基于树莓派python实现数字识别几何图形识别颜色二维码识别源码.zip

import cv2 as cv import numpy as np import math """ 功能：实现多种几何图形的形状及颜色的识别，并计算面积及周长 可以识别的图形：三角形，任意四边形（梯形，平行四边形，菱形，正方形，矩形，不特殊四边形）， 五边形，五角星，六边形，多边形，椭圆，半圆，圆 可以识别的颜色：红色，绿色，蓝色，黄色，黑色，紫色，橙色，白色 除了定义的可识别颜色外，其他返回其对应的rgb值，提示用户根据rgb值去找寻相应颜色 除了定义的可识别图形外，其他为未定义的图形 """ noise_b = 0.5 class ShapeAnalysis: def __init__(self): self.shapes = {'triangle': 0, 'quadrilateral': 0, 'trapezium': 0, 'parallelogram': 0, 'rectangle': 0, 'rhombus': 0, 'square': 0, 'pentagon': 0, 'pentagram': 0, 'hexagon': 0, 'polygons': 0, 'ellipse': 0, 'circle': 0, 'undefined': 0 } self.colors = {'white': 0, 'black': 0, 'red': 0, 'green': 0, 'blue': 0, 'yellow': 0, 'orange': 0, 'purple': 0, 'others': 0 } def analysis(self, frame): self.re_strover = '识别结果：\n' h, w, ch = frame.shape # 获取图形信息 result = np.zeros((h, w, ch), dtype=np.uint8) # 生成跟图形相同大小的矩阵 # cv.imshow("input image", frame) # 二值化图像 print('start to binary image and detect edges...\n') gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY) # threshold：固定阈值二值化 ret, dst输出图 = cv2.threshold(src输入图, thresh阈值, maxval, type) # type：二值化操作的类型，包含以下5种类型： cv2.THRESH_BINARY； # cv2.THRESH_BINARY_INV； cv2.THRESH_TRUNC； cv2.THRESH_TOZERO；cv2.THRESH_TOZERO_INV # adaptiveThreshold自适应阈值二值化 ret, binary = cv.threshold(gray, 5, 255, cv.THRESH_BINARY_INV) # cv.imshow("bin",binary) # cv.waitKey(0) kernel = np.ones((3, 3), dtype=np.uint8) binary = cv.dilate(binary, kernel, 1) # cv.imshow("bin1", binary) # cv.waitKey(0) # 函数cv2.findContours()有三个参数。第一个是输入图像，第二个是轮廓检索模式，第三个是轮廓近似方法。 # 轮廓的点集(contours)[Next, Previous, First_Child, Parent] # 各层轮廓的索引(hierarchy) img,contours, hierarchy = cv.findContours(binary, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE) if len(contours) < 1e-6: print('there is nothing can be detected! Please check the input image. Thanks！') else: shape_numbers = 0 for cnt in range(len(contours)): # 通过计算周长和面积来排除一些图像干扰 # 计算面积与周长 p = cv.arcLength(contours[cnt], True) area = cv.contourArea(contours[cnt]) if area < h*w*0.003: continue if area > noise_b and p > noise_b: # 如果面积和周长小于0.5判断为噪声干扰，不是图形 shape_numbers += 1 # 统计检测到图形 # 为图形，做统计分析 cv.drawContours(result, contours, cnt, (0, 255, 0), 2) # 画出轮廓 # 求解中心位置 mm = cv.moments(contours[cnt]) cx = int(mm['m10'] / (mm['m00'] + 1e-12)) cy = int(mm['m01'] / (mm['m00'] + 1e-12)) cv.circle(result, (cx, cy), 3, (0, 0, 255), -1) # if cx < w*0.2 or cx >w*0.8 or cy < h*0.2 or cy >h*0.8: # continue # 获取颜色信息 color = frame[cy][cx] color_str = "(" + str(color[0]) + ", " + str(color[1]) + ", " + str(color[2]) + ")" global color_type color_type = "" # 颜色匹配分析 if (color[0], color[1], color[2]) == (255, 255, 255): count = self.colors['white'] count = count + 1 self.colors['white'] = count color_type = '白色' cv.putText(result, "white", (cx + 5, cy), cv.FONT_HERSHEY_PLAIN, 0.4, (255, 255, 255), 1) elif (color[0], color[1], color[2]) == (0, 0, 0): count = self.colors['black'] count = count + 1 self.colors['black'] = count color_type = '黑色' cv.putText(result, "black", (cx + 5, cy), cv.FONT_HERSHEY_PLAIN, 0.4, (255, 255, 255), 1) elif (color[0], color[1], color[2]) == (0, 0, 255): count = self.colors['red'] count = count + 1 self.colors['red'] = count color_type = '红色' cv.putText(result, "red", (cx + 5, cy), cv.FONT_HERSHEY_PLAIN, 0.4, (255, 255, 255), 1) elif (color[0], color[1], color[2]) == (0, 255, 0): count = self.colors['green'] count = count + 1 self.colors['green'] = count color_type = '绿色' cv.putText(result, "green", (cx + 5, cy), cv.FONT_HERSHEY_PLAIN, 0.4, (255, 255, 255), 1) elif (color[0], color[1], color[2]) == (255, 0, 0): count = self.colors['blue'] count = count + 1 self.colors['blue'] = count color_type = '蓝色' cv.putText(result,"blue", (cx + 5, cy), cv.FONT_HERSHEY_PLAIN, 0.4, (255, 255, 255), 1) elif (color[0], color[1], color[2]) == (0, 128, 255): count = self.colors['orange'] count = count + 1 self.colors['orange'] = count color_type = '橙色' cv.putText(result, "orange", (cx + 5, cy), cv.FONT_HERSHEY_PLAIN, 0.4, (255, 255, 255), 1) elif (color[0], color[1], color[2]) == (0, 255, 255): count = self.colors['yellow'] count = count + 1 self.colors['yellow'] = count color_type = '黄色' cv.putText(result, "yellow", (cx + 5, cy), cv.FONT_HERSHEY_PLAIN, 0.4, (255, 255, 255), 1) elif (color[0], color[1], color[2]) == (255, 0, 255): count = self.colors['purple'] count = count + 1 self.colors['purple'] = count color_type = '紫色' cv.putText(result, "purple", (cx + 5, cy), cv.FONT_HERSHEY_PLAIN, 0.4, (255, 255, 255), 1) else: count = self.colors['others'] count = count + 1 self.colors['others'] = count color_type