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69 lines
2.7 KiB
Python
69 lines
2.7 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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# Advanced Frame Differencing Example
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#
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# Note: You will need an SD card to run this example.
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#
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# This example demonstrates using frame differencing with your OpenMV Cam. This
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# example is advanced because it performs a background update to deal with the
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# background image changing overtime.
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import sensor
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import os
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import time
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TRIGGER_THRESHOLD = 5
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BG_UPDATE_FRAMES = 50 # How many frames before blending.
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BG_UPDATE_BLEND = 128 # How much to blend by... ([0-255]==[0.0-1.0]).
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sensor.reset() # Initialize the camera sensor.
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sensor.set_pixformat(sensor.RGB565) # or sensor.RGB565
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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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if not "temp" in os.listdir():
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os.mkdir("temp") # Make a temp directory
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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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sensor.snapshot().save("temp/bg.bmp")
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print("Saved background image - Now frame differencing!")
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triggered = False
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frame_count = 0
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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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frame_count += 1
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if frame_count > BG_UPDATE_FRAMES:
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frame_count = 0
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# Blend in new frame. We're doing 255-alpha here because we want to
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# blend the new frame into the background. Not the background into the
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# new frame which would be just alpha. Blend replaces each pixel by
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# ((NEW*(alpha))+(OLD*(255-alpha)))/255. So, a low alpha results in
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# low blending of the new image while a high alpha results in high
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# blending of the new image. We need to reverse that for this update.
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img.blend("temp/bg.bmp", alpha=(255 - BG_UPDATE_BLEND))
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img.save("temp/bg.bmp")
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# Replace the image with the "abs(NEW-OLD)" frame difference.
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img.difference("temp/bg.bmp")
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hist = img.get_histogram()
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# This code below works by comparing the 99th percentile value (e.g. the
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# non-outlier max value against the 90th percentile value (e.g. a non-max
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# value. The difference between the two values will grow as the difference
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# image seems more pixels change.
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diff = hist.get_percentile(0.99).l_value() - hist.get_percentile(0.90).l_value()
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triggered = diff > TRIGGER_THRESHOLD
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print(clock.fps(), triggered) # Note: Your OpenMV Cam runs about half as fast while
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# connected to your computer. The FPS should increase once disconnected.
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