Does the toolkit support caffe model with image as output? And debug issue.

[idata]

Hi. I have noticed that the sample models were all caffe models for image classification, with "prob" as the output. I tried to launch my model of stereo matching on NCS but it doesn't work and give me the following traceback without any other error message:

File "../../src/./mvNCCheck.py", line 117, in

File "../../src/./mvNCCheck.py", line 91, in check_net File "../../src/./Controllers/CaffeParser.py", line 919, in parse_caffeKeyError: 'data'

I wonder whether the toolkit support models with images as output (like stereo matching / image enhancement / super resolution)?

Whether it support models with images of more than 3 channels as input (like a 16 bit depth image)?

Plus, is there any way to see the code for CaffeParser.py so that I can debug? Now I can only see the pyc file but not the original py file.

[idata]

@incredibleup The NCS SDK should have no issue with models using image outputs or models that use more than 3 channels. At the current moment, we are not planning to release the source code for CaffeParser.py. If you are still experiencing problems, please feel free to supply a link to the network in question, so that the issue may be further investigated. Thanks.

[idata]

Hi @Tome_at_Intel,

Is there an example of a model using image outputs? Ideally Tensorflow based.

Thanks..