Open iu110 opened 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?
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.
@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.
A great job, are there any tips on setting up bounding boxes to perform batch inferencing?