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少走弯路：OpenCV、insightface 等多方案人脸推理和识别

news 2025/8/22 15:26:08

脑壳有包又花时间折腾了一下，其实之前也折腾过，主要是新看了一个方法

在下图中查找脸部

第一种方案：

使用了opencv 的cv2.FaceDetectorYN. ，完整代码如下：

import numpy as np
import cv2img=cv2.imread("00000523.jpg")
# img=cv2.resize(img, new_shape)
faceDetector=cv2.FaceDetectorYN.create("opencv_zoo/models/face_detection_yunet/face_detection_yunet_2023mar.onnx","",(img.shape[1],img.shape[0]))
faces = faceDetector.detect(img)
f = faces[1]
for ps in f:x=int(ps[0])y=int(ps[1])w=int(ps[2])h=int(ps[3])s=ps[14]# print(x,y,w,h,s)cv2.rectangle(img, (x, y), (x+w, y+h), (0,0,255), 2)
cv2.namedWindow("d",0);
cv2.resizeWindow("d", int(img.shape[1]/2), int(img.shape[0]/2));
cv2.imshow("d",img)
cv2.waitKey()
# cv2.destoryAllWindows()
cv2.destroyAllWindows()

结果如下：

第二种方案：

使用了 cv2.CascadeClassifier("D:\\opencv-4.52\\data\\haarcascades\\haarcascade_frontalface_default.xml")

import numpy as np
import cv2img=cv2.imread("00000523.jpg")
cas_default = cv2.CascadeClassifier("D:\\opencv-4.52\\data\\haarcascades\\haarcascade_frontalface_default.xml")
faces_default = cas_default.detectMultiScale(img)
for (x,y,w,h) in faces_default:print(x,y,w,h)cv2.rectangle(img, (x, y), (x+w, y+h), (0,255,255), 2)
cv2.namedWindow("d",0);
cv2.resizeWindow("d", int(img.shape[1]/2), int(img.shape[0]/2));
cv2.imshow("d",img)
cv2.waitKey()
# cv2.destoryAllWindows()
cv2.destroyAllWindows()

结果如下：

以上两种都是opencv的自带方案，要么找脸不全，要么错误的找脸

然后是insightface 的方案：

import insightface
import cv2
import numpy as npmodel = insightface.app.FaceAnalysis()
model.prepare(ctx_id=0, det_thresh=0.45)face_img = cv2.imread('00000523.jpg')
rgb_small_frame = face_img[:, :, ::-1]
faces = model.get(rgb_small_frame)for r in faces:box=r.bbox.astype(int)color=(0, 0, 255)cv2.rectangle(face_img, (box[0], box[1]), (box[2], box[3]), color, 2)
cv2.namedWindow("d",0);
cv2.resizeWindow("d", int(face_img.shape[1]/2), int(face_img.shape[0]/2));
cv2.imshow("d",face_img)
cv2.waitKey()
cv2.destroyAllWindows()