unet ref training preview and inference script about joligen

[royale]

Hello, please could you try with the PR #577 and the following command:

python3 gen_single_image_diffusion.py --model-in-file /checkpoints/viton_bbox_ref/latest_net_G_A.pth --img-in /datasets/viton_ref/viton_bbox_ref/testA/imgs/00013_00.jpg --bbox-in /datasets/viton_ref/viton_bbox_ref/testA/bbox/00013_00.txt --ref-in /datasets/viton_ref/viton_bbox_ref/testA/ref/00017_00.jpg --dir-out /checkpoints/viton_bbox_ref/inference_output

[beniz]

This was closed by mistake (automatically from PR).
@concrete13377 can you try with the same image as @royale for a start ?
Some images have bboxes that are larger than the crop, these are corner cases.

This is what we get (from our internal chat):

The fuzzyness is from the resolution upsampling.

Note: models can be finetuned in higher dimensions easily as they are fully convolutional.

[concrete13377]

it's similiar, it seems that the code that generates samples preview during training and this separate inference script have some drastic differences

[concrete13377]

sure, I haven't notice that the suggested command have different image as an argument, with this one it works fine, thank you for your work!