for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
id, confidence = recognizer.predict(gray[y:y + h, x:x + w])
# Check if confidence is less them 100 ==> "0" is perfect match
if (confidence < 100):
id = names[id]
confidence = " {0}%".format(round(100 - confidence))
else:
id = "unknown"
confidence = " {0}%".format(round(100 - confidence))
#--------------
#crop_img = img[top:bottom, left:right]
crop_img = img[y:y + h, x:x + w]
#fname = "output_data/thumbnail({}).png".format(xx)
#cv2.imwrite(fname, crop_img)
text = _classify.specify(crop_img)
#print(text)
#--------------
cv2.putText(img, str(text), (x + 5, y - 5), font, 1, (255, 255, 255),
2)
cv2.putText(img, str(confidence), (x + 5, y + h - 5), font, 1,
(255, 255, 0), 1)
cv2.imshow('camera', img)
k = cv2.waitKey(10) & 0xff # Press 'ESC' for exiting video
if k == 27:
break
# Do a bit of cleanup
print("\n [INFO] Exiting Program and cleanup stuff")
cam.release()
cv2.destroyAllWindows()
