https://github.com/osmr/facedetver
Face Detection Verifier
https://github.com/osmr/facedetver
Last synced: over 1 year ago
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Face Detection Verifier
- Host: GitHub
- URL: https://github.com/osmr/facedetver
- Owner: osmr
- License: mit
- Created: 2019-09-11T18:41:55.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2019-09-19T09:21:16.000Z (over 6 years ago)
- Last Synced: 2025-01-18T14:53:23.141Z (over 1 year ago)
- Language: Python
- Size: 146 KB
- Stars: 2
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Face Detection Verifier
This repo contains scripts for solving the binary classification problem, where the positive class is undistorted images
of a person’s face, and the negative class is everything else, including images of parts of a person’s face, face
drawings, etc.
The repository contains scripts for building and analyzing the corresponding dataset, for training and testing models.
Two deep learning frameworks are supported: MXNet/Gluon and PyTorch. All scripts are completely duplicated.
In addition, the releases contain two training datasets and four models that solve the problem.
## Deployment Instructions
Recommended repository deployment protocol on the machine with CUDA 10.0 and cuDNN 7:
1. Install prerequesities for MXNet:
```
apt update
apt upgrade
apt install -y htop mc wget unzip python3-pip ipython3
apt install -y build-essential git ninja-build ccache
apt install -y apt-transport-https build-essential ca-certificates curl git libatlas-base-dev libcurl4-openssl-dev libjemalloc-dev libhdf5-dev liblapack-dev libopenblas-dev libopencv-dev libturbojpeg libzmq3-dev ninja-build software-properties-common sudo vim-nox
apt install -y libopenblas-dev libopencv-dev
apt install -y libsm6 libxext6 libxrender-dev
```
2. Install pip-packages from `requirements.txt`:
```
pip3 install --upgrade numpy opencv-python imgaug tqdm
pip3 install --upgrade mxnet-cu100 gluoncv2
pip3 install --upgrade torch torchvision pytorchcv
```
3. Clone the repo:
```
mkdir projects
cd projects
git clone https://github.com/osmr/facedetver.git
```
4. Create directory for dataset and models:
```
mkdir facedetver_data
cd facedetver_data
```
5. Download and extract dataset FDV1:
```
mkdir fdv1
cd fdv1
wget https://github.com/osmr/facedetver/releases/download/v0.0.1/fdv1_test.zip
wget https://github.com/osmr/facedetver/releases/download/v0.0.1/fdv1_train.zip
wget https://github.com/osmr/facedetver/releases/download/v0.0.1/fdv1_val.zip
unzip fdv1_test.zip
unzip fdv1_train.zip
unzip fdv1_val.zip
```
6. Or download and extract dataset FDV2:
```
mkdir fdv2
cd fdv2
wget https://github.com/osmr/facedetver/releases/download/v0.0.2/fdv2_test.zip
wget https://github.com/osmr/facedetver/releases/download/v0.0.2/fdv2_train.zip
wget https://github.com/osmr/facedetver/releases/download/v0.0.2/fdv2_val.zip
unzip fdv2_test.zip
unzip fdv2_train.zip
unzip fdv2_val.zip
```
7. Download and extract a model:
```
cd ..
mkdir resnet18_fdv1-0014
cd resnet18_fdv1-0014
wget https://github.com/osmr/facedetver/releases/download/v0.0.3/resnet18_fdv1-0014-a03f116e.params.zip
unzip resnet18_fdv1-0014-a03f116e.params.zip
```
8. Run a testing script:
```
cd ../../facedetver
python3 eval_gl.py --num-gpus=1 --model=resnet18 --save-dir=../facedetver_data/resnet18_fdv1-0014/ --batch-size=100 -j=4 --resume=../facedetver_data/resnet18_fdv1-0014/resnet18_fdv1-0014-a03f116e.params --calc-flops --show-bad-samples --data-subset=test
```
## Pretrainded Models
| Model | Dataset | Framework | Acc | F1 | MCC | Params | FLOPs/2 | Remarks |
| --- | --- | --- | ---: | ---: | ---: | ---: | ---: | --- |
| ResNet-18 | FDV1 | Gluon | 0.9976 | 0.9976 | 0.9952 | 11,177,538 | 1,819.90M | Training ([log](https://github.com/osmr/facedetver/releases/download/v0.0.3/resnet18_fdv1-0014-a03f116e.params.log)) |
| ResNet-18 | FDV1 | PyTorch | 0.9976 | 0.9976 | 0.9952 | 11,177,538 | 1,819.90M | Training ([log](https://github.com/osmr/facedetver/releases/download/v0.0.3/resnet18_fdv1-0011-85475034.pth.log)) |
| ResNet-18 | FDV2 | Gluon | 0.9971 | 0.9971 | 0.9942 | 11,177,538 | 1,819.90M | Training ([log](https://github.com/osmr/facedetver/releases/download/v0.0.3/resnet18_fdv2-0011-391f0c7e.params.log)) |
| ResNet-18 | FDV2 | PyTorch | 0.9971 | 0.9971 | 0.9942 | 11,177,538 | 1,819.90M | Training ([log](https://github.com/osmr/facedetver/releases/download/v0.0.3/resnet18_fdv2-0009-e1a3e6f2.pth.log)) |