https://github.com/brightxiaohan/facerecognizer
Deep face recognition.
https://github.com/brightxiaohan/facerecognizer
embedding-vectors face-recognition insightface reba
Last synced: 28 days ago
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Deep face recognition.
- Host: GitHub
- URL: https://github.com/brightxiaohan/facerecognizer
- Owner: BrightXiaoHan
- Created: 2019-03-18T09:23:58.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-06-05T08:47:10.000Z (over 6 years ago)
- Last Synced: 2025-04-24T01:43:39.386Z (5 months ago)
- Topics: embedding-vectors, face-recognition, insightface, reba
- Language: Python
- Size: 150 KB
- Stars: 5
- Watchers: 3
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Face Recognition Project
## Introduction
- This repo is a reimplementation of Arcface[(paper)](https://arxiv.org/abs/1801.07698), or Insightface[(github)](https://github.com/deepinsight/insightface)
- This repo is get inspiration from [insightface](https://github.com/deepinsight/insightface), [Insightface_Pytorh](https://github.com/TreB1eN/InsightFace_Pytorch)
## SetUp
#### Install MTCNN FaceDetector
Follow this instruction [FaceDetector Installation](./FaceDetector/README.md).
#### Install
```
python setup.py install
```
## Basic Usage
#### Download the pre-trained model.
Download from [pre-trained model](http://118.31.44.251:3000/DeepInsight/Models) and merge the part files
```bash
cat model_ir_se50.pth* > model_ir_se50.pth
mv model_ir_se50.pth /path/to/FaceRecognizer/output/res50
```
### FaceVerify
Verify if they are the same person.
```py
from insight_face import FaceSearcher
# Load pre-trained res50 model
searcher.load_state('./output/res50/model_ir_se50.pth', 50)
# Load face images
face1 = cv2.imread('./tests/assets/reba/2.jpg')
face2 = cv2.imread('./tests/assets/reba/3.jpg')
result = searcher.verify(face1, face2)
assert result is True
```
### Search
Find who they are.
```py
face_bank_dir = 'tests/assets/'
multi_face_img = cv2.imread("tests/assets/multi_face.jpg")
searcher.add_face_bank(face_bank_dir, force_reload=True, bank_name='test')
faces, names, best_sim, _, _ = searcher.search(multi_face_img, 'test')
print(names)
```
result
```
>> reba
```
### Match
Match the person between two pictures.
```python
source, target, sim = searcher.match(face1, multi_face_img)
cv2.imshow("source", source[0])
cv2.imshow("matched", target[0])
```
### Get embedding vectors
Get the raw embedding vectors of faces in given image.
```python
# expect a tensor shape with (3, 512)
emb, boxes, landmarks = searcher.embedding_faces_in_the_wild(multi_face_img)
```