Created
May 1, 2022 11:12
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Motion detection PiCamera
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from io import BytesIO | |
from time import sleep, time | |
from picamera import PiCamera | |
from PIL import Image, ImageChops | |
import numpy as np | |
def take_image(cam, stream): | |
stream.seek(0) | |
# stream.truncate() # resize to current position | |
print("Taking image") | |
cam.capture(stream, resize=(320, 240), format='jpeg') | |
# "Rewind" the stream to the beginning so we can read its content | |
return Image.open(stream) | |
def get_entropy(img): | |
w, h = img.size | |
a = np.array(img.convert('RGB')).reshape((w*h,3)) | |
h, e = np.histogramdd(a, bins=(16,)*3, range=((0,256),)*3) | |
prob = h/np.sum(h) # normalize | |
prob = prob[prob>0] # remove zeros | |
return -np.sum(prob*np.log2(prob)) | |
if __name__ == '__main__': | |
idx = 0 | |
streams = [BytesIO(), BytesIO()] | |
with PiCamera() as cam: | |
# cam.resolution = (1024, 768) | |
# Camera warmup (longer => better?) | |
cam.start_preview() | |
sleep(2) | |
imgs = [take_image(cam, streams[i]) for i in range(2)] | |
while True: | |
diff = ImageChops.difference(imgs[0], imgs[1]) | |
# arr = np.array(diff) | |
e = get_entropy(diff) | |
if e >= 0.2: | |
print(f"Motion detected: {e}") | |
diff.save(f"/tmp/diff-{int(time())}-{e}.jpeg") | |
else: | |
print(f"No motion: {e}") | |
sleep(60) # 10 sec | |
imgs[idx].close() | |
imgs[idx] = take_image(cam, streams[idx]) | |
idx = (idx + 1) % 2 |
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