Fiber/gesture-recognition
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修改了手势模型，优化指关节识别

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添加了测试框架
This commit is contained in:
Tabs 2022-06-13 15:48:59 +08:00
parent 25baacbca9
commit d0137634ed
1 changed files with 30 additions and 7 deletions
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37
demo.py
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@ -11,6 +11,8 @@ import mediapipe as mp
import cv2 import cv2
# import HandDetector # import HandDetector
import math import math
from datetime import datetime
import time
# 旋转函数 # 旋转函数
@ -200,28 +202,34 @@ class HandDetector:
:return: 竖起手指的列表 :return: 竖起手指的列表
""" """
knuckles = [] knuckles = []
distan = 10
if self.results.multi_hand_landmarks: if self.results.multi_hand_landmarks:
my_hand_type = self.hand_type() my_hand_type = self.hand_type()
# Thumb # Thumb
xx = self.re_lmList[self.tipIds[0]][0]
yy = self.re_lmList[self.tipIds[0] - 1][0]
if my_hand_type == "Right": if my_hand_type == "Right":
if self.lmList[self.tipIds[0]][0] > self.lmList[self.tipIds[0] - 1][0]: if -distan < xx - yy < distan:
knuckles.append(2)
elif xx > yy:
knuckles.append(1) knuckles.append(1)
else: else:
knuckles.append(0) knuckles.append(0)
else: else:
if self.lmList[self.tipIds[0]][0] < self.lmList[self.tipIds[0] - 1][0]: if -distan < xx - yy < distan:
knuckles.append(2)
elif xx < yy:
knuckles.append(1) knuckles.append(1)
else: else:
knuckles.append(0) knuckles.append(0)
# 12 knuckles # 12 knuckles
distan = 0.22
for i in range(1, 5): for i in range(1, 5):
for j in range(4): for j in range(3):
xx = self.lmList[self.tipIds[i]-j][1] xx = self.re_lmList[self.tipIds[i]-j][1]
yy = self.lmList[self.tipIds[i]-j - 1][1] yy = self.re_lmList[self.tipIds[i]-j - 1][1]
if -distan < xx - yy < distan: if -distan < xx - yy < distan:
knuckles.append(2) knuckles.append(2)
elif xx < yy: elif xx > yy:
knuckles.append(1) knuckles.append(1)
else: else:
knuckles.append(0) knuckles.append(0)
@ -248,6 +256,8 @@ class Main:
def gesture_recognition(self): def gesture_recognition(self):
self.detector = HandDetector() self.detector = HandDetector()
xl = [] # 特征值存储
startTime = time.time()
while True: while True:
frame, img = self.camera.read() frame, img = self.camera.read()
img = self.detector.find_hands(img) img = self.detector.find_hands(img)
@ -282,6 +292,19 @@ class Main:
elif x1 and (x2 == 0, x3 == 0, x4 == 0, x5 == 0): elif x1 and (x2 == 0, x3 == 0, x4 == 0, x5 == 0):
cv2.putText(img, "GOOD!", (x_1, y_1), cv2.FONT_HERSHEY_PLAIN, 3, cv2.putText(img, "GOOD!", (x_1, y_1), cv2.FONT_HERSHEY_PLAIN, 3,
(0, 0, 255), 3) (0, 0, 255), 3)
print(time.time() - startTime)
if (time.time() - startTime) < 2: # 手势存储时间
xl.append([x1, x2, x3, x4, x5])
cv2.putText(img, 'Please put the gesture to be stored in 1 second', (50, 50),
cv2.FONT_HERSHEY_PLAIN, 1.2, (255, 255, 255), 2)
else: # 开始手势存储
# startTime = time.time()
cv2.putText(img, 'Gesture stored, recognition started', (50, 50),
cv2.FONT_HERSHEY_PLAIN, 1.2, (255, 255, 255), 2)
else:
startTime = time.time() # 当检测不到手势时，初始化手势存储
cv2.putText(img, 'Please put the gesture to be stored in 1 second', (50, 50), cv2.FONT_HERSHEY_PLAIN,
1.2, (255, 255, 255), 2)
cv2.imshow("camera", img) cv2.imshow("camera", img)
key = cv2.waitKey(1) key = cv2.waitKey(1)