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sangyun884 / HR-VITON

Official PyTorch implementation for the paper High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditions (ECCV 2022).
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Specifications for Generation of 'image-parse-agnostic-v3.2' #29

Closed Atotem closed 1 year ago

Atotem commented 1 year ago

Hi, following your code, in order to generate the train/test dataset I apparently must prepare the 'image-parse-agnostic-v3.2'. It looks like it's the same file as in the 'openpose_img', but the regions of the neck and torso are dropped to zero values, but, with some peculiar differences. Which is the process to generate this type of data? Why isn't being performed online. Greetings.

Sincerely, @Atotem

koo616 commented 1 year ago

Hello @Atotem . Now you can get parse-agnostic images using 'get_parse_agnostic.py' code I uploaded. Please check it :)