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45 lines
1.9 KiB
Python
45 lines
1.9 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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# Structural Similarity (SSIM) Example
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#
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# This example shows off how to use the SSIM algorithm on your OpenMV Cam
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# to detect differences between two images. The SSIM algorithm compares
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# 8x8 blocks of pixels between two images to determine a similarity
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# score between two images.
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import sensor
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import time
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# The image has likely changed if the sim.min() is lower than this.
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MIN_TRIGGER_THRESHOLD = -0.4
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sensor.reset() # Initialize the camera sensor.
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sensor.set_pixformat(sensor.RGB565) # or sensor.GRAYSCALE
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sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others)
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sensor.skip_frames(time=2000) # Let new settings take affect.
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sensor.set_auto_whitebal(False) # Turn off white balance.
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clock = time.clock() # Tracks 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. However,
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# frame differencing doesn't use a lot of the extra space in the frame buffer.
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# But, things like AprilTags do and won't work if you do this...
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extra_fb = sensor.alloc_extra_fb(sensor.width(), sensor.height(), sensor.RGB565)
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print("About to save background image...")
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sensor.skip_frames(time=2000) # Give the user time to get ready.
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extra_fb.replace(sensor.snapshot())
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print("Saved background image!")
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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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sim = img.get_similarity(extra_fb)
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change = "- Change -" if sim.min() < MIN_TRIGGER_THRESHOLD else "- No Change -"
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print(clock.fps(), change, sim)
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