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47 lines
2.2 KiB
Python
47 lines
2.2 KiB
Python
# Robust Linear Regression Example
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#
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# This example shows off how to use the get_regression() method on your OpenMV Cam
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# to get the linear regression of a ROI. Using this method you can easily build
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# a robot which can track lines which all point in the same general direction
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# but are not actually connected. Use find_blobs() on lines that are nicely
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# connected for better filtering options and control.
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#
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# We're using the robust=True argument for get_regression() in this script which
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# computes the linear regression using a much more robust algorithm... but potentially
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# much slower. The robust algorithm runs in O(N^2) time on the image. So, YOU NEED
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# TO LIMIT THE NUMBER OF PIXELS the robust algorithm works on or it can actually
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# take seconds for the algorithm to give you a result... THRESHOLD VERY CAREFULLY!
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THRESHOLD = (0, 100) # Grayscale threshold for dark things...
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BINARY_VISIBLE = True # Does binary first so you can see what the linear regression
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# is being run on... might lower FPS though.
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import sensor
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import time
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sensor.reset()
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sensor.set_pixformat(sensor.GRAYSCALE)
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sensor.set_framesize(sensor.QQQVGA) # 80x60 (4,800 pixels) - O(N^2) max = 2,3040,000.
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sensor.skip_frames(time = 2000) # WARNING: If you use QQVGA it may take seconds
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clock = time.clock() # to process a frame sometimes.
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while(True):
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clock.tick()
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img = sensor.snapshot().binary([THRESHOLD]) if BINARY_VISIBLE else sensor.snapshot()
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# Returns a line object similar to line objects returned by find_lines() and
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# find_line_segments(). You have x1(), y1(), x2(), y2(), length(),
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# theta() (rotation in degrees), rho(), and magnitude().
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#
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# magnitude() represents how well the linear regression worked. It means something
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# different for the robust linear regression. In general, the larger the value the
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# better...
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line = img.get_regression([(255,255) if BINARY_VISIBLE else THRESHOLD], robust = True)
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if (line): img.draw_line(line.line(), color = 127)
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print("FPS %f, mag = %s" % (clock.fps(), str(line.magnitude()) if (line) else "N/A"))
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# About negative rho values:
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#
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# A [theta+0:-rho] tuple is the same as [theta+180:+rho].
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