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Create 7 hour video from +250.000 frames

I have 14 videos of 30 minutes (7 hours of videodata). I read in every video seperately, perform some morphological processing on each frame and then use cv2.imwrite() to save each processed frame. I'd like to make 1 big videofile of 7 hours of all processed frames. So far, I've been trying to use this code:
import numpy as np
import glob
img_array = []
for filename in glob.glob('C:/New folder/Images/*.jpg'):
img = cv2.imread(filename)
height, width, layers = img.shape
size = (width,height)
img_array.append(img)
out = cv2.VideoWriter('project.avi',cv2.VideoWriter_fourcc(*'DIVX'), 15, size)
for i in range(len(img_array)):
out.write(img_array[i])
out.release()
But an error is given when creating the img_array (memory overload). Is there any other way to make a 7 hour video from +250.000 frames?
Thank you.

check that all pictures are of the same size
as stated by others, don't read all pictures at once. it's not necessary.
Usually I'd prefer to create the VideoWriter before the loop but you need the size for that, and you only know that after you've read the first image. That's why I initialize that variable to None and create the VideoWriter once I have the first image
Also: DIVX and .avi may work but that's not the best option. the built-in option is to use MJPG (with .avi), which is always available in OpenCV. I would however recommend .mkv and avc1 (H.264) for general video, or you could look for a lossless codec that stores data in RGB instead of YUV (which may distort color information from screenshots... and also drawn lines and other hard edges). You could try the rle (note the space) codec, which is a lossless codec based on run-length encoding.
import cv2 # `import cv2 as cv` is preferred these days
import numpy as np
import glob
out = None # VideoWriter initialized after reading the first image
outsize = None
for filename in glob.glob('C:/New folder/Images/*.jpg'):
img = cv2.imread(filename)
assert img is not None, filename # file could not be read
(height, width, layers) = img.shape
thissize = (width, height)
if out is None: # this happens once at the beginning
outsize = thissize
out = cv2.VideoWriter('project.avi', cv2.VideoWriter_fourcc(*'DIVX'), 15, outsize)
assert out.isOpened()
else: # error checking for every following image
assert thissize == outsize, (outsize, thissize, filename)
out.write(img)
# finalize the video file (write headers/footers)
out.release()
You could also do this with an invocation of ffmpeg on the command line (or from your program):
How to create a video from images with FFmpeg?

You don't need to store each frame inside an array.
You can read the frame and write it to the video directly.
You can modify your code as:
import numpy as np
import glob
out = None
for filename in glob.glob('C:/New folder/Images/*.jpg'):
img = cv2.imread(filename)
if not out:
height, width, layers = img.shape
size = (width,height)
out = cv2.VideoWriter('project.avi',cv2.VideoWriter_fourcc(*'DIVX'), 15, size)
out.write(img)
out.release()

How do i take median of 5 grayscale frames?

I am taking input from a video and I want to take the median value of the first 5 frames so that I can use it as background image for motion detection using deferential.
Also, I want to use a time condition that, say if motion is not detected then calculate the background again, else wait t seconds. I am new to opencv and I don't know how to do it.. Please help
Also, I want to take my video in 1 fps but this does not work. Here is the code I have:
import cv2
BLUR_SIZE = 3
NOISE_CUTOFF = 12
cam = cv2.VideoCapture('gh10fps.mp4')
cam.set(3, 640)
cam.set(4, 480)
cam.set(cv2.cv.CV_CAP_PROP_FPS, 1)
fps=cam.get(cv2.cv.CV_CAP_PROP_FPS)
print "Current FPS: ",fps

If you really want the median of the first 5 frames, then following should do what you are looking for:
import numpy as np
import cv2
cap = cv2.VideoCapture(0)
frames = []
for _ in range(5):
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
frames.append(gray)
median = np.median(frames, axis=0).astype(dtype=np.uint8)
cv2.imshow('frame', median)
cv2.waitKey(0)
cap.release()
cv2.destroyAllWindows()
Note, this is just taking the source from a webcam as an example.

Python: How to get some images from a video in Python3?

How can I extract frames from a video file using Python3?
For example, I want to get 16 picture from a video and combine them into a 4x4 grid.
I don't want 16 separate images at the end, I want one image containing 16 frames from the video.
----Edit----
import av
container = av.open('/home/uguraba/Downloads/equals/equals.mp4')
video = next(s for s in container.streams)
for packet in container.demux(video):
for frame in packet.decode():
if frame.index %3000==0:
frame.to_image().save('/home/uguraba/Downloads/equals/frame-%04d.jpg' % frame.index)
By using this script i can get frames. There will be lots of frames saved. Can i take specific frames like 5000-7500-10000 ?
Also my question is how can i see the total frame number ?

