Wadhwani AI Bollworm Counting Challenge
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Helping India
€15 000 EUR
Challenge completed almost 3 years ago
Object Detection
Computer Vision
823 joined
146 active
Start
Sep 23, 22
Close
Dec 04, 22
Reveal
Dec 04, 22
Worm count discrepancy
Data · 8 Nov 2022, 15:18 · 3
Hello guys. I found out that if we compare CSV files with bounding boxes and train_csv with worm count there are some discrepancies in the number of worms present in the image. There are 136 instances that I found. Below is just an example of IDs that are not matching:
id_00695feae97d7bf88bb498a2.jpg
id_027743deacb53c14f0dac8fa.jpg
id_065837a379642cde8166ea78.jpg
id_066abd53fbc0b372f8a64ae4.jpg
id_0750c0ba1651c570dcaf137d.jpg
Could someone from the competition organizers somehow comment on this?
Hi yurri, as this is real-life data you need to take into account the human error of labeling. The image count should be similar but not necessarily exact in all cases.
hi, if this is human error in labeling, is it correct for the test dataset? for example, in the test submission, I found one image that contained pbw, but when I put the count number for that image, the MAE increased. I wonder if you could verify the correctness of the test dataset.
@amyflorida626