Hello大家好，最近竞赛需要开始研究OpenMV4，今天和大家分享一段基于色块识别的图形+颜色+坐标识别代码，实测准确率高于90%哦，当然，需要在光线和距离都合适的情况下使用（假如你的识别结果不尽如人意，可以自行调节颜色阈值和目标与摄像头的距离），下面，话不多说，上代码！（需要搭配OpenMV IDE使用）
# Untitled - By: zzy - 周五 11月 25 2022import sensor, image, timefrom pyb import UARTimport jsonoutput_str_green="[0,0]"output_str_red="[0,0]"output_str_blue="[0,0]"output_str_brown="[0,0]"output_str_yellow="[0,0]"#green_threshold = ( 0, 80, -70, -10, -0, 30)green_threshold = ( 3, 39, -29, 2, 1, 25)red_threshold = ( 28, 40, 51, 65, 22, 50)orange_threshold = ( 23, 39, 19, 42, 13, 31)blue_threshold = ( 50, 56, -14, 1, -31, -13)brown_threshold = ( 22, 30, 1, 17, 8, 25)yellow_threshold = ( 53, 58, -7, 3, 58, 63)sensor.reset()sensor.set_pixformat(sensor.RGB565)sensor.set_framesize(sensor.QVGA)sensor.set_windowing((0,20,320,200))#QVGA find Region Of Interest#sensor.set_windowing((5,10,160,95))#QQVGA find Region Of Interestsensor.skip_frames(10)sensor.set_auto_whitebal(False)clock = time.clock()uart = UART(3, 115200)def find_max(blobs): max_size=0 for blob in blobs: if blob.pixels() > max_size: max_blob=blob max_size = blob.pixels() return max_blobdef detect(max_blob):#输入的是寻找到色块中的最大色块 #print(max_blob.solidity()) shape=0 if max_blob.solidity()>0.90 or max_blob.density()>0.84: img.draw_rectangle(max_blob.rect(),color=(255,255,255)) shape=1 elif max_blob.density()>0.6: img.draw_circle((max_blob.cx(), max_blob.cy(),int((max_blob.w()+max_blob.h())/4))) shape=2 elif max_blob.density()>0.4: img.draw_rectangle(max_blob.rect(),color=(0,0,0)) shape=3 return shapewhile(True): #clock.tick() img = sensor.snapshot() # Take a picture and return the image. blobs_green = img.find_blobs([green_threshold]) blobs_red = img.find_blobs([red_threshold]) #blobs_orange = img.find_blobs([orange_threshold]) blobs_blue = img.find_blobs([blue_threshold]) blobs_brown = img.find_blobs([brown_threshold]) blobs_yellow = img.find_blobs([yellow_threshold]) if blobs_green: max_blob_green=find_max(blobs_green) shape_green=detect(max_blob_green) #img.draw_rectangle(max_blob_green.rect(),color=(0,255,0))#画框 img.draw_cross(max_blob_green.cx(), max_blob_green.cy(),color=(0,255,0))#画十字准星 output_str_green="[%d,%d,%d]" % (max_blob_green.cx(),max_blob_green.cy(),shape_green) #方式1 print('green:',output_str_green) else: print('not found green!') if blobs_red: max_blob_red=find_max(blobs_red) shape_red=detect(max_blob_red) #img.draw_rectangle(max_blob_red.rect(),color=(255,0,0)) img.draw_cross(max_blob_red.cx(), max_blob_red.cy(),color=(255,0,0)) output_str_red="[%d,%d,%d]" % (max_blob_red.cx(),max_blob_red.cy(),shape_red) #方式1 print('red:',output_str_red) else: print('not found red !') #if blobs_orange: #max_blob_orange=find_max(blobs_orange) #detect(max_blob_orange) ##img.draw_rectangle(max_blob_orange.rect(),color=(255,128,0)) #img.draw_cross(max_blob_orange.cx(), max_blob_orange.cy(),color=(255,128,0)) #output_str_orange="[%d,%d]" % (max_blob_orange.cx(),max_blob_orange.cy()) #方式1 #print('orange:',output_str_orange) #uart.write(output_str_orange+'\r\n') #else: #print('not found orange !') if blobs_blue: max_blob_blue=find_max(blobs_blue) shape_blue=detect(max_blob_blue) #img.draw_rectangle(max_blob_blue.rect(),color=(0,0,255)) img.draw_cross(max_blob_blue.cx(), max_blob_blue.cy(),color=(0,0,255)) output_str_blue="[%d,%d,%d]" % (max_blob_blue.cx(),max_blob_blue.cy(),shape_blue) #方式1 print('blue:',output_str_blue) else: print('not found blue !') if blobs_brown: max_blob_brown=find_max(blobs_brown) shape_brown=detect(max_blob_brown) #img.draw_rectangle(max_blob_brown.rect(),color=(205,133,63)) img.draw_cross(max_blob_brown.cx(), max_blob_brown.cy(),color=(205,133,63)) output_str_brown="[%d,%d,%d]" % (max_blob_brown.cx(),max_blob_brown.cy(),shape_brown) #方式1 print('brown:',output_str_brown) else: print('not found brown !') if blobs_yellow: max_blob_yellow=find_max(blobs_yellow) shape_yellow=detect(max_blob_yellow) #img.draw_rectangle(max_blob_yellow.rect(),color=(255,255,0)) img.draw_cross(max_blob_yellow.cx(), max_blob_yellow.cy(),color=(255,255,0)) output_str_yellow="[%d,%d,%d]" % (max_blob_yellow.cx(),max_blob_yellow.cy(),shape_yellow) #方式1 print('yellow:',output_str_yellow) else: print('not found yellow !') uart.write(output_str_green + output_str_red + output_str_blue + output_str_brown + output_str_yellow + '\r\n') #print(clock.fps())再来看看程序的运行结果吧 ，在识别出多个图形，颜色及坐标之后，性能仍然不赖
解除部分注释之后可以查看帧数以调整性能，开发者还可以根据自己的需求增加被检测颜色与图形，再将其通过串口发送到目标单片机上哦，假如之后有时间，我再出一份解释代码含义的文章，嘻嘻，就看大家的需求和小编的时间啦。来源地址：https://blog.csdn.net/qq_63910028/article/details/128072010
