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Performance comparison of human silhouette extraction from videos by semantic segmentation with ResNet-101 compared to statistical background modelling.

Python 100.00%
deeplabv3 opencv pytorch fcn mog2 gmg

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human-silhouette-extractor's Issues

Excuse me, error when running your "Proposed Solution.py"

when running

model = torch.hub.load('pytorch/vision:v0.6.0', 'deeplabv3_resnet101', pretrained=True)

error:

  File "C:\Users\hp\Miniconda3\envs\torch1.10\lib\urllib\request.py", line 649, in http_error_default
    raise HTTPError(req.full_url, code, msg, hdrs, fp)
urllib.error.HTTPError: HTTP Error 403: rate limit exceeded

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