请问这个程序采用了自适应阈值巡线（黑线），找不到黑线（屏幕全白）是什么原因
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import sensor, image, math from pyb import UART,LED LED(3).on() uart = UART(3, 115200) uart.init(115200, bits=8, parity=None, stop=1) def send_data(data1,data2,data3): global uart data = bytearray([0xb3,0xb3,data1,data2,data3,0x5b]) uart.write(data) ROIS = [ (0, 0, 128, 40, 0.2), (0, 40, 128, 40, 0.4), (0, 80, 128, 40, 0.6) ] range_stop = [400,100,70] range_wait = 500 weight_sum = 0 for r in ROIS: weight_sum += r[4] sensor.reset() sensor.set_contrast(1) sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QQVGA2) sensor.set_brightness(10) sensor.skip_frames(30) sensor.set_auto_whitebal(False) sensor.set_vflip(False) sensor.set_hmirror(False) def find_max(blobs): max_size=[0,0] max_ID=[-1,-1] for i in range(len(blobs)): if blobs[i].pixels()>max_size[0]: max_ID[1]=max_ID[0] max_size[1]=max_size[0] max_ID[0]=i max_size[0]=blobs[i].pixels() elif blobs[i].pixels()>max_size[1]: max_ID[1]=i max_size[1]=blobs[i].pixels() return max_ID def degrees(radians): return (180 * radians) / math.pi #def stop1(): def car_run(): centroid_sum = [0,0] left_center=[-1,-1,-1] right_center=[-1,-1,-1] flag_cross=0 flag_wait = [0,0] flag_stop = [0,0] for r in range(3): blobs = img.find_blobs([(0, l), (-128, a),(-128, b)], roi=ROIS[r][0:4],merge=True,area_threshold=200,margin=3,pixel_threshold=200) if blobs: stop_flag = flag_stop[0] max_ID=[-1,-1] max_ID=find_max(blobs) img.draw_rectangle(blobs[max_ID[0]].rect(),50) img.draw_cross(blobs[max_ID[0]].cx(),blobs[max_ID[0]].cy(),50) if max_ID[1]!=-1: flag_cross=1 #有岔路口 img.draw_rectangle(blobs[max_ID[1]].rect(),50) img.draw_cross(blobs[max_ID[1]].cx(),blobs[max_ID[1]].cy(),50) if blobs[max_ID[0]].cx()<blobs[max_ID[1]].cx(): left_center[r]=blobs[max_ID[0]].cx() right_center[r]=blobs[max_ID[1]].cx() else: left_center[r]=blobs[max_ID[1]].cx() right_center[r]=blobs[max_ID[0]].cx() else: flag_cross=0 if blobs[max_ID[0]].pixels()>range_wait: flag_wait[0]+=1 elif blobs[max_ID[0]].pixels()>range_stop[r]: flag_stop[0]=r+1 left_center[r]=right_center[r]=blobs[max_ID[0]].cx() centroid_sum[0] += left_center[r] * ROIS[r][4] centroid_sum[1] += right_center[r] * ROIS[r][4] if stop_flag == 3 and flag_stop[0] == 2: flag_stop[1] = 1 else: flag_stop[1] = 0 center_pos =[0,0] center_pos[0] = (centroid_sum[0] / weight_sum) center_pos[1] = (centroid_sum[1] / weight_sum) deflection_angle = [0,0] deflection_angle[0] = -math.atan((center_pos[0]-64)/80) deflection_angle[1] = -math.atan((center_pos[1]-64)/80) deflection_angle[0] = math.degrees(deflection_angle[0]) deflection_angle[1] = math.degrees(deflection_angle[1]) if flag_wait[0] >= 2: flag_wait[1] = 1 else: flag_wait[1] = 0 if center_pos[0]==center_pos[1]==0: deflection_angle[1]=deflection_angle[0]=0 A=[int(deflection_angle[0]),int(deflection_angle[1]),flag_stop[1],flag_wait[1]] #1等待 return A while(True): cross = 1 flag = 1 if(uart.any()): flag = uart.readchar() if flag == 1: cross = 1 if flag == 2: cross = 1 if flag == 3: cross = 1 if flag == 6: cross = 1 if flag == 7: cross = 0 if flag == 4: cross = 1 else: cross = 1 img = sensor.snapshot().lens_corr(strength = 0.5, zoom = 1.0) img.bilateral(3,color_sigma=0.1,space_sigma=0.1)#采用双边滤波 img.gaussian(3, unsharp=True,)#图像消除锐化 histogram = img.get_histogram() THRESHOLD = histogram.get_threshold() l = THRESHOLD .l_value() a = THRESHOLD .a_value() b = THRESHOLD .b_value() print(THRESHOLD) img.binary([(0, l), (-128, a),(-128, b)]) row_data=[0,0,0,0] row_data[0],row_data[1],row_data[2],row_data[3]=car_run() if cross == 0: if row_data[0] < -4: send_data(-4,row_data[2],row_data[3]) if -4<= row_data[0] < 0: send_data(row_data[0],row_data[2],row_data[3]) if 0 <= row_data[0] <= 3: send_data(0,row_data[2],row_data[3]) if row_data[0] >3: send_data(row_data[0],row_data[2],row_data[3]) if cross == 1: if row_data[1] < -5: send_data(-5,row_data[2],row_data[3]) if -5<= row_data[1] < 0: send_data(row_data[1],row_data[2],row_data[3]) if 0 <= row_data[1] <= 3: send_data(0,row_data[2],row_data[3]) if row_data[1] >3: send_data(row_data[1],row_data[2],row_data[3])
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我感觉是RGB模式下结果有问题，可以暂时用灰度图：
import sensor, image, time sensor.reset() sensor.set_pixformat(sensor.GRAYSCALE) sensor.set_framesize(sensor.QVGA) sensor.skip_frames(time = 2000) clock = time.clock() while(True): img = sensor.snapshot() histogram = img.get_histogram() THRESHOLD = histogram.get_threshold() print(THRESHOLD) img.binary([(0, THRESHOLD.value())])