From 85fb3ad83c2e725ccd38a133eb559deea88b7b00 Mon Sep 17 00:00:00 2001 From: Tabs <54019007+Tabshhh@users.noreply.github.com> Date: Mon, 13 Jun 2022 17:23:55 +0800 Subject: [PATCH] =?UTF-8?q?=E5=AE=9E=E7=8E=B0=E4=BA=86=E6=AD=A3=E9=9D=A2?= =?UTF-8?q?=E6=89=8B=E5=8A=BF=E6=B5=8B=E8=AF=95=EF=BC=8C=E5=8F=AF=E6=B7=BB?= =?UTF-8?q?=E5=8A=A0=E6=96=B0=E6=89=8B=E5=8A=BF=E5=B9=B6=E5=8A=A0=E4=B8=8A?= =?UTF-8?q?=E6=A0=87=E7=AD=BE?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- demo.py | 61 ++++++++++++++++++++++++++++----------------------------- 1 file changed, 30 insertions(+), 31 deletions(-) diff --git a/demo.py b/demo.py index a23b831..4a48ab9 100644 --- a/demo.py +++ b/demo.py @@ -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)