颜色识别与形状识别的组合

核心思路

根据色块做一遍初筛 然后在roi中继续寻找圆形

演示效果

Color And Shape

源代码

# 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

# For color tracking to work really well you should ideally be in a very, very,
# very, controlled enviroment where the lighting is constant...
red_threshold_01 = (120, 160, 0, 40, 0, 40)

#设置红色的阈值,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.QQVGA) # 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([red_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, 255, 0))
                img.draw_circle(max_circle.x(), max_circle.y(), max_circle.r() + 1, color = (0, 255, 0))


    print(clock.fps()) # Note: Your OpenMV Cam runs about half as fast while
    # connected to your computer. The FPS should increase once disconnected.
Copyright 杭州云江科技有限公司 2017 all right reserved,powered by Gitbook该文件修订时间: 2018-04-02 09:53:12

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