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Japan_Gifu_v0.2
Addax-Data-Science/Japan_Gifu_v0.2
Japan_Gifu_v0.2 is a machine learning model from Addax-Data-Science. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Original repo: https://github.com/gifu-wildlife/MDetToolsForJCameraTraps
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Public
Updated Jul 14, 2025
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385 MB
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.pth385 MB · 100%
At a glance
- License
- mit
- Access
- Public
- Created
- May 26, 2025
- Updated
- Jul 14, 2025
- SHA
- a5ed5e65
Model card
From the Hugging Face model README
Original repo: https://github.com/gifu-wildlife/MDetToolsForJCameraTraps
The model weights have been soptred here for easy integration with AddaxAI: https://addaxdatascience.com/addaxai/
Gifu-wildlife cls model v0.2 (resnet50) for AddaxAI v6.14
Filename (weight): gifu-wildlife_cls_resnet50_v0.2.1.pth
Changes from v0.1:
- Trained using data excluding “human” and “dog” due to insufficient data. As a result, the number of categories decreased from 15 to 13.
- Modified classify_datections.py to match changes in AddaxAI v6.14.
- Changed “rabbit” to “hare.”
- Carefully rewrote classes.csv.
Test results[2025-05-20]:
- Top1 Accuracy : 0.926
- Top3 Accuracy : 0.987
- class wise acc | bear:0.816 | bird:0.571 | boar:0.941 | cat:0.200 | deer:0.971 | fox:0.607 | masked:0.519 | monkey:0.000 | mustelidae:0.600 | rabbit:0.235 | raccoondog:0.871 | serow:0.884 | squirrel:0.649
Note: It should be noted that the dataset is biased toward deer, which may lead to an overestimation of both Top1 and Top3 accuracy.
- License
- mit
- Created
- May 26, 2025
- Updated
- Jul 14, 2025