Portable RetinaFace in Pytorch. Easy to use as loss function for bounding boxes and facial landmark.
Prerequisites:
- Python 3.x with argparse, torch, and PIL (Pillow)
- Trained RetinaFace model download from Google Drive (default path: './weights/Resnet50_Final.pth')
from loss import RetinaFaceLoss
detector = RetinaFaceDetector()
# Preprocess image
img_A, _, _, _ = detector.preprocess_image("./data/A.jpg")
img_B, _, _, _ = detector.preprocess_image("./data/B.jpg")
loss = RetinaFaceLoss()
bbox_loss = loss.bounding_box_loss(img_A, img_B)
print("Bounding box loss: ", bbox_loss)
# Landmark loss
landmark_loss = loss.landmark_loss(img_A, img_B)
print("Landmark loss: ", landmark_loss)Instructions for running run_loss.py:
Steps:
- Open a terminal.
- Navigate to the directory containing
run_loss.py. - Run:
python run_loss.py [options]python run_loss.py --help
usage: run_loss.py [-h] [-p_A IMAGE_PATH_A] [-p_B IMAGE_PATH_B] [-m TRAINED_MODEL] [--network NETWORK] [--gpu] [--confidence_threshold CONFIDENCE_THRESHOLD] [--top_k TOP_K] [--nms_threshold NMS_THRESHOLD]
[--keep_top_k KEEP_TOP_K]
optional arguments:
-h, --help show this help message and exit
-p_A IMAGE_PATH_A, --image_path_A IMAGE_PATH_A
Path to image A
-p_B IMAGE_PATH_B, --image_path_B IMAGE_PATH_B
Path to image B
-m TRAINED_MODEL, --trained_model TRAINED_MODEL
Path to trained model
--network NETWORK Backbone network mobile0.25 or resnet50
--gpu Use gpu inference
--confidence_threshold CONFIDENCE_THRESHOLD
confidence_threshold
--top_k TOP_K top_k
--nms_threshold NMS_THRESHOLD
nms_threshold
--keep_top_k KEEP_TOP_K
keep_top_k
Instructions for running run_detector.py:
Steps:
- Open a terminal.
- Navigate to the directory containing
run_detector.py. - Run:
python run_detector.py [options]
python run_detector.py --help
usage: run_detector.py [-h] [-p IMAGE_PATH] [-m TRAINED_MODEL] [--network NETWORK] [--gpu] [--confidence_threshold CONFIDENCE_THRESHOLD] [--top_k TOP_K] [--nms_threshold NMS_THRESHOLD] [--keep_top_k KEEP_TOP_K] [-s]
[--vis_thres VIS_THRES]
Retinaface
optional arguments:
-h, --help show this help message and exit
-p IMAGE_PATH, --image_path IMAGE_PATH
Trained state_dict file path to open
-m TRAINED_MODEL, --trained_model TRAINED_MODEL
Trained state_dict file path to open
--network NETWORK Backbone network mobile0.25 or resnet50
--gpu Use gpu inference
--confidence_threshold CONFIDENCE_THRESHOLD
confidence_threshold
--top_k TOP_K top_k
--nms_threshold NMS_THRESHOLD
nms_threshold
--keep_top_k KEEP_TOP_K
keep_top_k
-s, --save_image show detection results
--vis_thres VIS_THRES
visualization_threshold