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* Added pooling functions to make getting small images easy. set_binning works too... but, it zooms in way to much. pooling functions aout you to shrink the image while not zooming in. * To make the pooling functions easy to use I created a version that pools the image out of place and one that pools the image in place. The inplace pooling function can work on the frame buffer (see edits to sensor.c) * I added the code to do hann windowing to the FFT lib. However, I commented it out after it improved performance by basically zero. Specialized windowing stuff will only come in handy for folks trying to tune their algorithm... not in general for everything. * I added subpixel resolution for the phase correlation code. You can now track the image movement really precisely. Additionally, I fixed up the displacement outputs to give expected results. I also added a QoR output for the displacement code so that you can know when the results are bad. * Finally, an example script has been added to show off the features.
46 lines
1.9 KiB
Python
46 lines
1.9 KiB
Python
# Optical Flow Example
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#
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# Your OpenMV Cam can use optical flow to determine the displacement between
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# two images. This allows your OpenMV Cam to track movement like how your laser
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# mouse tracks movement. By tacking the difference between successive images
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# you can determine instaneous displacement with your OpenMV Cam too!
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import sensor, image, time
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sensor.reset() # Initialize the camera sensor.
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sensor.set_pixformat(sensor.GRAYSCALE) # or sensor.GRAYSCALE
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sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others)
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sensor.skip_frames(10) # Let new settings take affect.
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clock = time.clock() # Tracks FPS.
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# Create a down sampled copy of the image. Down sampling is by 5 (horizontally)
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# and 4 (vertically). This results in a 64x60 image from QVGA.
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old = sensor.snapshot().mean_pooled(5, 4)
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# NOTE: The find_displacement function works by taking the 2D FFTs of the old
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# and new images and compares them using phase correlation. Your OpenMV Cam
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# only has enough memory to work on two 64x64 FFTs (or 128x32, 32x128, or etc).
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while(True):
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clock.tick() # Track elapsed milliseconds between snapshots().
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img = sensor.snapshot() # Take a picture and return the image.
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# Down sample the current image in place.
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img.mean_pool(5, 4)
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# Delta X is the x displacement. Note that it is only valid for small
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# amounts of displacement before being ambiguous...
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# Delta Y is the x displacement. Note that it is only valid for small
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# amounts of displacement before being ambiguous...
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# Reponse is the quality of the displacement info. When it goes below
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# 0.10 or so the quality of the results are poor...
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[delta_x, delta_y, response] = old.find_displacement(img)
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print("%0.1f X\t%0.1f Y\t%0.2f QoR\t%0.2f FPS" % \
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(delta_x, delta_y, response, clock.fps()))
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# Uncomment this to get the difference between frames
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# old = img.copy()
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