# -*- coding:utf-8 -*- """ CODE >>> SINCE IN CAIXYPROMISE. STRIVE FOR EXCELLENT. CONSTANTLY STRIVING FOR SELF-IMPROVEMENT. @ by: caixy @ date: 2021-10-1 """ import cv2 import mediapipe as mp class HandDetector: """ 使用mediapipe库查找手。导出地标像素格式。添加了额外的功能。 如查找方式，许多手指向上或两个手指之间的距离。而且提供找到的手的边界框信息。 """ def __init__(self, mode=False, maxHands=2, detectionCon=0.5, minTrackCon=0.5): """ :param mode: 在静态模式下，对每个图像进行检测 :param maxHands: 要检测的最大手数 :param detectionCon: 最小检测置信度 :param minTrackCon: 最小跟踪置信度 """ self.mode = mode self.maxHands = maxHands self.modelComplex = False self.detectionCon = detectionCon self.minTrackCon = minTrackCon # 初始化手部识别模型 self.mpHands = mp.solutions.hands self.hands = self.mpHands.Hands(self.mode, self.maxHands, self.modelComplex, self.detectionCon, self.minTrackCon) self.mpDraw = mp.solutions.drawing_utils # 初始化绘图器 self.tipIds = [4, 8, 12, 16, 20] # 指尖列表 self.fingers = [] self.lmList = [] def findHands(self, img, draw=True): """ 从图像(BRG)中找到手部。 :param img: 用于查找手的图像。 :param draw: 在图像上绘制输出的标志。 :return: 带或不带图形的图像 """ imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) # 将传入的图像由BGR模式转标准的Opencv模式——RGB模式， self.results = self.hands.process(imgRGB) if self.results.multi_hand_landmarks: for handLms in self.results.multi_hand_landmarks: if draw: self.mpDraw.draw_landmarks(img, handLms, self.mpHands.HAND_CONNECTIONS) return img def findPosition(self, img, handNo=0, draw=True): """ 查找单手的地标并将其放入列表中像素格式。还可以返回手部周围的边界框。 :param img: 要查找的主图像 :param handNo: 如果检测到多只手，则为手部id :param draw: 在图像上绘制输出的标志。(默认绘制矩形框) :return: 像素格式的手部关节位置列表；手部边界框 """ xList = [] yList = [] bbox = [] bboxInfo = [] self.lmList = [] if self.results.multi_hand_landmarks: myHand = self.results.multi_hand_landmarks[handNo] for id, lm in enumerate(myHand.landmark): h, w, c = img.shape px, py = int(lm.x * w), int(lm.y * h) xList.append(px) yList.append(py) self.lmList.append([px, py]) if draw: cv2.circle(img, (px, py), 5, (255, 0, 255), cv2.FILLED) xmin, xmax = min(xList), max(xList) ymin, ymax = min(yList), max(yList) boxW, boxH = xmax - xmin, ymax - ymin bbox = xmin, ymin, boxW, boxH cx, cy = bbox[0] + (bbox[2] // 2), \ bbox[1] + (bbox[3] // 2) bboxInfo = {"id": id, "bbox": bbox, "center": (cx, cy)} if draw: cv2.rectangle(img, (bbox[0] - 20, bbox[1] - 20), (bbox[0] + bbox[2] + 20, bbox[1] + bbox[3] + 20), (0, 255, 0), 2) return self.lmList, bboxInfo def fingersUp(self): """ 查找列表中打开并返回的手指数。会分别考虑左手和右手 ：return：竖起手指的列表 """ if self.results.multi_hand_landmarks: myHandType = self.handType() fingers = [] # Thumb if myHandType == "Right": if self.lmList[self.tipIds[0]][0] > self.lmList[self.tipIds[0] - 1][0]: fingers.append(1) else: fingers.append(0) else: if self.lmList[self.tipIds[0]][0] < self.lmList[self.tipIds[0] - 1][0]: fingers.append(1) else: fingers.append(0) # 4 Fingers for id in range(1, 5): if self.lmList[self.tipIds[id]][1] < self.lmList[self.tipIds[id] - 2][1]: fingers.append(1) else: fingers.append(0) return fingers def handType(self): """ 检查传入的手部是左还是右 ：return: "Right" 或 "Left" """ if self.results.multi_hand_landmarks: if self.lmList[17][0] < self.lmList[5][0]: return "Right" else: return "Left" class Main: def __init__(self): self.camera = cv2.VideoCapture(0, cv2.CAP_DSHOW) self.camera.set(3, 1280) self.camera.set(4, 720) def Gesture_recognition(self): fps = cv2.CAP_PROP_FPS self.detector = HandDetector() while True: frame, img = self.camera.read() img = self.detector.findHands(img) lmList, bbox = self.detector.findPosition(img) if lmList: x_1, y_1 = bbox["bbox"][0], bbox["bbox"][1] x1, x2, x3, x4, x5 = self.detector.fingersUp() 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) cv2.imshow("camera", img) key = cv2.waitKey(1) if cv2.getWindowProperty('camera', cv2.WND_PROP_VISIBLE) < 1: break elif key == 27: break if __name__ == '__main__': Solution = Main() Solution.Gesture_recognition()