opencv入门——检测图片中的简单形状

效果图

代码：

# #day03
# 
# #将多张不同大小、通道的图片展示在同一窗口
# # 定义函数，第一个参数是缩放比例，第二个参数是需要显示的图片组成的元组或者列表
# def ManyImgs(scale, imgarray):
#     rows = len(imgarray)         # 元组或者列表的长度
#     cols = len(imgarray[0])      # 如果imgarray是列表，返回列表里第一幅图像的通道数，如果是元组，返回元组里包含的第一个列表的长度
#     # print("rows=", rows, "cols=", cols)
# 
#     # 判断imgarray[0]的类型是否是list
#     # 是list，表明imgarray是一个元组，需要垂直显示
#     rowsAvailable = isinstance(imgarray[0], list)
# 
#     # 第一张图片的宽高
#     width = imgarray[0][0].shape[1]
#     height = imgarray[0][0].shape[0]
#     # print("width=", width, "height=", height)
# 
#     # 如果传入的是一个元组
#     if rowsAvailable:
#         for x in range(0, rows):
#             for y in range(0, cols):
#                 # 遍历元组，如果是第一幅图像，不做变换
#                 if imgarray[x][y].shape[:2] == imgarray[0][0].shape[:2]:
#                     imgarray[x][y] = cv2.resize(imgarray[x][y], (0, 0), None, scale, scale)
#                 # 将其他矩阵变换为与第一幅图像相同大小，缩放比例为scale
#                 else:
#                     imgarray[x][y] = cv2.resize(imgarray[x][y], (imgarray[0][0].shape[1], imgarray[0][0].shape[0]), None, scale, scale)
#                 # 如果图像是灰度图，将其转换成彩色显示
#                 if  len(imgarray[x][y].shape) == 2:
#                     imgarray[x][y] = cv2.cvtColor(imgarray[x][y], cv2.COLOR_GRAY2BGR)
# 
#         # 创建一个空白画布，与第一张图片大小相同
#         imgBlank = np.zeros((height, width, 3), np.uint8)
#         hor = [imgBlank] * rows   # 与第一张图片大小相同，与元组包含列表数相同的水平空白图像
#         for x in range(0, rows):
#             # 将元组里第x个列表水平排列
#             hor[x] = np.hstack(imgarray[x])
#         ver = np.vstack(hor)   # 将不同列表垂直拼接
#     # 如果传入的是一个列表
#     else:
#         # 变换操作，与前面相同
#         for x in range(0, rows):
#             if imgarray[x].shape[:2] == imgarray[0].shape[:2]:
#                 imgarray[x] = cv2.resize(imgarray[x], (0, 0), None, scale, scale)
#             else:
#                 imgarray[x] = cv2.resize(imgarray[x], (imgarray[0].shape[1], imgarray[0].shape[0]), None, scale, scale)
#             if len(imgarray[x].shape) == 2:
#                 imgarray[x] = cv2.cvtColor(imgarray[x], cv2.COLOR_GRAY2BGR)
#         # 将列表水平排列
#         hor = np.hstack(imgarray)
#         ver = hor
#     return ver
# 
# #绘制轮廓
# def getContours(img):
#     coutours,hierarchy=cv2.findContours(img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
#     for cnt in coutours:
#         area=cv2.contourArea(cnt)
#         if area>100:
#             cv2.drawContours(imgcontours, cnt, -1, (0, 0, 255), 5)
#             #周长
#             peri=cv2.arcLength(cnt,True)
#             print(peri)
#             #拟合轮廓点集
#             approx=cv2.approxPolyDP(cnt,0.03*peri,True)
#             print((approx))
#             objcor=len(approx)
# 
#             x,y,w,h=cv2.boundingRect(approx)
#             cv2.rectangle(imgcontours,(x,y),(x+w,y+h),(255,0,0),5)
#             if objcor==3:
#                 # imgr=paint_chinese_opencv(imgcontours,"三角形",(x+(w//2)-10,y+(h//2)-10),(255,255,255))
#                 cv2.putText(imgcontours,"SanJiaoXing",(x+(w//2)-10,y+(h//2)-10),cv2.FONT_HERSHEY_COMPLEX,1,(0,0,0),2)
#             elif objcor==4:cv2.putText(imgcontours,"ZhengFangXing",(x+(w//2)-10,y+(h//2)-10),cv2.FONT_HERSHEY_COMPLEX,1,(0,0,0),2)
#             else:cv2.putText(imgcontours,str(objcor)+"YuanXing",(x+(w//2)-10,y+(h//2)-10),cv2.FONT_HERSHEY_COMPLEX,1,(0,0,0),2)
# 
# 
# img1=cv2.imread("C:/Users/31132/Desktop/xingz.jpg")
# imgcontours=img1.copy()
# imggry=cv2.cvtColor(img1,cv2.COLOR_BGR2GRAY)
# imgblur=cv2.GaussianBlur(imggry,(3,3),2)
# imgcanny=cv2.Canny(imgblur,30,30)
# 
# getContours(imgcanny)
# imgblank=np.zeros_like(img1)
# imgs=ManyImgs(0.3,([img1,imggry,imgblur],[imgcanny,imgcontours,imgblank]))
# 
# cv2.imshow("1",imgs)
# 
# imgsres=ManyImgs(0.6,[img1,imgcontours])
# cv2.imshow("res",imgsres
#            )
# cv2.waitKey(0)