thresholded)# 在第300帧后保存手部图像else:hand=segment_hand(gray_frame)ifhandisnotNone:thresholded,hand_segment=hand# 在手部轮廓周围画出轮廓线cv2.drawContours(frame_copy,[hand_segment+(ROI_right,ROI
class HandGestureRecognition: def __init__(self): # maximum depth deviation for a pixel to be considered # within range self.abs_depth_dev = 14 # cut-off angle (deg): everything below this is a convexity # point that belongs to two extended fingers self.thresh_deg = 80.0 recognize方...
pipinstallopencv-python mediapipe 1. 下面是一个简单的手势识别示例,利用MediaPipe获取手势的关键点,并使用OpenCV进行实时显示。 AI检测代码解析 importcv2importmediapipeasmp# 初始化MediaPipe Handsmp_hands=mp.solutions.hands hands=mp_hands.Hands(static_image_mode=False,max_num_hands=2,min_detection_confidence...
pip install opencv-python mediapipe numpy 然后,在你的Python脚本中导入这些库: python import cv2 import mediapipe as mp import numpy as np 4. 编写代码以捕获视频流,并使用所选工具进行手势识别 以下是一个使用MediaPipe实现简单手势识别的Python代码示例: python # 初始化MediaPipe手势识别模块 mp_hands =...
首先,你需要确保你的Python环境已经准备好。我们将使用OpenCV和mediapipe库来实现手势识别。 pipinstallopencv-python mediapipe 1. 这些库将提供视频处理和手势识别所需的功能。 2. 获取视频流 接下来,我们需要从摄像头获取视频流,以便捕捉手势。 importcv2# 初始化视频捕捉cap=cv2.VideoCapture(0)whileTrue:# 捕捉帧...
其次,NumPy 数组(Python 中 OpenCV 图像的基本格式)已针对数组计算进行了优化,因此分别访问和修改每个image[c,r]像素将非常慢。相反,我们应该认识到<<8操作与将像素值乘以2 ^ 8 = 256相同,并且可以通过cv2.divide函数实现按像素划分。 因此,我们的淡化函数的改进版本可能如下所示:...
实现代码前首先进行依赖安装,这里需要安装python-opencv和MediaPipe,可使用以下命令: powershell pip install opencv-python pip install mediapipe 首先是引入库文件,这里主要用到的是一个mediapipe的sdk包和opencv的包。其他的numpy、time、math都是python和深度学习的基础包,不多介绍。 python import mediapipe as mp ...
Hand gesture recognition has usage in various applications like medicine, accessibility support etc. In this paper, we would like to propose on how to develop a hand gesture recognition simulation using OpenCV and python 2.7. Histogram based approach is used to separate out the hand from the ...
#pip install opencv-python #3.2 安装mediapipe #pip install mediapipe #3.3 安装tf #pip install tensorflow #3.4 下载预训练好的文件 #https://techvidvan.s3.amazonaws.com/machine-learning-projects/hand-gesture-recognition-code.zip #接下来就是开始编码了 ...
hand_mask_in_frame[hand_y:hand_y+hand_h,hand_x:hand_x+hand_w]=hand_mask thresh_deg=80.0 # Convexity hull based gesture recognition. contours=None ifself.opencv_ver=='3': contours_image,contours,contours_hierarchy=cv2.findContours(