圖片人臉識(shí)別

import cv2filepath = 'img/xingye-1.png'img = cv2.imread(filepath) # 讀取圖片gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 轉(zhuǎn)換灰色# OpenCV人臉識(shí)別分類(lèi)器classifier = cv2.CascadeClassifier( 'C:Python36Libsite-packagesopencv-masterdatahaarcascadeshaarcascade_frontalface_default.xml')color = (0, 255, 0) # 定義繪制顏色# 調(diào)用識(shí)別人臉faceRects = classifier.detectMultiScale( gray, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32))if len(faceRects): # 大于0則檢測(cè)到人臉 for faceRect in faceRects: # 單獨(dú)框出每一張人臉 x, y, w, h = faceRect # 框出人臉 cv2.rectangle(img, (x, y), (x + h, y + w), color, 2) # 左眼 cv2.circle(img, (x + w // 4, y + h // 4 + 30), min(w // 8, h // 8), color) #右眼 cv2.circle(img, (x + 3 * w // 4, y + h // 4 + 30), min(w // 8, h // 8), color) #嘴巴 cv2.rectangle(img, (x + 3 * w // 8, y + 3 * h // 4), (x + 5 * w // 8, y + 7 * h // 8), color)cv2.imshow('image', img) # 顯示圖像c = cv2.waitKey(10)cv2.waitKey(0)cv2.destroyAllWindows()

視頻人臉識(shí)別

# -*- coding:utf-8 -*-# OpenCV版本的視頻檢測(cè)import cv2# 圖片識(shí)別方法封裝def discern(img): gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) cap = cv2.CascadeClassifier( 'C:Python36Libsite-packagesopencv-masterdatahaarcascadeshaarcascade_frontalface_default.xml' ) faceRects = cap.detectMultiScale( gray, scaleFactor=1.2, minNeighbors=3, minSize=(50, 50)) if len(faceRects): for faceRect in faceRects: x, y, w, h = faceRect cv2.rectangle(img, (x, y), (x + h, y + w), (0, 255, 0), 2) # 框出人臉 cv2.imshow('Image', img)# 獲取攝像頭0表示第一個(gè)攝像頭cap = cv2.VideoCapture(0)while (1): # 逐幀顯示 ret, img = cap.read() # cv2.imshow('Image', img) discern(img) if cv2.waitKey(1) & 0xFF == ord(’q’): breakcap.release() # 釋放攝像頭cv2.destroyAllWindows() # 釋放窗口資源

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