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60 lines
2.1 KiB
Python
60 lines
2.1 KiB
Python
# GIF Video Recording on Movement 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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# You can use your OpenMV Cam to record gif files. You can either feed the
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# recorder object RGB565 frames or Grayscale frames. Use photo editing software
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# like GIMP to compress and optimize the Gif before uploading it to the web.
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#
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# This example demonstrates using frame differencing with your OpenMV Cam to do
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# motion detection. After motion is detected your OpenMV Cam will take video.
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import sensor, image, time, gif, pyb, os
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RED_LED_PIN = 1
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BLUE_LED_PIN = 3
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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.QQVGA) # or sensor.QVGA (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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if not "temp" in os.listdir(): os.mkdir("temp") # Make a temp directory
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while(True):
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pyb.LED(RED_LED_PIN).on()
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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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pyb.LED(RED_LED_PIN).off()
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sensor.snapshot().save("temp/bg.bmp")
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print("Saved background image - Now detecting motion!")
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pyb.LED(BLUE_LED_PIN).on()
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diff = 10 # We'll say we detected motion after 10 frames of motion.
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while(diff):
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img = sensor.snapshot()
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img.difference("temp/bg.bmp")
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stats = img.statistics()
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# Stats 5 is the max of the lighting color channel. The below code
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# triggers when the lighting max for the whole image goes above 20.
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# The lighting difference maximum should be zero normally.
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if (stats[5] > 20):
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diff -= 1
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g = gif.Gif("example-%d.gif" % pyb.rng(), loop=True)
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clock = time.clock() # Tracks FPS.
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print("You're on camera!")
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for i in range(100):
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clock.tick()
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# clock.avg() returns the milliseconds between frames - gif delay is in
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g.add_frame(sensor.snapshot(), delay=int(clock.avg()/10)) # centiseconds.
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print(clock.fps())
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g.close()
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pyb.LED(BLUE_LED_PIN).off()
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print("Restarting...")
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