mirror of
https://github.com/deepinsight/insightface.git
synced 2026-05-18 06:38:19 +00:00
Update README.md
This commit is contained in:
@@ -1,11 +1,31 @@
|
||||
### RetinaFace Face Detector
|
||||
# RetinaFace Face Detector
|
||||
|
||||
## Introduction
|
||||
|
||||
RetinaFace is a robust single stage face detector which initially described as an [arXiv technical report](https://arxiv.org/abs/1905.00641)
|
||||
|
||||
|
||||
## Training
|
||||
|
||||
1. Download groundtruth labels from [baiducloud](https://pan.baidu.com/s/1Laby0EctfuJGgGMgRRgykA) or dropbox and organise the dataset directory under ``insightface/RetinaFace/`` as follows(images can be downloaded from WiderFace website directly):
|
||||
```Shell
|
||||
data/retinaface/
|
||||
train/
|
||||
images/
|
||||
label.txt
|
||||
val/
|
||||
images/
|
||||
label.txt
|
||||
test/
|
||||
images/
|
||||
label.txt
|
||||
```
|
||||
|
||||
## Testing
|
||||
|
||||
Please check ``test.py`` for model usage.
|
||||
|
||||
Pretrained Model: [RetinaFace-R50](https://pan.baidu.com/s/1C6nKq122gJxRhb37vK0_LQ) is a medium size model with ResNet50 backbone. WiderFace validation mAP: Easy 96.5, Medium 95.6, Hard 90.4. It can output face bounding boxes and five landmarks in a single forward pass.
|
||||
|
||||
Light weight and large models will be released soon.
|
||||
|
||||

|
||||
|
||||

|
||||
|
||||
Reference in New Issue
Block a user