5分钟上手Open MV颜色识别_openmv中怎么通过hsv来识别颜色

代码是选自星瞳OpenMV实例，下面我就讲解如何调参，修改代码。

①阈值调试器位置

②对LAB进行调试

使想要识别的物体呈现白色，背景为黑色

③获取LAB阈值并改入

将thresholds的参数改为刚复制的LAB阈值

# Single Color RGB565 Blob Tracking Example
#
# This example shows off single color RGB565 tracking using the OpenMV Cam.
 
import sensor
import time
import math
 
threshold_index = 0  # 0 for red, 1 for green, 2 for blue
 
# Color Tracking Thresholds (L Min, L Max, A Min, A Max, B Min, B Max)
# The below thresholds track in general red/green/blue things. You may wish to tune them...
thresholds = [
    (30, 100, 15, 127, 15, 127),  # generic_red_thresholds
    (30, 100, -64, -8, -32, 32),  # generic_green_thresholds
    (0, 30, 0, 64, -128, 0),
]  # generic_blue_thresholds
 
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()
 
# Only blobs that with more pixels than "pixel_threshold" and more area than "area_threshold" are
# returned by "find_blobs" below. Change "pixels_threshold" and "area_threshold" if you change the
# camera resolution. "merge=True" merges all overlapping blobs in the image.
 
while True:
    clock.tick()
    img = sensor.snapshot()
    for blob in img.find_blobs(
        [thresholds[threshold_index]],
        pixels_threshold=200,
        area_threshold=200,
        merge=True,
    ):
        # These values depend on the blob not being circular - otherwise they will be shaky.
        if blob.elongation() > 0.5:
            img.draw_edges(blob.min_corners(), color=(255, 0, 0))
            img.draw_line(blob.major_axis_line(), color=(0, 255, 0))
            img.draw_line(blob.minor_axis_line(), color=(0, 0, 255))
        # These values are stable all the time.
        img.draw_rectangle(blob.rect())
        img.draw_cross(blob.cx(), blob.cy())
        # Note - the blob rotation is unique to 0-180 only.
        img.draw_keypoints(
            [(blob.cx(), blob.cy(), int(math.degrees(blob.rotation())))], size=20
        )
    print(clock.fps())

 

④改后效果

可以看到图象识别已经改为绿色

代码展示

# Single Color RGB565 Blob Tracking Example
#
# This example shows off single color RGB565 tracking using the OpenMV Cam.
 
import sensor
import time
import math
 
threshold_index = 0  # 0 for red, 1 for green, 2 for blue
 
# Color Tracking Thresholds (L Min, L Max, A Min, A Max, B Min, B Max)
# The below thresholds track in general red/green/blue things. You may wish to tune them...
thresholds = [
    (0, 76, -128, -13, -128, 31),  # LAB_thresholds
]
 
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()
 
# Only blobs that with more pixels than "pixel_threshold" and more area than "area_threshold" are
# returned by "find_blobs" below. Change "pixels_threshold" and "area_threshold" if you change the
# camera resolution. "merge=True" merges all overlapping blobs in the image.
 
while True:
    clock.tick()
    img = sensor.snapshot()
    for blob in img.find_blobs(
        [thresholds[threshold_index]],
        pixels_threshold=200,
        area_threshold=200,
        merge=True,
    ):
        # These values depend on the blob not being circular - otherwise they will be shaky.
        if blob.elongation() > 0.5:
            img.draw_edges(blob.min_corners(), color=(255, 0, 0))
            img.draw_line(blob.major_axis_line(), color=(0, 255, 0))
            img.draw_line(blob.minor_axis_line(), color=(0, 0, 255))
        # These values are stable all the time.
        img.draw_rectangle(blob.rect())
        img.draw_cross(blob.cx(), blob.cy())
        # Note - the blob rotation is unique to 0-180 only.
        img.draw_keypoints(
            [(blob.cx(), blob.cy(), int(math.degrees(blob.rotation())))], size=20
        )
    print(clock.fps())