InsightFace#
2D and 3D Face Analysis Project
Quick Start#
Install#
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple insightface==0.7.3
Quick Example#
import cv2
import numpy as np
import insightface
from insightface.app import FaceAnalysis
from insightface.data import get_image as ins_get_image
app = FaceAnalysis(providers=['CUDAExecutionProvider', 'CPUExecutionProvider'])
app.prepare(ctx_id=0, det_size=(640, 640))
img = ins_get_image('t1')
faces = app.get(img)
rimg = app.draw_on(img, faces)
cv2.imwrite("./t1_output.jpg", rimg)
Model Zoo#
| Name | Detection Model | Recognition Model | Alignment | Attributes | Model-Size | Link | Auto |
|---|---|---|---|---|---|---|---|
| antelopev2 | SCRFD-10GF | ResNet100@Glint360K | 2d106 & 3d68 | Gender&Age | 407MB | link | N |
| buffalo_l | SCRFD-10GF | ResNet50@WebFace600K | 2d106 & 3d68 | Gender&Age | 326MB | link | Y |
| buffalo_m | SCRFD-2.5GF | ResNet50@WebFace600K | 2d106 & 3d68 | Gender&Age | 313MB | link | N |
| buffalo_s | SCRFD-500MF | MBF@WebFace600K | 2d106 & 3d68 | Gender&Age | 159MB | link | N |
| buffalo_sc | SCRFD-500MF | MBF@WebFace600K | - | - | 16MB | link | N |
Buffalo#
人脸检测 → 关键点 → 人脸识别 → 属性分析
det_10g.onnx: 人脸检测2d106det.onnx: 2D关键点1k3d68.onnx: 3D关键点w600k_r50.onnx: 人脸识别（核心）genderage.onnx: 属性分析
Tips#
WebFace600K (600K identities) is the same as WebFace12M (12 million images). It is the first 3 parts of the 42M compressed package.
WebFace42M datasets cannot access! CANNOT open https://www.face-benchmark.org/download.html
Examples#
# 人体检测
examples/person_detection/scrfd_person.py
# 人脸检测
examples/face_detection/detect.py
# 对齐2D人脸关键点
alignment/coordinate_reg/image_infer.py
# 性别年龄判断
attribute/gender_age/test.py
# 调用人脸识别模型
examples/face_recognition/insightface_app.py # 记得更换成要对比的两张人脸的路径
Screenshots#
