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78 lines
3.3 KiB
Python
78 lines
3.3 KiB
Python
# This work is licensed under the MIT license.
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# Copyright (c) 2013-2023 OpenMV LLC. All rights reserved.
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# https://github.com/openmv/openmv/blob/master/LICENSE
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#
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# Differential Optical Flow Rotation/Scale
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#
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# This example shows off using your OpenMV Cam to measure
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# rotation/scale by comparing the current and the previous
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# image against each other. Note that only rotation/scale is
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# handled - not X and Y translation in this mode.
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#
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# To run this demo effectively please mount your OpenMV Cam on a steady
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# base and SLOWLY rotate the camera around the lens and move the camera
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# forward/backwards to see the numbers change.
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# I.e. Z direction changes only.
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#
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# NOTE You have to use a small power of 2 resolution when using
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# find_displacement(). This is because the algorithm is powered by
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# something called phase correlation which does the image comparison
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# using FFTs. A non-power of 2 resolution requires padding to a power
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# of 2 which reduces the usefulness of the algorithm results. Please
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# use a resolution like B64X64 or B64X32 (2x faster).
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#
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# Your OpenMV Cam supports power of 2 resolutions of 64x32, 64x64,
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# 128x64, and 128x128. If you want a resolution of 32x32 you can create
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# it by doing "img.scale(x_scale=0.5, y_scale=0.5, hint=image.AREA)" on a 64x64 image.
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import sensor
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import time
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import math
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sensor.reset() # Reset and initialize the sensor.
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sensor.set_pixformat(sensor.RGB565) # Set pixel format to RGB565 (or GRAYSCALE)
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sensor.set_framesize(sensor.B64X64) # Set frame size to 64x64... (or 64x32)...
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sensor.skip_frames(time=2000) # Wait for settings take effect.
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clock = time.clock() # Create a clock object to track the FPS.
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# Take from the main frame buffer's RAM to allocate a second frame buffer.
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# There's a lot more RAM in the frame buffer than in the MicroPython heap.
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# However, after doing this you have a lot less RAM for some algorithms...
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# So, be aware that it's a lot easier to get out of RAM issues now.
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extra_fb = sensor.alloc_extra_fb(sensor.width(), sensor.height(), sensor.RGB565)
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extra_fb.replace(sensor.snapshot())
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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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# This algorithm is hard to test without a perfect jig... So, here's a cheat to see it works.
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# Put in a z_rotation value below and you should see the r output be equal to that.
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if 0:
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expected_rotation = 20.0
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extra_fb.rotation_corr(z_rotation=(-expected_rotation))
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# This algorithm is hard to test without a perfect jig... So, here's a cheat to see it works.
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# Put in a zoom value below and you should see the z output be equal to that.
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if 0:
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expected_zoom = 0.8
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extra_fb.rotation_corr(zoom=(2.00 - expected_zoom))
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displacement = extra_fb.find_displacement(img, logpolar=True)
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extra_fb.replace(img)
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# Offset results are noisy without filtering so we drop some accuracy.
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rotation_change = int(math.degrees(displacement.rotation()) * 5) / 5.0
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zoom_amount = displacement.scale()
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if (
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displacement.response() > 0.1
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): # Below 0.1 or so (YMMV) and the results are just noise.
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print(
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"{0:+f}r {1:+f}z {2} {3} FPS".format(
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rotation_change, zoom_amount, displacement.response(), clock.fps()
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)
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)
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else:
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print(clock.fps())
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