判断色块坐标是否在画面中心坐标一定范围内，报错？希望能看下我这逻辑代码是否可以？
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# Blob Detection Example # # This example shows off how to use the find_blobs function to find color # blobs in the image. This example in particular looks for dark green objects. import sensor, image, time, pyb,mjpeg from pyb import UART,Pin,Timer import utime import json uart=pyb.UART(3,115200,timeout_char=1000) uart.init(115200, bits=8, parity=None, stop=1) p_out = Pin('P7',Pin.OUT_PP) p_out.low() # For color tracking to work really well you should ideally be in a very, very, # very, controlled enviroment where the lighting is constant... blue_threshold_01 = (0, 100, -16, 127, -128, -31) #设置蓝色的阈值，括号里面的数值分别是L A B 的最大值和最小值（minL, maxL, minA, # maxA, minB, maxB），LAB的值在图像左侧三个坐标图中选取。如果是灰度图，则只需 #设置（min, max）两个数字即可。 # You may need to tweak the above settings for tracking green things... # Select an area in the Framebuffer to copy the color settings. sensor.reset() # Initialize the camera sensor. sensor.set_pixformat(sensor.RGB565) # use RGB565. sensor.set_framesize(sensor.QVGA) # use QVGA for quailtiy ,use QQVGA for speed. sensor.skip_frames(10) # Let new settings take affect. sensor.set_auto_whitebal(False) #关闭白平衡。白平衡是默认开启的，在颜色识别中，需要关闭白平衡。 clock = time.clock() # Tracks FPS. ''' 扩宽roi ''' def expand_roi(roi): # set for QQVGA 160*120 extra = 5 win_size = (160, 120) (x, y, width, height) = roi new_roi = [x-extra, y-extra, width+2*extra, height+2*extra] if new_roi[0] < 0: new_roi[0] = 0 if new_roi[1] < 0: new_roi[1] = 0 if new_roi[2] > win_size[0]: new_roi[2] = win_size[0] if new_roi[3] > win_size[1]: new_roi[3] = win_size[1] return tuple(new_roi) while(True): clock.tick() # Track elapsed milliseconds between snapshots(). img = sensor.snapshot() # Take a picture and return the image. # pixels_threshold=100, area_threshold=100 blobs = img.find_blobs([blue_threshold_01], area_threshold=150) if blobs: #如果找到了目标颜色 # print(blobs) for blob in blobs: #迭代找到的目标颜色区域 is_circle = False max_circle = None max_radius = -1 new_roi = expand_roi(blob.rect()) for c in img.find_circles(threshold = 2000, x_margin = 20, y_margin = 20, r_margin = 10, roi=new_roi): is_circle = True # img.draw_circle(c.x(), c.y(), c.r(), color = (255, 255, 255)) if c.r() > max_radius: max_radius = c.r() max_circle = c if is_circle: # 如果有对应颜色的圆形 标记外框 # Draw a rect around the blob. img.draw_rectangle(new_roi) # rect img.draw_rectangle(blob.rect()) # rect #用矩形标记出目标颜色区域 img.draw_cross(blob[5], blob[6]) # cx, cy img.draw_circle(max_circle.x(), max_circle.y(), max_circle.r(), color = (0, 0, 255)) img.draw_circle(max_circle.x(), max_circle.y(), max_circle.r() + 1, color = (0, 0, 255)) print(blob[5], blob[6]) z=100 x_h=(blob[5]>>8)&0xff x_l=blob[5]&0xff y_h=(blob[6]>>8)&0xff y_l=blob[6]&0xff z_h=(z>>8)&0xff z_l=z&0xff data=bytearray([0x02,x_h,x_l,y_h,y_l,z_h,z_l,0x06,0x0D,0X0A]) print('you send:',data) uart.write(data) if (sensor.width/2 -10<=blob[5]<=sensor.width/2 +10) and (sensor.height/2 -10<=blob[6]<=sensor.height/2 +10): z=50 x_h=(blob[5]>>8)&0xff x_l=blob[5]&0xff y_h=(blob[6]>>8)&0xff y_l=blob[6]&0xff z_h=(z>>8)&0xff z_l=z&0xff data1=bytearray([0x02,x_h,x_l,y_h,y_l,z_h,z_l,0x06,0x0D,0X0A]) print('you send:',data1) uart.write(data1) timesleep(1000) timesleep(1000) timesleep(1000) z=0 x_h=(blob[5]>>8)&0xff x_l=blob[5]&0xff y_h=(blob[6]>>8)&0xff y_l=blob[6]&0xff z_h=(z>>8)&0xff z_l=z&0xff data2=bytearray([0x02,x_h,x_l,y_h,y_l,z_h,z_l,0x06,0x0D,0X0A]) print('you send:',data2) uart.write(data2) #p_out.high() print(clock.fps()) # Note: Your OpenMV Cam runs about half as fast while # connected to your computer. The FPS should increase once disconnected.!
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sensor.width是个啥？
函数调用要用括号。
sensor.width()