Efficient face detection using SCRFD.
pip install scrfd
from scrfd import SCRFD, Threshold
from PIL import Image
face_detector = SCRFD.from_path("./models/scrfd.onnx")
threshold = Threshold(probability=0.4)
image = Image.open("./images/solvay_conference_1927.jpg").convert("RGB")
faces = face_detector.detect(image, threshold=threshold)
for face in faces:
bbox = face.bbox
kps = face.keypoints
score = face.probability
print(f"{bbox=}, {kps=}, {score=}")
FAQs
Efficient face detection using SCRFD
We found that scrfd demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Company News
Socket is joining TC54 to help develop standards for software supply chain security, contributing to the evolution of SBOMs, CycloneDX, and Package URL specifications.
Security News
PyPI now allows maintainers to archive projects, improving security and helping users make informed decisions about their dependencies.
Research
Security News
Malicious npm package postcss-optimizer delivers BeaverTail malware, targeting developer systems; similarities to past campaigns suggest a North Korean connection.