Crypto Smart Camera: Motion Capture

motion_capture.py

import io
import random
import picamera
from PIL import Image
from
import json
import re
import requests

global previous_frame
global current_frame
global last_capture_at
global avg

def upload_capture():
    if current_frame is not None:
        last_capture_at = time.time()
        Note(host='http://greenthumb-proto.herokuapp.com',
             title='This is an automated upload',
             frame=current_frame,
             profile=profile,
             user_email='myemail@gmail.com',

             user_token='sometokenhere').create_note()

def detect_motion(camera):
    stream = io.BytesIO()
    camera.capture(stream, format='jpeg', use_video_port=True)
    stream.seek(0)
    if previous_frame is None:
        previous_frame = Image.open(stream)
        return False
    else:
        current_frame = Image.open(stream)
        result = motion(current_frame, previous_frame)
        # You could decide to call upload_capture() 
        # Here periodically in an event loop for timelapse uploads
        previous_frame = current_frame

        return result

with picamera.PiCamera() as camera:
    camera.resolution = (1920, 1080)
    stream = picamera.PiCameraCircularIO(camera, seconds=10)

    try:
        while True:
            camera.wait_recording(1)
            periodic_capture()
            if detect_motion(camera):
                print('Motion detected!')
                note = Note(host='http://greenthumb-proto.herokuapp.com',
                    title='This is an automated upload',
                    profile=profile,
                    user_email='myemail@gmail.com',
                    user_token='sometokenhere')
                # Split the camera recording to the note frames buffer
                camera.split_recording(note)
                # Copy the last 10 seconds of the stream prior to the split to the note
                stream.copy_to(note, seconds=10)
                # Clear the in memory stream buffer
                stream.clear()
                # Wait on recording while detect_motion is true for the camera feed
                while detect_motion(camera):
                    camera.wait_recording(1)
                                    
                print('Motion stopped!')
                # Split the camera recording back to the in memory stream buffer
                camera.split_recording(stream)
                note.create_note()
    finally:
        camera.stop_recording()

Taking from the examples of split capturing from a circular stream and custom output objects