Yolov9 bad results
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Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 15/100
- Issue type
- Bug
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- computer-vision, machine-learning, python
- Domain
- computer-vision, machine-learning
Research direction
No repository file, test, or entry point is mentioned. Start by comparing the linked merged dataset with the construction-site-safety dataset and the reported evaluation metrics, focusing on label coverage and dataset composition. Done means documenting whether the data explains the degraded results and identifying a suitable dataset or training approach.
Written by the indexing model from the issue text.
Description
I want to train a model with personal protective equipment. When I train with a helmet, vest and mask, the results are good, but when I add gloves and goggles in addition to these equipment by taking images from different datasets, the results get quite bad. Is there a dataset or approach you can recommend?
I need a dataset of situations with and without hardhats, vests, masks, gloves and goggles(Hardhat,No-Hardhat, Glove, No-Glove etc.)
https://universe.roboflow.com/yavuzhan-zom9x/mergeddataset-50xku/dataset/19 (Dataset I created by merging)
https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety (The dataset I use for hardhats, vests and masks)
I am presenting the success evaluation metrics of the last model I trained in the screenshot.
Thanks for your support.
- Dominant language
- Python
- Stars
- 642
- Forks
- 146
- Avg merge
- 1d 10h
- Merged PRs (30d)
- 13
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