limuloo / MIGC

[CVPR 2024 Highlight] "MIGC: Multi-Instance Generation Controller for Text-to-Image Synthesis" (Official Implementation)
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Batch inference #9

Open iu110 opened 4 months ago

iu110 commented 4 months ago

A great job, are there any tips on setting up bounding boxes to perform batch inferencing?

limuloo commented 4 months ago

@iu110 Thank you for your recognition of our work. Do you mean to include images with varying numbers of boxes in a single batch, or should the number of boxes be the same in all images within a batch?

iu110 commented 4 months ago

Thank you for getting back to me. Your current code only provides inference for a single image. If I want to infer multiple different images simultaneously, such as the 800 samples you provided, do I need to set up multiple sets of bounding boxes manually? Would you happen to have any tips for this? After all, it may be difficult to set them manually.

limuloo commented 4 months ago

@iu110 If you want to infer multiple different images simultaneously, you can do it this way:

Taking COCO-MIG as an example, where each image contains at most 6 instances, you can pad those images with fewer than 6 instances using empty text and a [0, 0, 0, 0] bounding box to reach 6 instances, which will have minimal impact on the results. Once all images are ensured to contain 6 instances, you can then place different images into one batch for inference.