我想要将颜色识别、形状识别、测距三种融合在一起可以实现吗?
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就是我想要同时识别到颜色和形状 然后串口终端返回与物块的距离
现在是识别不到物块 Lm的值也没有返回
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代码有问题,如果不只有一个色块,底下的就不会执行。
起码你要加一个find_max之类的。
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那我现在应该怎么修改呢?
import sensor, image, time sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQVGA) sensor.skip_frames(time = 2000) sensor.set_auto_gain(False) # must be turned off for color tracking sensor.set_auto_whitebal(False) # must be turned off for color tracking clock = time.clock() K=5000#the value should be measured yellow_threshold = (94, 100, -128, 127, -128, 127) while(True): clock.tick() img = sensor.snapshot().lens_corr(1.8) sensor.set_hmirror(True) #水平方向翻转 sensor.set_vflip(True) #垂直方向翻转 for c in img.find_circles(threshold = 3500, x_margin = 10, y_margin = 10, r_margin = 10, r_min = 2, r_max = 100, r_step = 2): area = (c.x()-c.r(), c.y()-c.r(), 2*c.r(), 2*c.r()) #area为识别到的圆的区域,即圆的外接矩形框 statistics = img.get_statistics(roi=area)#像素颜色统计 #print(statistics) #(94, 100, -128, 127, -128, 127)是红色的阈值,所以当区域内的众数(也就是最多的颜色),范围在这个阈值内,就说明是红色的圆。 #l_mode(),a_mode(),b_mode()是L通道,A通道,B通道的众数。 if 94<statistics.l_mode()<100 and -128<statistics.a_mode()<127 and -128<statistics.b_mode()<127:#if the circle is red img.draw_rectangle(area, color = (255, 255, 255)) #将非红色的圆用白色的矩形框出来 def find_max(blobs): #识别最大色块 max_size=0 for blob in blobs: if blob[2]*blob[3] > max_size: max_blob=blob max_size = blob[2]*blob[3] return max_blob blobs = img.find_blobs([yellow_threshold]) if len(blobs) == 1: # Draw a rect around the blob. b = blobs[0] img.draw_rectangle(b[0:4]) # rect img.draw_cross(b[5], b[6]) # cx, cy Lm = (b[2]+b[3])/2 length = K/Lm print(Lm)
这是我重新修改的 还是实现不了 麻烦您指教
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@4oqs 你这纯复制粘贴。。。。咋会有用呢,k的值没改,距离是不对的,而且输出的是像素,不是距离
另外这个是识别圆形区域的
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此回复已被删除!
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@egxs emmm……那想问问您 方形的识别该怎么写?能教一下我吗回复
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@kidswong999 想请教您 我现在该怎么去修改 或者是重新去写?
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此回复已被删除!
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import sensor, image, time sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQVGA) sensor.skip_frames(time = 2000) sensor.set_auto_gain(False) # must be turned off for color tracking sensor.set_auto_whitebal(False) # must be turned off for color tracking clock = time.clock() K=500#the value should be measured yellow_threshold = (56, 79, 35, 127, -128, 127) def find_max(blobs): #识别最大色块 max_size=0 for blob in blobs: if blob[2]*blob[3] > max_size: max_blob=blob max_size = blob[2]*blob[3] return max_blob while(True): clock.tick() img = sensor.snapshot().lens_corr(1.8) sensor.set_hmirror(False) #水平方向翻转 sensor.set_vflip(False) #垂直方向翻转 for r in img.find_rects(threshold = 20000): img.draw_rectangle(r.rect(), color = (255, 0, 0)) area = (r.x(),r.y(),r.w(),r.h()) for p in r.corners(): img.draw_circle(p[0], p[1], 5, color = (0, 255, 0)) # for c in img.find_circles(threshold = 3500, x_margin = 10, y_margin = 10, r_margin = 10, # r_min = 2, r_max = 100, r_step = 2): print (r) #area为识别到的圆的区域,即圆的外接矩形框 statistics = img.get_statistics(roi=area)#像素颜色统计 #print(statistics) #(94, 100, -128, 127, -128, 127)是红色的阈值,所以当区域内的众数(也就是最多的颜色),范围在这个阈值内,就说明是红色的圆。 #l_mode(),a_mode(),b_mode()是L通道,A通道,B通道的众数。 if 56<statistics.l_mode()<79 and 35<statistics.a_mode()<127 and -128<statistics.b_mode()<127:#if the circle is red img.draw_rectangle(area, color = (255, 255, 255)) #将非红色的圆用白色的矩形框出来 blobs = img.find_blobs([yellow_threshold]) if len(blobs) == 1: # Draw a rect around the blob. max_blob=find_max(blobs) b = blobs[0] img.draw_rectangle(b[0:4]) # rect img.draw_cross(b[5], b[6]) # cx, cy Lm = (b[2]+b[3])/2 length = K/Lm #print(Lm) print(length)
你试试看,我这里用的是红色的阈值
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@egxs 感谢您!
但是识别起来还是有点飘 会框到其他的地方
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你好,我想问你的这个问题解决了吗??