Hardik Dava

@onuralpszr have you tested the PR with large dataset? I am afraid we have to move fast with this PR as it is a blocker for integration with yoloexplorer. Let...

@tfriedel @onuralpszr I tested this PR. I would say it is better than exisiting solution. @SkalskiP please take a look also as this might needs in changing API a bit....

Code to reproduce my issue. ```python import supervision as sv data = "train2017" ds = sv.DetectionDataset.from_yolo( images_directory_path=f"../../dataset/coco/images/{data}", annotations_directory_path=f"../../dataset/coco/labels/{data}", data_yaml_path=f"../../supervision/data/coco128.yaml", ) for image_name, image, labels in ds: print(f"{image_name} : {image.shape}, {len(labels)}")...

@tfriedel then this might be something wrong from my end. Just a question, can we use lazydict for detections as well? Then, the increase in memory will be solved. What...

@onuralpszr I tested code and it seems we can use this implementation. What is your thoughts on this?

Can we also add how to modify documentation in case of modifying existing feature and adding a new feature?

@SkalskiP Do you think of any other features to be included? Please go through the descriptions once.

hello @SkalskiP @onuralpszr , let's try to finish this as it will make good reflection from community.

@onuralpszr @SkalskiP Should we include this in next release?

@SkalskiP yes, it is better in terms of accuracy but not in terms of speed. You can learn about it more and direct comparision on this blogpost: https://learnopencv.com/weighted-boxes-fusion/