create synthetic dataset for Semantic Segmentation or instance segmentation about synthetic-dataset-object-detection HOT 3 OPEN

The composition of masks of the objects, which is generated during the script, can be used for instance segmentation. Just save the composition with masks into png-file. Also save classes of the objects on the composition into txt-file.

You can use the saved png- and txt-files for training an instance segmentation model using this tutorial: https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html

Example
Lets suppose that the saved png-file contains pixels with values 0, 1, 2, 3, 4, 5. Pixels equal to 0 are related to background, pixels equal to other numbers are related to the objects. So, we have 5 objects on the image.

Lets suppose that the saved txt-file contains classes 2, 1, 1, 2, 2 (order matters!). It means that the object 1 is related to class 2, object 2 is related to class 1, object 3 is related to class 1, object 4 is related to class 2, object 5 is related to class 2.

Class 1 could be a cat, and class 2 could be a dog.

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Thank you very much for your guidance. I will try my best

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update for yolov7? add video?

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