Welcome to JetCobot repository
10.Gesture recognition
Gesture recognition
1.Introduction
MediaPipe is a data stream processing machine learning application development framework developed and open-source by Google. It is a graph based data processing pipeline used to build and utilize various forms of data sources, such as video, audio, sensor data, and any time series data.
MediaPipe is cross platform and can run on embedded platforms (such as Raspberry Pi), mobile devices (iOS and Android), workstations, and servers, with support for mobile GPU acceleration. MediaPipe provides cross platform, customizable ML solutions for real-time and streaming media.
The core framework of MediaPipe is implemented in C++and provides support for languages such as Java and Objective C. The main concepts of MediaPipe include packets, streams, calculators, graphs, and subgraphs.
Features of MediaPipe:
-End to end acceleration: Built in fast ML inference and processing can accelerate even on regular hardware. -Build once, deploy anytime, anywhere: A unified solution suitable for Android, iOS, desktop/cloud, web, and IoT. -Ready to use solution: a cutting-edge ML solution that showcases all the functionalities of the framework. -Free and open-source: frameworks and solutions under Apache 2.0, fully extensible and customizable.
2. Gesture recognition
The hand gesture recognition designed based on the right hand can accurately recognize when specific conditions are met. The recognizable gestures include: Zero, One, Two, Three, Four, Five, Six, Seven, Eight, Ok, Rock, Thumb_up (like), Thumbd_down (thumb down), Heart_stngle (one handed heart comparison), a total of 14 categories.
2.1 Start
Input following command to start the program
xxxxxxxxxxrosrun jetcobot_mediapipe 10_GestureRecognition.py
2.2 About code
Code path：~/jetcobot_ws/src/jetcobot_mediapipe/scripts/10_GestureRecognition.py
x#!/usr/bin/env python3# encoding: utf-8import mathimport timeimport cv2 as cvimport numpy as npimport mediapipe as mp
class handDetector: def __init__(self, mode=False, maxHands=2, detectorCon=0.5, trackCon=0.5): self.tipIds = [4, 8, 12, 16, 20] self.mpHand = mp.solutions.hands self.mpDraw = mp.solutions.drawing_utils self.hands = self.mpHand.Hands( static_image_mode=mode, max_num_hands=maxHands, min_detection_confidence=detectorCon, min_tracking_confidence=trackCon ) self.lmList = [] self.lmDrawSpec = mp.solutions.drawing_utils.DrawingSpec(color=(0, 0, 255), thickness=-1, circle_radius=6) self.drawSpec = mp.solutions.drawing_utils.DrawingSpec(color=(0, 255, 0), thickness=2, circle_radius=2)
def get_dist(self, point1, point2): x1, y1 = point1 x2, y2 = point2 return abs(math.sqrt(math.pow(abs(y1 - y2), 2) + math.pow(abs(x1 - x2), 2)))
def calc_angle(self, pt1, pt2, pt3): point1 = self.lmList[pt1][1], self.lmList[pt1][2] point2 = self.lmList[pt2][1], self.lmList[pt2][2] point3 = self.lmList[pt3][1], self.lmList[pt3][2] a = self.get_dist(point1, point2) b = self.get_dist(point2, point3) c = self.get_dist(point1, point3) try: radian = math.acos((math.pow(a, 2) + math.pow(b, 2) - math.pow(c, 2)) / (2 * a * b)) angle = radian / math.pi * 180 except: angle = 0 return abs(angle)
def findHands(self, frame, draw=True): self.lmList = [] img = np.zeros(frame.shape, np.uint8) img_RGB = cv.cvtColor(frame, cv.COLOR_BGR2RGB) self.results = self.hands.process(img_RGB) if self.results.multi_hand_landmarks: for i in range(len(self.results.multi_hand_landmarks)): if draw: self.mpDraw.draw_landmarks(frame, self.results.multi_hand_landmarks[i], self.mpHand.HAND_CONNECTIONS, self.lmDrawSpec, self.drawSpec) self.mpDraw.draw_landmarks(img, self.results.multi_hand_landmarks[i], self.mpHand.HAND_CONNECTIONS, self.lmDrawSpec, self.drawSpec) for id, lm in enumerate(self.results.multi_hand_landmarks[i].landmark): h, w, c = frame.shape cx, cy = int(lm.x * w), int(lm.y * h) self.lmList.append([id, cx, cy]) return frame, img
