echonet / dynamic

EchoNet-Dynamic is a deep learning model for assessing cardiac function in echocardiogram videos.
https://echonet.github.io/dynamic
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Segmentation Mask Identification #65

Open MAGomes95 opened 2 years ago

MAGomes95 commented 2 years ago

Is there a way I can identify the pixels belonging to the segmentation masks?

I performed some comparison across the pixel intensities for a given frame in a given video-clip for a variety of videos-clips. Based on the code, I thought that all pixels belonging to the segmentation mask would have a value of 255. Nevertheless, this is not the case. For example, there are frames from target that not only contain pixels with intensity being 255 but other, like 240, 247, 230 and 192.

Based on the difference on the frequencies of pixel intensities, it is clear that the target frame has a lot more pixel which intensities are very high compared with the input frame. In that sense, the mask is associated with high-value pixel intensities. But I would like a straight way of identifying such pixels, for example "Pixels with value superior to X in the predicted frame, belong to the segmentation mask".

Thank you :)