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import cv2
import mediapipe as mp
mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands
handlist = []
v_4_cx = 0
v_8_cx = 0
v_12_cx = 0
v_16_cx = 0
v_20_cx = 0
v_4_cy = 0
h = 0
w = 0
cap = cv2.VideoCapture(0)
with mp_hands.Hands(False, min_detection_confidence=0.5, min_tracking_confidence=0.5) as hands:
while cap.isOpened():
success, image = cap.read()
if not success:
print("Ignoring empty camera frame.")
# If loading a video, use 'break' instead of 'continue'.
continue
# Flip the image horizontally for a later selfie-view display, and convert
# the BGR image to RGB.
image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)
# To improve performance, optionally mark the image as not writeable to
# pass by reference.
image.flags.writeable = False
results = hands.process(image)
text = "NA"
# Draw the hand annotations on the image.
image.flags.writeable = True
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
if results.multi_hand_landmarks:
for hand_landmarks in results.multi_hand_landmarks:
assert isinstance(hand_landmarks.landmark, object)
for id, landmks in enumerate(hand_landmarks.landmark):
# print(id, landmks)
h, w, c = image.shape
#print("windwow")
#print(h)
#print(w)
#print("end")
cx, cy = int(landmks.x * w), int(landmks.y * h)
handlist.append([id, cx, cy])
if id == 4:
v_4_cx = cx
v_4_cy = cy
if id == 8:
v_8_cx = cx
if id == 12:
v_12_cx = cx
if id == 16:
v_16_cx = cx
if id == 20:
v_20_cx = cx
if id == 0:
v_0_cx = cx
v_0_cy = cy
if v_4_cy > v_0_cy and (v_8_cx - v_12_cx) < 50 and (v_16_cx - v_20_cx) < 50:
text = "Not Good"
if v_4_cy < v_0_cy and (v_8_cx - v_12_cx) < 50 and (v_16_cx - v_20_cx) < 50:
text = "Good"
#print(v_4_cy)
#print(v_0_cy)
# if handlist[4][cx]= handlist[4][cx] :
# cv2.circle(image, (cx, cy), 10, (255, 0, 255), cv2.FILLED)
mp_drawing.draw_landmarks(image, hand_landmarks, mp_hands.HAND_CONNECTIONS)
cv2.putText(image, text, (50, 120), cv2.FONT_HERSHEY_PLAIN , 2, (255,0,0))
cv2.imshow('Thumbsup', image)
# print(handlist)
if cv2.waitKey(5) & 0xFF == 27:
break
cap.release() |