def frame_combine(slef,frame, src): if len(frame.shape) == 3: frameH, frameW = frame.shape[:2] srcH, srcW = src.shape[:2] dst = np.zeros((max(frameH, srcH), frameW + srcW, 3), np.uint8) dst[:, :frameW] = frame[:, :] dst[:, frameW:] = src[:, :] else: src = cv.cvtColor(src, cv.COLOR_BGR2GRAY) frameH, frameW = frame.shape[:2] imgH, imgW = src.shape[:2] dst = np.zeros((frameH, frameW + imgW), np.uint8) dst[:, :frameW] = frame[:, :] dst[:, frameW:] = src[:, :] return dst
def fingersUp(self): fingers=[] # Thumb if (self.calc_angle(self.tipIds[0], self.tipIds[0] - 1, self.tipIds[0] - 2) > 150.0) and ( self.calc_angle( self.tipIds[0] - 1, self.tipIds[0] - 2, self.tipIds[0] - 3) > 150.0): fingers.append(1) else: fingers.append(0) # 4 finger for id in range(1, 5): if self.lmList[self.tipIds[id]][2] < self.lmList[self.tipIds[id] - 2][2]: fingers.append(1) else: fingers.append(0) return fingers
def get_gesture(self): gesture = "" fingers = self.fingersUp() if self.lmList[self.tipIds[0]][2] > self.lmList[self.tipIds[1]][2] and \ self.lmList[self.tipIds[0]][2] > self.lmList[self.tipIds[2]][2] and \ self.lmList[self.tipIds[0]][2] > self.lmList[self.tipIds[3]][2] and \ self.lmList[self.tipIds[0]][2] > self.lmList[self.tipIds[4]][2] : gesture = "Thumb_down"
elif self.lmList[self.tipIds[0]][2] < self.lmList[self.tipIds[1]][2] and \ self.lmList[self.tipIds[0]][2] < self.lmList[self.tipIds[2]][2] and \ self.lmList[self.tipIds[0]][2] < self.lmList[self.tipIds[3]][2] and \ self.lmList[self.tipIds[0]][2] < self.lmList[self.tipIds[4]][2] and \ self.calc_angle(self.tipIds[1] - 1, self.tipIds[1] - 2, self.tipIds[1] - 3) < 150.0 : gesture = "Thumb_up" if fingers.count(1) == 3 or fingers.count(1) == 4: if fingers[0] == 1 and ( self.get_dist(self.lmList[4][1:], self.lmList[8][1:])<self.get_dist(self.lmList[4][1:], self.lmList[5][1:]) ): gesture = "OK" elif fingers[2] == fingers[3] == 0: gesture = "Rock" elif fingers.count(1) == 3: gesture = "Three" else: gesture = "Four" elif fingers.count(1) == 0: gesture = "Zero" elif fingers.count(1) == 1: gesture = "One" elif fingers.count(1) == 2: if fingers[0] == 1 and fingers[4] == 1: gesture = "Six" elif fingers[0] == 1 and self.calc_angle(4, 5, 8) > 90: gesture = "Eight" elif fingers[0] == fingers[1] == 1 and self.get_dist(self.lmList[4][1:], self.lmList[8][1:]) < 50: gesture = "Heart_single" else: gesture = "Two" elif fingers.count(1)==5:gesture = "Five" if self.get_dist(self.lmList[4][1:], self.lmList[8][1:]) < 60 and \ self.get_dist(self.lmList[4][1:], self.lmList[12][1:]) < 60 and \ self.get_dist(self.lmList[4][1:], self.lmList[16][1:]) < 60 and \ self.get_dist(self.lmList[4][1:], self.lmList[20][1:]) < 60 : gesture = "Seven" if self.lmList[self.tipIds[0]][2] < self.lmList[self.tipIds[1]][2] and \ self.lmList[self.tipIds[0]][2] < self.lmList[self.tipIds[2]][2] and \ self.lmList[self.tipIds[0]][2] < self.lmList[self.tipIds[3]][2] and \ self.lmList[self.tipIds[0]][2] < self.lmList[self.tipIds[4]][2] and \ self.calc_angle(self.tipIds[1] - 1, self.tipIds[1] - 2, self.tipIds[1] - 3) > 150.0 : gesture = "Eight" return gesture
'''Zero One Two Three Four Five Six Seven EightOk: OKRock: rockThumb_up : 点赞Thumb_down: 拇指向下Heart_single: 单手比心'''
if __name__ == '__main__': capture = cv.VideoCapture(0) capture.set(6, cv.VideoWriter.fourcc('M', 'J', 'P', 'G')) capture.set(cv.CAP_PROP_FRAME_WIDTH, 640) capture.set(cv.CAP_PROP_FRAME_HEIGHT, 480) print("capture get FPS : ", capture.get(cv.CAP_PROP_FPS)) pTime = cTime = 0 hand_detector = handDetector(detectorCon=0.75) while capture.isOpened(): ret, frame = capture.read() # frame = cv.flip(frame, 1) frame, img = hand_detector.findHands(frame, draw=False) if len(hand_detector.lmList) != 0: totalFingers = hand_detector.get_gesture() cv.rectangle(frame, (0, 430), (230, 480), (0, 255, 0), cv.FILLED) cv.putText(frame, str(totalFingers), (10, 470), cv.FONT_HERSHEY_PLAIN, 2, (255, 0, 0), 2) if cv.waitKey(1) & 0xFF == ord('q'): break cTime = time.time() fps = 1 / (cTime - pTime) pTime = cTime text = "FPS : " + str(int(fps)) cv.putText(frame, text, (10, 30), cv.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 255), 1) dist = hand_detector.frame_combine(frame, img) cv.imshow('dist', dist) # cv.imshow('frame', frame) # cv.imshow('img', img) capture.release() cv.destroyAllWindows()