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PyTorch implementation of "Pyramid Scene Parsing Network".

License: MIT License

Python 99.12% Shell 0.88%
convolutional-neural-networks semantic-segmentation instance-segmentation scene-understanding pytorch pretrained-models ade20k deep-halftoning dilatednet cascade-dilatednet transfer-learning sceneparse150 sceneparsing supervision scene-parsing resnet-101 pyramid pyramid-pooling

objectnet's Issues

about merge most common classes

hi,Nikronic!

I have a question for you about ObjectNet. How did you merge most common classes to reduce number of classes from 150 to 25?

Convert all Open-cv methods to Pillow one

This may be crucial to manipulate tensors. So all the time we have a numpy array image or Pillow one because of Pytorch image processing backend which is Pillow.

Normalization is required

Using normalization in custom transforms required as below:

normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],
                                 std=[0.229, 0.224, 0.225])

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