Create origin.py

origin.py

@@ -0,0 +1,190 @@
+
+# -*- 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 = []
+        self.connection = [(1,0,5),(1,0,17),(5,0,17),(2,1,0),(3,2,1),(4,3,2),(0,5,6),(0,5,9),(6,5,9),(5,6,7),(6,7,8),(5,9,13),(5,9,10),(10,9,13),(9,10,11),(10,11,12),(9,13,14),(9,13,17),(14,13,17),(13,14,15),(14,15,16),(13,17,18),(0,17,13),(0,17,18),(17,18,19),(18,19,20)]
+
+    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):
+        while True:
+            self.detector = HandDetector()
+            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)
+            if cv2.getWindowProperty('camera', cv2.WND_PROP_VISIBLE) < 1:
+                break
+            cv2.waitKey(1)
+
+
+if __name__ == '__main__':
+    Solution = Main()
+    Solution.Gesture_recognition()