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实现了正面手势测试，可添加新手势并加上标签

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This commit is contained in:
Tabs 2022-06-13 17:23:55 +08:00
parent d0137634ed
commit 85fb3ad83c
1 changed files with 30 additions and 31 deletions
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61
demo.py
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@ -13,6 +13,7 @@ import cv2
import math
from datetime import datetime
import time
import numpy as np
# 旋转函数
@ -229,7 +230,7 @@ class HandDetector:
yy = self.re_lmList[self.tipIds[i]-j - 1][1]
if -distan < xx - yy < distan:
knuckles.append(2)
elif xx > yy:
elif xx < yy:
knuckles.append(1)
else:
knuckles.append(0)
@ -256,53 +257,51 @@ class Main:
def gesture_recognition(self):
self.detector = HandDetector()
xl = [] # 特征值存储
gesture_store = {}
startTime = time.time()
stored_round = 1
stored_flag = 0
xl = np.zeros((1, 13)) # 特征值存储
while True:
frame, img = self.camera.read()
img = self.detector.find_hands(img)
lm_list, bbox = self.detector.find_position(img)
if lm_list:
re_lm_list = self.detector.revolve(img)
x_1, y_1 = bbox["bbox"][0], bbox["bbox"][1]
x1, x2, x3, x4, x5 = self.detector.re_fingers_up()
knucks = self.detector.knuckles_up()
# x1, x2, x3, x4, x5 = self.detector.re_fingers_up()
#
# if (x2 == 1 and x3 == 1) and (x4 == 0 and x5 == 0 and x1 == 0):
# cv2.putText(img, "GOOD!", (x_1, y_1), cv2.FONT_HERSHEY_PLAIN, 3,
# (0, 0, 255), 3)
if (x2 == 1 and x3 == 1) and (x4 == 0 and x5 == 0 and x1 == 0):
cv2.putText(img, "2_TWO", (x_1, y_1), cv2.FONT_HERSHEY_PLAIN, 3,
(0, 0, 255), 3)
elif (x2 == 1 and x3 == 1 and x4 == 1) and (x1 == 0 and x5 == 0):
cv2.putText(img, "3_THREE", (x_1, y_1), cv2.FONT_HERSHEY_PLAIN, 3,
(0, 0, 255), 3)
elif (x2 == 1 and x3 == 1 and x4 == 1 and x5 == 1) and (x1 == 0):
cv2.putText(img, "4_FOUR", (x_1, y_1), cv2.FONT_HERSHEY_PLAIN, 3,
(0, 0, 255), 3)
elif x1 == 1 and x2 == 1 and x3 == 1 and x4 == 1 and x5 == 1:
cv2.putText(img, "5_FIVE", (x_1, y_1), cv2.FONT_HERSHEY_PLAIN, 3,
(0, 0, 255), 3)
elif x2 == 1 and x1 == 0 and (x3 == 0, x4 == 0, x5 == 0):
cv2.putText(img, "1_ONE", (x_1, y_1), cv2.FONT_HERSHEY_PLAIN, 3,
(0, 0, 255), 3)
elif x1 == 1 and x2 == 1 and (x3 == 0, x4 == 0, x5 == 0):
cv2.putText(img, "8_EIGHT", (x_1, y_1), cv2.FONT_HERSHEY_PLAIN, 3,
(0, 0, 255), 3)
elif x1 == 1 and x5 == 1 and (x3 == 0, x4 == 0, x5 == 0):
cv2.putText(img, "6_SIX", (x_1, y_1), cv2.FONT_HERSHEY_PLAIN, 3,
(0, 0, 255), 3)
elif x1 and (x2 == 0, x3 == 0, x4 == 0, x5 == 0):
cv2.putText(img, "GOOD!", (x_1, y_1), cv2.FONT_HERSHEY_PLAIN, 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])
if (time.time() - startTime) < 3: # 手势存储时间
xl = np.vstack((xl, knucks))
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
else: # 开始手势识别
self.detector.fingers = xl
value = ''
for j in range(13):
value = value + str(np.argmax(
np.bincount(xl[:, j].astype(int)))) # 找出第3列最频繁出现的值
gesture_store[value] = stored_round
stored_flag = 1
# startTime = time.time()
gesture_dete = ''.join(str(knuck) for knuck in knucks)
if gesture_dete in gesture_store:
cv2.putText(img, str(gesture_store[gesture_dete]), (x_1, y_1), cv2.FONT_HERSHEY_PLAIN, 3,
(0, 0, 255), 3)
cv2.putText(img, 'Gesture stored, recognition started', (50, 50),
cv2.FONT_HERSHEY_PLAIN, 1.2, (255, 255, 255), 2)
else:
if stored_flag:
stored_round += 1
stored_flag = 0
startTime = time.time() # 当检测不到手势时，初始化手势存储
xl = np.zeros((1, 13)) # 特征值存储
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)