Custom testing images - empty reference labels about rpcmvos HOT 3 CLOSED

I figured out my problem. The annotating tool that I used returned a greyscale image (1-channel) which it should do, but it didn't return a monotone mask (if inspecting the PNG I linked above, there are grey pixels which there shouldn't be). By giving all non-zero pixels the value 1, the model works.

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Hi, I think you are trying to format your custom dataset into YouTubeVOS format for evaluation, my suggestions are as follows:

• A binary mask in your case only includes 0 and 1. However, as the number of objects in the YouTubeVOS dataset may be larger than 2, the value of each pixel of the annotated image can be a value larger than 2. That is to say, each pixel of the annotated image is expected to be a value >=0, e.g., the value can be in {0,1,2} if there are two foreground objects at most (here 0 indicates the background). For this point, I think you can have a deeper look at the annotation of YouTubeVOS before evaluating your custom dataset.
• Specifically, you can print out the value of the annotated image in the read_label function ( ./dataloaders/datasets.py#L450) for the evaluation on YouTubeVOS. Then, I think you can understand the annotation format of YouTubeVOS better. Afterward, you can transform the annotation format of your custom annotated image into the YouTube-VOS format.
• If you have new problems or questions, feel free to ask me. : )

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I figured out my problem. The annotating tool that I used returned a greyscale image (1-channel) which it should do, but it didn't return a monotone mask (if inspecting the PNG I linked above, there are grey pixels which there shouldn't be). By giving all non-zero pixels the value 1, the model works.

Glad to know that you have solved the problem.

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