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Python調用OpenCV實現人臉識別

source display document down char name 實現 cvt config

[硬件環境]

Win10 64位

[軟件環境]

Python版本:2.7.3

IDE:JetBrains PyCharm 2016.3.2

Python庫:

1.1) OpenCV

其他:

1.1) OpenCV Python庫

[搭建過程]

OpenCV Python庫:

1. 安裝opencv_python-3.2.0.6-cp27-cp27m-win32.whl

[相關代碼]

import cv2
import numpy as np

cv2.namedWindow("test") # Create a window
cap = cv2.VideoCapture(0) #Open camera one
success, frame = cap.read() #Read one frame print("Camera open operation is: ", success); color = (255,0,0) #Config the color classfier = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml") #Make sure this xml file is in the same directory with py file #
Otherwise change it to absolute directory. This xml file can be found in D:\My Documents\Downloads\opencv\sources\data\haarcascades while success: success, frame = cap.read() size = frame.shape[:2] # image = np.zeros(size, dtype = np.float16) # image = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) #
cv2.equalizeHist(image, image) # #Below three lines config the minimal image size divisor = 8 h, w = size minSize = ((int)(w/divisor), (int)(h/divisor)) faceRects = classfier.detectMultiScale(image, 1.2, 2, cv2.CASCADE_SCALE_IMAGE, minSize) #Face detect if len(faceRects) > 0:#If face array length > 0 for faceRect in faceRects: #Draw a rectangle for every face xf, yf, wf, hf = faceRect x = int((float)(xf)) y = int((float)(yf)) w = int((float)(wf)) h = int((float)(hf)) cv2.rectangle(frame, (x, y), (x + w, y + h), color) cv2.circle(frame, ((int)(x + 1.2 * w / 4), (int)(y + h / 3)), min((int)(w / 8), (int)(h / 8)), (255, 0, 0)) cv2.circle(frame, ((int)(x + 2.8 * w / 4), (int)(y + h / 3)), min((int)(w / 8), (int)(h / 8)), (255, 0, 0)) #cv2.rectangle(frame, ((int)(x + 3 * w / 8, (int)(y + 3 * h / 4))), ((int)(x + 5 * w / 8), (int)(y + 7 * h / 8)), (255, 0, 0)) cv2.imshow("test", frame) #Display image key = cv2.waitKey(10) c = chr(key & 255) if c in [q, Q, chr(27)]: break cv2.destroyWindow("test")

Python調用OpenCV實現人臉識別