pythonopencvface-detectioneye-detection

Python OpenCV - Detect eyes and save


I am new to OpenCV. I need to detect the eyes using opencv and save them in a folder for further classification. I have written following script for the same:

import numpy as np
import cv2

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')

cap = cv2.VideoCapture(0)
while True:
     ret, img = cap.read()
     gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
     faces = face_cascade.detectMultiScale(gray, 1.3, 5)
     count=1
     for (x,y,w,h) in faces:
         cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
         roi_gray = gray[y:y+h, x:x+w]
         roi_color = img[y:y+h, x:x+w]

         eyes = eye_cascade.detectMultiScale(roi_gray)
         for (ex,ey,ew,eh) in eyes:
             crop_img = roi_color[ey: ey + eh, ex: ex + ew]
             cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
             s="{0}.jpg"
             s1='/home/kushal/Pictures/Webcam/'+s.format(count)
             count=count+1
             cv2.imwrite(s1,crop_img)
cv2.imshow('img',img)
k = cv2.waitKey(30) & 0xff
if k == 27:
    break

cap.release()
cv2.destroyAllWindows()

I want to save as many eye images as possible. But I am getting only 3-4 eye images saved. Is it possible to get one frame or one image per second? What should be the modification done in this code?


Solution

  • Move count=1 outside of while-loop.

    count = 1
    while True:
        pass
        #your code
    

    And the indent of cv2.imshow is not that correct.

    import numpy as np
    import cv2
    
    face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
    eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
    
    cap = cv2.VideoCapture(0)
    count=1
    
    while True:
        ret, img = cap.read()
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, 1.2, 5)
        for (x,y,w,h) in faces:
            cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
            roi_gray = gray[y:y+h, x:x+w]
            roi_color = img[y:y+h, x:x+w]
    
            eyes = eye_cascade.detectMultiScale(roi_gray)
            for (ex,ey,ew,eh) in eyes:
                print(count)
                crop_img = roi_color[ey: ey + eh, ex: ex + ew]
                cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
                s1='tmp/{}.jpg'.format(count)
                count=count+1
                cv2.imwrite(s1,crop_img)
    
        cv2.imshow('img',img)
        k = cv2.waitKey(30) & 0xff
        if k == 27:
            break
    
    cap.release()
    cv2.destroyAllWindows()