# Basic Frame Differencing Example # # Note: You will need an SD card to run this example. # # This example demonstrates using frame differencing with your OpenMV Cam. It's # called basic frame differencing because there's no background image update. # So, as time passes the background image may change resulting in issues. import sensor, image, pyb, os, time TRIGGER_THRESHOLD = 5 sensor.reset() # Initialize the camera sensor. sensor.set_pixformat(sensor.RGB565) # or sensor.GRAYSCALE sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others) sensor.skip_frames(time = 2000) # Let new settings take affect. sensor.set_auto_whitebal(False) # Turn off white balance. clock = time.clock() # Tracks FPS. if not "temp" in os.listdir(): os.mkdir("temp") # Make a temp directory print("About to save background image...") sensor.skip_frames(time = 2000) # Give the user time to get ready. sensor.snapshot().save("temp/bg.bmp") print("Saved background image - Now frame differencing!") while(True): clock.tick() # Track elapsed milliseconds between snapshots(). img = sensor.snapshot() # Take a picture and return the image. # Replace the image with the "abs(NEW-OLD)" frame difference. img.difference("temp/bg.bmp") hist = img.get_histogram() # This code below works by comparing the 99th percentile value (e.g. the # non-outlier max value against the 90th percentile value (e.g. a non-max # value. The difference between the two values will grow as the difference # image seems more pixels change. diff = hist.get_percentile(0.99).l_value() - hist.get_percentile(0.90).l_value() triggered = diff > TRIGGER_THRESHOLD print(clock.fps(), triggered) # Note: Your OpenMV Cam runs about half as fast while # connected to your computer. The FPS should increase once disconnected.