圖檔人臉識别
import cv2
filepath = "img/xingye-1.png"
img = cv2.imread(filepath) # 讀取圖檔
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 轉換灰色
# OpenCV人臉識别分類器
classifier = cv2.CascadeClassifier(
"C:\Python36\Lib\site-packages\opencv-master\data\haarcascades\haarcascade_frontalface_default.xml"
)
color = (0, 255, 0) # 定義繪制顔色
# 調用識别人臉
faceRects = classifier.detectMultiScale(
gray, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32))
if len(faceRects): # 大于0則檢測到人臉
for faceRect in faceRects: # 單獨框出每一張人臉
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()
視訊人臉識别
# -*- coding:utf-8 -*-
# OpenCV版本的視訊檢測
import cv2
# 圖檔識别方法封裝
def discern(img):
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cap = cv2.CascadeClassifier(
"C:\Python36\Lib\site-packages\opencv-master\data\haarcascades\haarcascade_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)
# 擷取攝像頭0表示第一個攝像頭
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'):
break
cap.release() # 釋放攝像頭
cv2.destroyAllWindows() # 釋放視窗資源
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