From e2e37af9c04b3c44d47dfa459f3ecd0d2f2d23c0 Mon Sep 17 00:00:00 2001 From: leaf <48828021+leafliber@users.noreply.github.com> Date: Thu, 30 Jun 2022 21:11:21 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=A0=E9=99=A4demo?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- demo.py | 194 -------------------------------------------------------- 1 file changed, 194 deletions(-) delete mode 100644 demo.py diff --git a/demo.py b/demo.py deleted file mode 100644 index 0ac1a8e..0000000 --- a/demo.py +++ /dev/null @@ -1,194 +0,0 @@ -# -*- coding:utf-8 -*- - -""" -信号设计课程小组设计 - -@ by: Leaf -@ date: 2022-05-28 -""" - -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, max_hands=2, detection_con=0.5, min_track_con=0.5): - """ - :param mode: 在静态模式下，对每个图像进行检测 - :param max_hands: 要检测的最大手数 - :param detection_con: 最小检测置信度 - :param min_track_con: 最小跟踪置信度 - """ - self.results = None - self.mode = mode - self.max_hands = max_hands - self.modelComplex = 1 - self.detection_con = detection_con - self.min_track_con = min_track_con - - # 初始化手部的识别模型 - self.mpHands = mp.solutions.hands - self.hands = self.mpHands.Hands(static_image_mode=self.mode, - max_num_hands=self.max_hands, - min_detection_confidence=self.detection_con, - min_tracking_confidence=self.min_track_con) - 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 find_hands(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 - """ - img_rgb = 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(img_rgb) - - 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 find_position(self, img, hand_no=0, draw=True): - """ - 查找单手的地标并将其放入列表中像素格式。还可以返回手部的周围的边界框。 - :param img: 要查找的主图像 - :param hand_no: 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 - """ - - x_list = [] - y_list = [] - bbox_info = [] - self.lmList = [] - if self.results.multi_hand_landmarks: - my_hand = self.results.multi_hand_landmarks[hand_no] - for _, lm in enumerate(my_hand.landmark): - h, w, c = img.shape - px, py = int(lm.x * w), int(lm.y * h) - x_list.append(px) - y_list.append(py) - self.lmList.append([px, py]) - if draw: - cv2.circle(img, (px, py), 5, (255, 0, 255), cv2.FILLED) - x_min, x_max = min(x_list), max(x_list) - y_min, y_max = min(y_list), max(y_list) - box_w, box_h = x_max - x_min, y_max - y_min - bbox = x_min, y_min, box_w, box_h - cx, cy = bbox[0] + (bbox[2] // 2), bbox[1] + (bbox[3] // 2) - bbox_info = {"id": hand_no, "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, bbox_info - - def fingers_up(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 - """ - fingers = [] - if self.results.multi_hand_landmarks: - my_hand_type = self.hand_type() - # Thumb - if my_hand_type == "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 i in range(1, 5): - if self.lmList[self.tipIds[i]][1] < self.lmList[self.tipIds[i] - 2][1]: - fingers.append(1) - else: - fingers.append(0) - return fingers - - def hand_type(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.detector = None - self.camera = cv2.VideoCapture(0, cv2.CAP_DSHOW) - self.camera.set(3, 1280) - self.camera.set(4, 720) - - def gesture_recognition(self): - self.detector = HandDetector() - while True: - frame, img = self.camera.read() - img = self.detector.find_hands(img) - lm_list, bbox = self.detector.find_position(img) - - if lm_list: - x_1, y_1 = bbox["bbox"][0], bbox["bbox"][1] - x1, x2, x3, x4, x5 = self.detector.fingers_up() - - 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 x3 and x1 == 0 and x2 == 0 and (x4 == 0, x5 == 0): - cv2.putText(img, "FUCK YOU!!", (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()