85 lines
3.6 KiB
Python
85 lines
3.6 KiB
Python
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import cv2
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import mediapipe as mp
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import time
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import math
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import threading
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import pyautogui
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cap = cv2.VideoCapture(0)
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pyautogui.PAUSE = 0.01
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mpHands = mp.solutions.hands
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hands = mpHands.Hands(max_num_hands=1, min_tracking_confidence=0.95, min_detection_confidence=0.90)
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mpDraw = mp.solutions.drawing_utils
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mov_dis = 0.2379
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click_dis = 0.2823
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sensitivity = 3.5
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testing8_12 = []
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testing0_5 = []
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testing3_5 = []
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def get_distance(first, second, height, width):
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dist_x = (results.multi_hand_landmarks[0].landmark[first].x - results.multi_hand_landmarks[0].landmark[
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second].x) * width
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dist_y = (results.multi_hand_landmarks[0].landmark[first].y - results.multi_hand_landmarks[0].landmark[
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second].y) * height
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return math.sqrt(abs(dist_x ** 2 + dist_y ** 2))
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def dist(point1, point2, pointa, pointb, pointc, pointd):
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dis12 = get_distance(point1, point2, h, w)
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distab = get_distance(pointa, pointb, h, w)
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distcd = get_distance(pointc, pointd, h, w)
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testing8_12.append(dis12)
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testing0_5.append(distab)
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testing3_5.append(distcd)
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print(f"8-12: {round(sum(testing8_12)/len(testing8_12), 2)} | 0-5 {round(sum(testing0_5)/len(testing0_5), 2)} | 3-5 {round(sum(testing3_5)/len(testing3_5), 2)}")
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x, y = None, None
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click = False
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while True:
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success, img = cap.read()
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h, w, c = img.shape
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imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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results = hands.process(imgRGB)
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if results.multi_hand_landmarks:
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dist_palm = round(get_distance(0, 5, h, w))
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if not x and not y:
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x, y = results.multi_hand_landmarks[0].landmark[4].x * w, results.multi_hand_landmarks[0].landmark[4].y * h
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dis_1 = get_distance(12, 8, h, w)
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cv2.putText(img, f"""MOVE: {round(dis_1)}/{round(mov_dis * dist_palm, 2)} - {"true" if dis_1 < mov_dis * dist_palm else "false"}""", (0, 15),
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cv2.FONT_HERSHEY_PLAIN, 1.5, (255, 0, 255), thickness=2)
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cv2.putText(img, f"""CLICK: {round(get_distance(5, 3, h, w))}/{round(click_dis * dist_palm, 2)} - {"true" if get_distance(5, 3, h, w) < click_dis * dist_palm else "false"}""", (0, 40),
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cv2.FONT_HERSHEY_PLAIN, 1.5, (255, 0, 255), thickness=2)
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cv2.putText(img,
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f"""DRAG: {"true" if dis_1 < mov_dis * dist_palm and get_distance(5, 3, h, w) < click_dis * dist_palm else "false"}""",
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(0, 65),
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cv2.FONT_HERSHEY_PLAIN, 1.5, (255, 0, 255), thickness=2)
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for handLms in results.multi_hand_landmarks:
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mpDraw.draw_landmarks(img, handLms, mpHands.HAND_CONNECTIONS)
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if dis_1 < mov_dis * dist_palm and get_distance(5, 3, h, w) < click_dis * dist_palm:
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pyautogui.mouseDown()
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pyautogui.moveRel(-(results.multi_hand_landmarks[0].landmark[8].x * w - x) * sensitivity,
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(results.multi_hand_landmarks[0].landmark[8].y * h - y) * sensitivity, duration=0.001)
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elif dis_1 < mov_dis * dist_palm:
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pyautogui.mouseUp()
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pyautogui.moveRel(-(results.multi_hand_landmarks[0].landmark[8].x * w - x) * sensitivity,
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(results.multi_hand_landmarks[0].landmark[8].y * h - y) * sensitivity, duration=0.001)
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elif get_distance(5, 3, h, w) < click_dis * dist_palm and not click:
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pyautogui.mouseUp()
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pyautogui.click()
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click = True
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else:
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pyautogui.mouseUp()
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click = False
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x, y = results.multi_hand_landmarks[0].landmark[8].x * w, results.multi_hand_landmarks[0].landmark[8].y * h
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dist(8, 12, 0, 5, 3, 5)
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else:
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x, y = None, None
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cv2.imshow("Image", img)
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cv2.waitKey(1)
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