可以在边缘检测程序之后再加识别矩形程序吗 加了以后报错
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![替代文字]( 图片地址)
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需要发代码,不然没法知道问题
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# 边缘检测例子: # # 这个程序示范了在图像上使用morph函数来进行边缘检测。 # 然后在进行阈值和滤波 import sensor, image, time #设置核函数滤波,核内每个数值值域为[-128,127],核需为列表或元组 kernel_size = 1 # kernel width = (size*2)+1, kernel height = (size*2)+1 kernel = [-1, -1, -1,\ -1, +8, -1,\ -1, -1, -1] # 这个一个高通滤波器。见这里有更多的kernel # http://www.fmwconcepts.com/imagemagick/digital_image_filtering.pdf thresholds = [(100, 255)] # grayscale thresholds设置阈值 sensor.reset() # 初始化 sensor. sensor.set_pixformat(sensor.GRAYSCALE) # or sensor.RGB565 sensor.set_framesize(sensor.QQVGA) # or sensor.QVGA (or others) sensor.skip_frames(10) # 让新的设置生效 clock = time.clock() # 追踪FPS # 在OV7725 sensor上, 边缘检测可以通过设置sharpness/edge寄存器来增强。 # 注意:这个会edge detection can be enhanced # significantly by setting the sharpness/edge registers. # Note: This will be implemented as a function later. if (sensor.get_id() == sensor.OV7725): sensor.__write_reg(0xAC, 0xDF) sensor.__write_reg(0x8F, 0xFF) while(True): clock.tick() # Track elapsed milliseconds between snapshots(). img = sensor.snapshot() # Take a picture and return the image. img.morph(kernel_size, kernel) #morph(size, kernel, mul=Auto, add=0),morph变换,mul根据图像对比度 #进行调整,mul使图像每个像素乘mul;add根据明暗度调整,使得每个像素值加上add值。 #如果不设置则不对morph变换后的图像进行处理。 img.binary(thresholds) #利用binary函数对图像进行分割 # Erode pixels with less than 2 neighbors using a 3x3 image kernel img.erode(1, threshold = 2) #侵蚀函数erode(size, threshold=Auto),去除边缘相邻处多余的点。threshold #用来设置去除相邻点的个数,threshold数值越大,被侵蚀掉的边缘点越多,边缘旁边 #白色杂点少;数值越小,被侵蚀掉的边缘点越少,边缘旁边的白色杂点越多。 print(clock.fps()) # Note: Your OpenMV Cam runs about half as fast while # connected to your computer. The FPS should increase once disconnected. for r in img.find_rects(threshold = 10000): img.draw_rectangle(r.rect(), color = (255, 0, 0)) for p in r.corners(): img.draw_circle(p[0], p[1], 5, color = (0, 255, 0)) print(r) print("FPS %f" % clock.fps())
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@18561538293 我测试了你的代码,可以正常运行,没有出现你说的错误。
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你是OpenMV3嘛?
OpenMV2的话,用不了矩形识别。
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@yuan 是啊 我直接在边缘检测历程后面粘贴了识别矩形 运行不了啊
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你这个代码我可以运行啊,没有问题