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The Caltech Fish Counting Dataset
Hi, I'm playing around with the tiny version of this dataset and when I inspected tiny_dataset/annotations-tiny/elwha/Elwha_2018_OM_ARIS_2018_07_09_2018-07-09_190000_490_941/gt_tiny.txt
, it seems to contain 47 frames ranging from 208-254. However, when I look at the raw data at tiny_dataset/raw/elwha/Elwha_2018_OM_ARIS_2018_07_09_2018-07-09_190000_490_941
, there seems to be 50 frames ranging from 197 to 246. What explains the discrepancy I'm seeing?
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
It seems like the link is broken for the tiny dataset. Could you update it with the correct one?
Thank you for sharing the dataset.
Could you please share the model training and testing code? Thanks
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