ghost
ML 1. import cv2 from matplotlib import pyplot as plt crick1 = cv2.imread('OIP.jpg',1) plt.imshow(crick1[:,:,::-1]) import cv2 from matplotlib import pyplot as plt crick1 = cv2.imread('OIP.jpg',1) plt.imshow(crick1[:,:,::-1]) gray_img = cv2.cvtColor (crick1, cv2.COLOR_BGR2GRAY) plt.imshow(gray_img,cmap='gray') import cv2 crick1 = cv2.imread('OIP.jpg',1) gray_img = cv2.cvtColor (crick1, cv2.COLOR_BGR2GRAY) haar_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') mouth_cascade = cv2.CascadeClassifier('haarcascade_mcs_mouth.xml') faces = haar_cascade.detectMultiScale(gray_img,1.3,5) for (x, y, w, h) in faces: cv2.rectangle(crick1, (x, y), (x+w, y+h), (255, 0, 0), 2) roi_gray = gray_img[y:y+h, x:x+w] roi_color = crick1[y:y+h, x:x+w] mouth = mouth_cascade.detectMultiScale(roi_gray) for (ex,ey,ew,eh) in mouth: cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(255,0,0)...