https://github.com/liushuan/YOLO-V3-Tensorflow2.0-Face-Detect-via-Wider-Face
使用 TensorFlow2.0 训练YOLOV3模型 和Wider Face 数据集，进行人脸检测
https://github.com/liushuan/YOLO-V3-Tensorflow2.0-Face-Detect-via-Wider-Face
Last synced: 5 months ago
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使用 TensorFlow2.0 训练YOLOV3模型 和Wider Face 数据集，进行人脸检测
- Host: GitHub
- URL: https://github.com/liushuan/YOLO-V3-Tensorflow2.0-Face-Detect-via-Wider-Face
- Owner: liushuan
- Created: 2019-07-25T02:22:27.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2023-03-25T00:19:23.000Z (about 2 years ago)
- Last Synced: 2024-08-02T19:01:54.396Z (9 months ago)
- Language: Python
- Size: 5.46 MB
- Stars: 21
- Watchers: 1
- Forks: 9
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- Awesome-Tensorflow2 - liushuan/YOLO-V3-Tensorflow2.0-Face-Detect-via-Wider-Face
README
# TensorFlow2.x-YOLOv3
A minimal tensorflow implementation of YOLOv3, with support for training, inference and evaluation.
## Installation
Install requirements and download pretrained weights
```
$ pip3 install -r ./docs/requirements.txt
$ wget https://pjreddie.com/media/files/yolov3.weights
```
## Quick start
In this part, we will use pretrained weights to make predictions on both image and video.
```
$ python image_demo.py
$ python video_demo.py # if use camera, set video_path = 0
```
## Train yymnist
Download [yymnist](https://github.com/YunYang1994/yymnist) dataset and make data.
```
$ git clone https://github.com/YunYang1994/yymnist.git
$ python yymnist/make_data.py --images_num 1000 --images_path ./data/dataset/train --labels_txt ./data/dataset/yymnist_train.txt
$ python yymnist/make_data.py --images_num 200 --images_path ./data/dataset/test --labels_txt ./data/dataset/yymnist_test.txt
```
Open `./core/config.py` and do some configurations
```
__C.YOLO.CLASSES = "./data/classes/yymnist.names"
```
Finally, you can train it and then evaluate your model
```
$ python train.py
$ tensorboard --logdir ./data/log
$ python test.py
$ cd ../mAP
$ python main.py # Detection images are expected to save in `YOLOV3/data/detection`
```
Track training progress in Tensorboard and go to http://localhost:6006/
```
$ tensorboard --logdir ./data/log
```
| train |test|
|---|---
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