https://github.com/hizhangp/yolo_tensorflow

Tensorflow implementation of YOLO, including training and test phase.
https://github.com/hizhangp/yolo_tensorflow

detection tensorflow yolo

Last synced: 4 days ago
JSON representation

Tensorflow implementation of YOLO, including training and test phase.

• Host: GitHub
• URL: https://github.com/hizhangp/yolo_tensorflow
• Owner: hizhangp
• License: mit
• Created: 2016-10-25T10:51:54.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2019-05-22T05:22:26.000Z (over 5 years ago)
• Last Synced: 2024-08-02T01:16:02.317Z (3 months ago)
• Topics: detection, tensorflow, yolo
• Language: Python
• Homepage:
• Size: 191 KB
• Stars: 794
• Watchers: 32
• Forks: 443
• Open Issues: 54
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-yolo-object-detection - hizhangp/yolo_tensorflow

README

        
## YOLO_tensorflow

Tensorflow implementation of [YOLO](https://arxiv.org/pdf/1506.02640.pdf), including training and test phase.

### Installation

1. Clone yolo_tensorflow repository

	```Shell

	$ git clone https://github.com/hizhangp/yolo_tensorflow.git

    $ cd yolo_tensorflow

	```

2. Download Pascal VOC dataset, and create correct directories

	```Shell

	$ ./download_data.sh

	```

3. Download [YOLO_small](https://drive.google.com/file/d/0B5aC8pI-akZUNVFZMmhmcVRpbTA/view?usp=sharing)

weight file and put it in `data/weight`

4. Modify configuration in `yolo/config.py`

5. Training

	```Shell

	$ python train.py

	```

6. Test

	```Shell

	$ python test.py

	```

### Requirements

1. Tensorflow

2. OpenCV