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78 lines
2.2 KiB
78 lines
2.2 KiB
import sqlite3
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conn = sqlite3.connect('info.db')
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c = conn.cursor()
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print ("数据库打开成功")
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strs = "INSERT INTO XYZ VALUES ("
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import cv2
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import mediapipe as mp
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mp_drawing = mp.solutions.drawing_utils
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mp_drawing_styles = mp.solutions.drawing_styles
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mp_hands = mp.solutions.hands
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num = 0
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# For webcam input:
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cap = cv2.VideoCapture(0)
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with mp_hands.Hands(
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model_complexity=0,
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max_num_hands=2,
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min_detection_confidence=0.5,
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min_tracking_confidence=0.5) as hands:
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while cap.isOpened():
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success, image = cap.read()
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if not success:
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print("Ignoring empty camera frame.")
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# If loading a video, use 'break' instead of 'continue'.
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continue
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# To improve performance, optionally mark the image as not writeable to
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# pass by reference.
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image.flags.writeable = False
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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results = hands.process(image)
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# Draw the hand annotations on the image.
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image.flags.writeable = True
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image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
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aa=0
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if results.multi_hand_landmarks:
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wt = []
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for i in range(42 * 3):
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wt.append(0)
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for i,hand_landmarks in enumerate(results.multi_hand_landmarks):
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if (results.multi_handedness[i].classification[0].label)=="Left":
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num = 0
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else:
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num =1
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for j,handlms in enumerate(hand_landmarks.landmark):
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wt[num*21*3+j*3],wt[num*21*3+j*3+1],wt[num*21*3+j*3+2] = handlms.x, handlms.y, handlms.z
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mp_drawing.draw_landmarks(
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image,
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hand_landmarks,
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mp_hands.HAND_CONNECTIONS,
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mp_drawing_styles.get_default_hand_landmarks_style(),
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mp_drawing_styles.get_default_hand_connections_style())
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# Flip the image horizontally for a selfie-view display.
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cv2.imshow('MediaPipe Hands', cv2.flip(image, 1))
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ctl = cv2.waitKey(5)
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if ctl == ord('q'):
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break
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elif ctl==ord('s'):
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strs = "INSERT INTO XYZ VALUES ("
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word = "\'"+input()+"\',"
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strs+=word
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print(aa)
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for i in wt:
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strs+=str(i)[:7]+","
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strs = strs[:-1] + ");"
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print(strs)
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c.execute(strs)
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cap.release()
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conn.commit()
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print ("数据插入成功")
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conn.close() |