xiaochus / Yolov3
Licence: mit
Keras implementation of yolo v3 object detection.
Stars: ✭ 585
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python
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YOLOv3
Keras(TF backend) implementation of yolo v3 objects detection.
According to the paper YOLOv3: An Incremental Improvement.
Requirement
- OpenCV 3.4
- Python 3.6
- Tensorflow-gpu 1.5.0
- Keras 2.1.3
Quick start
-
Download official yolov3.weights and put it on top floder of project.
-
Run the follow command to convert darknet weight file to keras h5 file. The
yad2k.pywas modified from allanzelener/YAD2K.
python yad2k.py cfg\yolo.cfg yolov3.weights data\yolo.h5
- run follow command to show the demo. The result can be found in
images\res\floder.
python demo.py
Demo result
It can be seen that yolo v3 has a better classification ability than yolo v2.
TODO
- Train the model.
Reference
@article{YOLOv3,
title={YOLOv3: An Incremental Improvement},
author={J Redmon, A Farhadi },
year={2018}
Copyright
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