The Omdena Abuja ANPD is trained on YOLOv4-Tiny. You only look once (YOLO) is a state-of-the-art, real-time object detection system. On a Pascal Titan X it processes images at 30 FPS and has a mAP of 57.9% on COCO test-dev.
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See YOLOv4 Github for full documentation on training and testing.
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src module
- Update inferences file
- Update ANPD folder
- Update all notebooks
- Update repo basic filesOmdena Abuja ANPD
The first release of the Omdena Abuja ANPD is trained YOLOv4-Tiny while optical character recognition (OCR) is done with easyOCR. This release contains;
anpd.zip: This archive needed by src module written to implement the ANPD. Remember to unzip it into the root folder. The archive contains;
anpd_1000.weights: This weights file is saved at the first 1000 iterations, you can start training from this weights checkpoint.
anpd_best.weights: This weights file is the best weights file for making implementation and inferences.
anpd_last.weights: This weights file is saved at the last iterations of the previous training, you can resume training from this weights checkpoint
Full Changelog: https://github.com/abdulazeezoj/omdena-abuja-anpd/commits/v1.0.0
Source code(tar.gz)
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