Routine explanation 10-Color-Tracking->multi_color_code_tracking multi-color combination recognition
Video tutorial 4 - Color recognition: https://singtown.com/learn/49993/
# 多颜色组合识别
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# 这个例子展示了使用OpenMV Cam进行多色代码跟踪。
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# 颜色代码是由两种或更多颜色组成的色块。下面的例子只会跟踪其中有两种或多种颜色的彩色物体。
import sensor, image, time
# 颜色跟踪阈值(L Min, L Max, A Min, A Max, B Min, B Max)
# 下面的阈值一般跟踪红色/绿色的东西。你可以调整它们…
thresholds = [(30, 100, 15, 127, 15, 127), # generic_red_thresholds -> index is 0 so code == (1 << 0)
(30, 100, -64, -8, -32, 32), # generic_green_thresholds -> index is 1 so code == (1 << 1)
(0, 15, 0, 40, -80, -20)] # generic_blue_thresholds -> index is 2 so code == (1 << 2)
# 当“find_blobs”的“merge = True”时,code代码被组合在一起。
sensor.reset()
#初始化摄像头,reset()是sensor模块里面的函数
sensor.set_pixformat(sensor.RGB565)
#设置图像色彩格式,有RGB565色彩图和GRAYSCALE灰度图两种
sensor.set_framesize(sensor.QVGA)
#设置图像像素大小
sensor.skip_frames(time = 2000)
sensor.set_auto_gain(False) # 颜色跟踪必须关闭自动增益
sensor.set_auto_whitebal(False) # 颜色跟踪必须关闭白平衡
clock = time.clock()
# 只有比“pixel_threshold”多的像素和多于“area_threshold”的区域才被
# 下面的“find_blobs”返回。 如果更改相机分辨率,
# 请更改“pixels_threshold”和“area_threshold”。 “merge = True”合并图像中所有重叠的色块。
while(True):
clock.tick()
img = sensor.snapshot()
for blob in img.find_blobs(thresholds, pixels_threshold=100, area_threshold=100, merge=True):
if blob.code() == 3: # r/g code
img.draw_rectangle(blob.rect())
img.draw_cross(blob.cx(), blob.cy())
img.draw_string(blob.x() + 2, blob.y() + 2, "r/g")
if blob.code() == 5: # r/b code
img.draw_rectangle(blob.rect())
img.draw_cross(blob.cx(), blob.cy())
img.draw_string(blob.x() + 2, blob.y() + 2, "r/b")
if blob.code() == 6: # g/b code
img.draw_rectangle(blob.rect())
img.draw_cross(blob.cx(), blob.cy())
img.draw_string(blob.x() + 2, blob.y() + 2, "g/b")
if blob.code() == 7: # r/g/b code
img.draw_rectangle(blob.rect())
img.draw_cross(blob.cx(), blob.cy())
img.draw_string(blob.x() + 2, blob.y() + 2, "r/g/b")
print(clock.fps())
Singtown Technology OpenMV official Chinese document function explanation: