https://github.com/12345k/multi-face-comparison
This repo is meant for backend API for face comparision and computer vision. It is built on python flask framework
https://github.com/12345k/multi-face-comparison
bac comparison deeplearning distance face face-detection face-recognition flask machine-learning postman python python3
Last synced: 6 months ago
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This repo is meant for backend API for face comparision and computer vision. It is built on python flask framework
- Host: GitHub
- URL: https://github.com/12345k/multi-face-comparison
- Owner: 12345k
- Created: 2018-08-27T12:13:00.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2020-05-23T18:45:33.000Z (over 5 years ago)
- Last Synced: 2025-03-27T20:40:26.560Z (6 months ago)
- Topics: bac, comparison, deeplearning, distance, face, face-detection, face-recognition, flask, machine-learning, postman, python, python3
- Language: Python
- Homepage:
- Size: 475 KB
- Stars: 25
- Watchers: 2
- Forks: 16
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Multi-Face-Comparison
Compare two images and it will return True or False. This is the main focus of this repo. I have attached two py file.
One is compare_image.py this can be run in the terminal with two images name like
> karthick_aravindan@ml-machine:~/Documents/Two-Face-Comparison$ python compare_image.py image_1.jpg image_2.jpg
Another File is app.py. This file is api which can be attached to website or other apps. In this we compare multiple faces with one target image.
## Requirment
```
pip install face_recognition
pip install flask
pip install scipy
```
# Run
```
> karthick_aravindan@ml-machine:~/Two-Face-Comparison$ python app.py
```
Flask api will be hosted 8000 port
### Endpoints
- /api/v1/compare_faces
- /api/v1/detect_faces
## Output for compare_image.py
Distance and Boolean value. Distance is higher means it is false and lower is True
###### command line output
```
> karthick_aravindan@ml-machine:~/Two-Face-Comparison$ python compare_image.py ami.jpg AMI.jpg
> 0.5439451765528829
> True
```
## Output for compare face API
Output will be in json format. Addition I have calculate time take to predict
###### Example
```
[
{
"result": "True",
"distance": 0.0,
"time_taken": 0.29,
"target": "rajini.jpeg",
"face": "rajini.jpeg"
},
{
"result": "False",
"distance": 0.77,
"time_taken": 0.339,
"target": "rajini.jpeg",
"face": "kamal.jpg"
}
]
```
I have used postman to check the api. The url mostly will be like http://localhost:8000/compare_faces in POST format.
#### form-data key name will be target and faces in Postman
## Detect Faces API
It will returns list of face coordinates for the images.
#### Example
```
[
{
"coordinates": [
{
"ymin": 46,
"xmin": 175,
"ymax": 136,
"xmax": 86
}
],
"time_taken": 0.046,
"image_name": "kamal.jpg"
},
{
"coordinates": [
{
"ymin": 32,
"xmin": 101,
"ymax": 84,
"xmax": 49
}
],
"time_taken": 0.016,
"image_name": "harry.jpg"
}
]
```
###### command line output
```
> karthick_aravindan@ml-machine:~/Two-Face-Comparison$ python detect_face.py image_path/ami.jpg
> Coordinates: [(53, 114, 115, 52)]
```
Links for other resources
https://face-recognition.readthedocs.io/en/latest/installation.html