find_keypoints()函数的返回数据
时间: 2024-04-21 08:29:46 浏览: 17
根据你提供的信息,我假设你是在讨论图像处理领域中的find_keypoints()函数。该函数通常用于在图像中寻找特征点或关键点,以便进行后续的特征提取和匹配等操作。其返回数据通常是一个包含检测到的关键点信息的数据结构,可以是一个数组、一个列表或者一个字典等。该数据结构通常包含每个关键点的坐标、尺度、方向、响应值等信息。具体的返回数据格式也可能因实现方式不同而有所差异。
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left_kp = left_arrow.find_keypoints(max_keypoints=1)[0]
这行代码的作用是找到一个左箭头图像的关键点。具体来说,它使用了一个名为`find_keypoints`的函数来找到图像中的关键点,该函数的参数`max_keypoints`指定要找到的最大关键点数,这里是1。函数返回一个关键点列表,而此处我们直接取第一个关键点。最后,将找到的关键点赋值给变量`left_kp`。
# Single Color Code Tracking Example # # This example shows off single color code tracking using the CanMV Cam. # # A color code is a blob composed of two or more colors. The example below will # only track colored objects which have both the colors below in them. import sensor, image, time, math # Color Tracking Thresholds (L Min, L Max, A Min, A Max, B Min, B Max) # The below thresholds track in general red/green things. You may wish to tune them... 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) # Codes are or'ed together when "merge=True" for "find_blobs". 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" must be set to merge overlapping color blobs for color codes. 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 == (1 << 1) | (1 << 0) # 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())
这段代码是一个单色码跟踪的示例,使用了CanMV Cam进行跟踪。它会跟踪具有下列颜色的物体:
1. 红色:亮度范围在30到100之间,A通道范围在15到127之间,B通道范围在15到127之间。
2. 绿色:亮度范围在30到100之间,A通道范围在-64到-8之间,B通道范围在-32到32之间。
代码中使用了图像传感器来捕获图像,并进行颜色跟踪。通过设置阈值来确定跟踪颜色的范围。然后,使用`find_blobs`函数找到符合阈值要求的颜色块,并绘制出来。最后,打印出每秒处理的帧数。
请注意,这段代码中的阈值是一些通用的阈值,你可能需要根据实际情况进行调整。