mot2yolo.py and coco2yolo.py give differing results (coco2yolo.py CORRECT)

[suzanne-stathatos]

coco2yolo and mot2yolo give differing results.

For example, ...yolo_data/labels/train-v4/2018-05-30-JD150_LeftFar_Stratum1_Set1_LO_2018-05-30_230004_2222_2422_100.txt that was used to train the eccv model gives:

0 0.4097222222222222 0.10032102728731943 0.20138888888888884 0.020866773675762437

After downloading mot annotations from CaltechData, and pulling this latest repo, I run python mot2yolo.py --in_dir ../Data/fishcounting/eccv_2022/annotations_mot/ --out_dir ./labels_from_mot --image_dir ../Data/fishcounting/eccv_2022/frames/raw/

When I look at the same file, i.e. , labels_from_mot/labels/kenai-train/2018-05-30-JD150_LeftFar_Stratum1_Set1_LO_2018-05-30_230004_2222_2422/100.txt I get

0 0.5729166666666666 0.04173354735152488 0.2361111111111111 0.02247191011235955

(I looked at 101.txt to see if it was an off-by-one kind of error - no match)

When I run coco2yolo, python coco2yolo.py --in_dir ../Data/fishcounting/eccv_2022/coco_formatted_annotations --out_dir labels_from_coco
I get

0 0.4097222222222222 0.10032102728731943 0.2013888888888889 0.02086677367576244

coco2yolo agrees with our existing yolo data
mot2yolo does not