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HandDetector.py
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HandDetector.py
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import cv2
import mediapipe as mp
import time
import logging
logger = logging.getLogger(__name__)
class HandDetector:
def __init__(
self,
static_image_mode=False,
max_num_hands=2,
min_detection_confidence=0.5,
min_tracking_confidence=0.5,
):
self.static_image_mode = static_image_mode
self.max_num_hands = max_num_hands
self.min_detection_confidence = min_detection_confidence
self.min_tracking_confidence = min_tracking_confidence
self.mp_hands = mp.solutions.hands
self.mp_draw = mp.solutions.drawing_utils
self.hands = self.mp_hands.Hands(
self.static_image_mode, self.max_num_hands, self.min_detection_confidence, self.min_tracking_confidence
)
def find_hands(self, img, draw=True):
imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
results = self.hands.process(imgRGB)
if results.multi_hand_landmarks:
for hand in results.multi_hand_landmarks:
if draw:
self.mp_draw.draw_landmarks(img, hand, self.mp_hands.HAND_CONNECTIONS)
return img
def find_position(self, img, hand_num=0, draw=True):
imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
results = self.hands.process(imgRGB)
lm_list = []
if results.multi_hand_landmarks:
my_hand = results.multi_hand_landmarks[hand_num]
for _id, lm in enumerate(my_hand.landmark):
h, w, c = img.shape
cx, cy = int(lm.x * w), int(lm.y * h)
lm_list.append([_id, cx, cy])
if draw:
cv2.circle(img, (cx, cy), 10, (255, 0, 255), cv2.FILLED)
return lm_list
def main():
cap = cv2.VideoCapture(0)
pTime = 0
cTime = 0
detector = HandDetector()
while True:
success, img = cap.read()
img = detector.find_hands(img)
# lm_list_hand_0 = detector.find_position(img, hand_num=0)
cTime = time.time()
fps = 1 / (cTime - pTime)
pTime = cTime
cv2.putText(
img,
str(int(fps)),
(10, 70),
cv2.FONT_HERSHEY_PLAIN,
3,
(255, 255, 255),
3,
)
cv2.imshow("Image", img)
cv2.waitKey(1)
if __name__ == "__main__":
main()