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rodent.py
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rodent.py
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"""
Rodent
Usage:
rodent.py capture [--until=<time>] [--folder=<folder>] [--interval=<interval>]
rodent.py make_video [--folder=<folder>]
rodent.py automate [--until=<time>] [--folder=<folder>] [--interval=<interval>]
rodent.py motion [--until=<time>] [--folder=<folder>]
Options:
-h --help Show this screen
--until=<time> Until when to record, needs to be a HH:MM format (ie 12:45)
--folder=<folder> The folder in which the pictures are stored [default: photos]
--interval=<interval> The interval between 2 photos [default: 1]
"""
import datetime
import os
import time
import cv2
from docopt import docopt
import utils
def start_camera(camera, folder, interval, until=None):
"""
Start taking pictures every interval.
If until is specified, it will take pictures
until that time is reached (24h format).
Needs to be of the following format: HH:MM
"""
utils.clear_directory(folder)
number = 0
while True:
_, image = camera.read()
now = datetime.datetime.now()
number += 1
print 'Taking picture number %d at %s' % (number, now.isoformat())
utils.save_image(image, folder, now)
if utils.time_over(until, now):
break
time.sleep(interval)
del(camera)
def make_video(folder):
"""
Takes all the pics in the folder given and make a video
out of it.
"""
# Sorting on dates, ISO ftw
filenames = sorted(os.listdir(folder))
# Completely arbitrary values, probably will need to fix that later
# If the video is too fast or too slow, change the fps value manually
fps = 2
if 20 <= len(filenames) <= 40:
fps = 4
elif 41 <= len(filenames) <= 200:
fps = 10
elif 201 <= len(filenames) <= 500:
fps = 20
elif len(filenames) > 500:
fps = 40
# Find out size of the pictures we're taking
first_pic = cv2.imread('%s/%s' % (folder, filenames[0]))
# shape gives a tuple (height, width, layer)
height, width, _ = first_pic.shape
# magic below, might need to change the codec for your own webcam
fourcc = cv2.cv.CV_FOURCC(*'XVID')
video = cv2.VideoWriter('output.avi', fourcc, fps, (width, height))
for filename in filenames:
video.write(cv2.imread('%s/%s' % (folder, filename)))
video.release()
def motion_detection(camera, folder, until):
"""
Uses 3 frames to look for motion, can't remember where
I found it but it gives better result than my first try
with comparing 2 frames.
"""
utils.clear_directory(folder)
# Need to get 2 images to start with
previous_image = cv2.cvtColor(camera.read()[1], cv2.cv.CV_RGB2GRAY)
current_image = cv2.cvtColor(camera.read()[1], cv2.cv.CV_RGB2GRAY)
purple = (140, 25, 71)
while True:
now = datetime.datetime.now()
_, image = camera.read()
gray_image = cv2.cvtColor(image, cv2.cv.CV_RGB2GRAY)
difference1 = cv2.absdiff(previous_image, gray_image)
difference2 = cv2.absdiff(current_image, gray_image)
result = cv2.bitwise_and(difference1, difference2)
# Basic threshold, turn the bitwise_and into a black or white (haha)
# result, white (255) being a motion
_, result = cv2.threshold(result, 40, 255, cv2.THRESH_BINARY)
# Let's show a square around the detected motion in the original pic
low_point, high_point = utils.find_motion_boundaries(result.tolist())
if low_point is not None and high_point is not None:
cv2.rectangle(image, low_point, high_point, purple, 3)
print 'Motion detected ! Taking picture'
utils.save_image(image, folder, now)
previous_image = current_image
current_image = gray_image
if utils.time_over(until, now):
break
del(camera)
if __name__ == "__main__":
arguments = docopt(__doc__)
folder = arguments['--folder']
interval = int(arguments['--interval'])
until = arguments['--until']
camera = cv2.VideoCapture(0)
try:
if arguments['capture']:
start_camera(camera, folder, interval, until)
elif arguments['make_video']:
make_video(folder)
elif arguments['automate']:
start_camera(camera, folder, interval, until)
make_video(folder)
elif arguments['motion']:
motion_detection(camera, folder, until)
except KeyboardInterrupt:
# OpenCV doesn't like CTRL+C sometimes.
del(camera)