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https://github.com/cabelo/oneapi-antispoofing
Certiface AntiSpoofing use oneAPI for fast decode video for perform liveness detection with inference.
https://github.com/cabelo/oneapi-antispoofing
Last synced: 3 months ago
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Certiface AntiSpoofing use oneAPI for fast decode video for perform liveness detection with inference.
- Host: GitHub
- URL: https://github.com/cabelo/oneapi-antispoofing
- Owner: cabelo
- License: apache-2.0
- Created: 2020-10-31T02:27:36.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2023-12-01T18:06:59.000Z (about 1 year ago)
- Last Synced: 2024-08-02T15:09:15.452Z (6 months ago)
- Language: C++
- Size: 14 MB
- Stars: 2
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-oneapi - Certiface Anti-Spoofing - Certiface AntiSpoofing use oneAPI for fast decode video for perform liveness detection with inference. The system is capable of spotting fake faces and performing anti-face spoofing in face recognition systems. (Table of Contents / AI - Computer Vision)
README
# oneapi-antispoofing
***Certiface AntiSpoofing*** use oneAPI for fast decode video for perform liveness detection with inference. The system is capable of spotting fake faces and performing anti-face spoofing in face recognition systems. The user could try to hold up a your photo. Maybe they even have a photo or video on their smartphone (obtained in facebook, for example)
This project/solution use harness heterogeneous computing architecture including CPUs and GPUs from servers to notebooks. The software tools such as oneVPL, computer vision techniques with openCV and Deep Learning technologies based on Intel features.
## Methodology / Approach
Using deep learning for detect photo with fast decoder h264/h265 format video. Technologies Used:
- oneAPI
- openCV
- openVINO
Technologies Used: oneAPI and openCV
## Installation instructions:
***Under construction***
Below, a quick description of how to manually install the ***oneapi-antispoofing*** project.
### Prepare ambient
Install the openCV library and set up the oneapi development environment as in the example below.
``` bash
$ source /opt/intel/oneapi/setvars.sh
:: initializing oneAPI environment ...
:: dnnl -- latest
:: advisor -- latest
:: dpcpp-ct -- latest
:: dev-utilities -- latest
:: ipp -- latest
:: ccl -- latest
:: compiler -- latest
:: ippcp -- latest
:: daal -- latest
:: debugger -- latest
:: mpi -- latest
:: intelpython -- latest
:: tbb -- latest
:: vpl -- latest
:: vtune -- latest
:: mkl -- latest
:: oneAPI environment initialized ::
```
### Clone and build the project
Clone the repository at desired location:
``` bash
$ git clone https://github.com/cabelo/oneapi-antispoofing
$ cd oneapi-antispoofing
$ mkdir build
$ cd build
$ cmake ..
$ make
```
### Run the example
Below, how to run the project. Enter in build folder and execute the commands:
``` bash
$ wget https://service.assuntonerd.com.br/downloads/antispoofing.weights
$ wget https://service.assuntonerd.com.br/downloads/antispoofing.cfg
$ make run
```
Or to test fraud, use the command below:
``` bash
$ ./antispoofing ../content/fraud-video.h265 y
```
To test real case, use the command below:
``` bash
$ ./antispoofing ../content/real-video.h265 y
```
### To Do
- [x] First version
- [x] Publish in github
- [x] Teste and port (if necessary) to oneAPI Beta10
- [x] Teste and port (if necessary) to oneAPI 2023
- [x] Teste and port to oneVPL 2023
- [ ] Create webserver REST
## The final result
Bellow an example running in my machine with Linux OpenSUSE Leap 15.2, 15.3 and 15.4.
contact : Alessandro de Oliveira Faria (A.K.A.CABELO) [email protected]
Thank you Sujata Tibewala and Emma Mai.
