code. classifier.add(ZeroPadding2D(padding=(2,2), input_shape = (64, 64, 1))) but i got error. Error when checking input: expected zero_padding2d_1_input to have shape (64, 64, 1) but got array with shape (64, 64, 3)
input: "data" input_shape { dim: 1 dim: 3 dim: 424 dim: 424 } input: "im_info" input_shape { dim: 1 dim: 3 } the test AP does not change a bit, indicates there is some …
Since Caffe model is generally trained on ImageNet which has RGB or 3-channel images, the easiest way to do this is by replicating the monochrome channel by three times. In RGB …
How does caffe know the dimensions of the input data. i understand the blob of grayscale image should be 100x1x96x96 (batchsize x channel x height x width) But when i load …
File "/home/gys/caffe/python/caffe/classifier.py", line 77, in predict for in_ in inputs]) File "/home/gys/caffe/python/caffe/pycaffe.py", line 261, in _Net_preprocess channel_order = …
Interfaces. Caffe has command line, Python, and MATLAB interfaces for day-to-day usage, interfacing with research code, and rapid prototyping. While Caffe is a C++ library at heart and …
Caffe defines a net layer-by-layer in its own model schema. The network defines the entire model bottom-to-top from input data to loss. As data and derivatives flow through the network in the …
the network has input like this: name: "suma" input: "data" input_shape { dim: 1 dim: 1 dim: 11 dim: 11 } that means we just. Browse Community. Register Help cancel. Turn on …
Because for an RGB image, there are 3 channels, 'R', 'G' and 'B' So, the input shape will be (height, width, 3) But since grayscale has only one channel, the input shape becomes …
I'm trying to use the MINST Caffe example via the C++ API, but I'm having a bit of trouble working out how to restructure the network prototxt file I'll deploy after training. ...
If the image is grey-scale, then the channel argument takes a value of 1, and if coloured, then it takes a value of 3, one for each of Red, Green and Blue channels. …
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