自动RGB565颜色跟踪示例
这个例子展示了使用OpenMV的单色自动RGB565色彩跟踪。
import sensor, image, time
print("Letting auto algorithms run. Don't put anything in front of the camera!")
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
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()
捕捉图像中心的颜色阈值。
r = [(320//2)-(50//2), (240//2)-(50//2), 50, 50] # 50x50 center of QVGA.
print("Auto algorithms done. Hold the object you want to track in front of the camera in the box.")
print("MAKE SURE THE COLOR OF THE OBJECT YOU WANT TO TRACK IS FULLY ENCLOSED BY THE BOX!")
for i in range(60):
img = sensor.snapshot()
img.draw_rectangle(r)
print("Learning thresholds...")
threshold = [50, 50, 0, 0, 0, 0] # Middle L, A, B values.
for i in range(60):
img = sensor.snapshot()
hist = img.get_histogram(roi=r)
lo = hist.get_percentile(0.01) # 获取1％范围的直方图的CDF（根据需要调整）！
hi = hist.get_percentile(0.99) # 获取1％范围的直方图的CDF（根据需要调整）！
# 平均百分位值。
threshold[0] = (threshold[0] + lo.l_value()) // 2
threshold[1] = (threshold[1] + hi.l_value()) // 2
threshold[2] = (threshold[2] + lo.a_value()) // 2
threshold[3] = (threshold[3] + hi.a_value()) // 2
threshold[4] = (threshold[4] + lo.b_value()) // 2
threshold[5] = (threshold[5] + hi.b_value()) // 2
for blob in img.find_blobs([threshold], pixels_threshold=100, area_threshold=100, merge=True, margin=10):
img.draw_rectangle(blob.rect())
img.draw_cross(blob.cx(), blob.cy())
img.draw_rectangle(r)
print("Thresholds learned...")
print("Tracking colors...")
while(True):
clock.tick()
img = sensor.snapshot()
for blob in img.find_blobs([threshold], pixels_threshold=100, area_threshold=100, merge=True, margin=10):
img.draw_rectangle(blob.rect())
img.draw_cross(blob.cx(), blob.cy())
print(clock.fps())
对于识别相同的颜色，用以上程序得到的颜色阈值与自己在阈值编辑器里得到的阈值相差较大（就是用以上程序识别颜色的效果不大理想），请问大神您有什么更好的自动RGB565色彩跟踪方法呢