Use PyMedia or PyAV to access image data and PIL or Pillow to manipulate it in desired form(s).
These libraries have plenty of examples, so with basic knowledge about the video muxing/demuxing and picture editing you should be able to do it pretty quickly. It's not so complicated as it would seem at first.
Essentially, you demux the video stream into frames, going frame by frame.
You get the picture either in its original (e.g. JPEG) or raw form and push it into PIL/Pillow.
You do with it what you want, resizing etc... - PIL provides all necessary stuff.
And then you paste it into one big image at desired position.
That's all.

You can do that with OpenCV3, the Python wrapper and Numpy.
First you need to do is capture the frames then save them separately and finally paste them all in a bigger matrix.
import numpy as np
import cv2
cap = cv2.VideoCapture(video_source)
# capture the 4 frames
_, frame1 = cap.read()
_, frame2 = cap.read()
_, frame3 = cap.read()
_, frame4 = cap.read()
# 'glue' the frames using numpy and vertigal/horizontal stacks
big_frame = np.vstack((np.hstack((frame1, frame2)),
np.hstack((frame3, frame4))))
# Show a 4x4 unique frame
cv2.imshow('result', big_frame)
cv2.waitKey(1000)
To compile and install OpenCV3 and Numpy in Python3 you can follow this tutorial.
You can implement a kind of "control panel" from 4 different video sources with something like that:
import numpy as np
import cv2
cam1 = cv2.VideoCapture(video_source1)
cam2 = cv2.VideoCapture(video_source2)
cam3 = cv2.VideoCapture(video_source3)
cam4 = cv2.VideoCapture(video_source4)
while True:
more1, frame_cam1 = cam1.read()
more2, frame_cam2 = cam2.read()
more3, frame_cam3 = cam3.read()
more4, frame_cam4 = cam4.read()
if not all([more1, more2, more3, more4]) or cv2.waitKey(1) & 0xFF in (ord('q'), ord('Q')):
break
big_frame = np.vstack((np.hstack((frame_cam1, frame_cam2)),
np.hstack((frame_cam3, frame_cam4))))
# Show a 4x4 unique frame
cv2.imshow('result', big_frame)
print('END. One or more sources ended.')

Reduced camera resolution but higher display window in python open cv

I am working on a project which requires to do face detection on raspberry pi. I have a USB camera to do this. The frame rate was apparently very slow. So, I scaled down the capture resolution using VideoCapture.set(). This decreased the resolution to 320, 214 as I set it. This increased the capture frame rate considerably but it the feed in displayed the feed on a window on 320 X 214. I want to keep the same capture resolution but I want higher size display window. I am just a beginner to python and open cv. Please help me do it. Below is the code I wrote for just a simple camera feed.
import numpy as np
import cv2
import time
cap = cv2.VideoCapture(-1)
cap.set(3, 320) #width
cap.set(4, 216) #height
cap.set(5, 15) #frame rate
time.sleep(2)
while(cap.isOpened()):
ret, frame = cap.read()
cv2.imshow("captured video", frame)
if cv2.waitKey(33) == ord('q'):
break
cap.release()
cv2.destroyAllWindows()

If I understand you correctly, you want the display image to be a scaled up version of the original. If so, you just need cv2.resize
display_scale = 4
height, width = frame.shape[0:2]
height_display, width_display = display_scale * height, display_scale * width
# you can choose different interpolation methods
frame_display = cv2.resize(frame, (display_width, display_height),
interpolation=cv2.INTER_CUBIC)
cv2.imshow("captured video", frame_display)

Python JPEG to movie

I am looking for a way to concatenate a directory of images files (e.g., JPEGs) to a movie file (MOV, MP4, AVI) with Python. Ideally, this would also allow me to take multiple JPEGs from that directory and "paste" them into a grid which is one frame of a movie file. Which modules could achieve this?

You could use the Python interface of OpenCV, in particular a VideoWriter could probably do the job. From what I understand of the doc, the following would do what you want:
w = cvCreateVideoWriter(filename, -1, <your framerate>,
<your frame size>, is_color=1)
and, in a loop, for each file:
cvWriteFrame(w, frame)
Note that I have not tried this code, but I think that I got the idea right. Please tell me if it works.

here's a cut-down version of a script I have that took frames from one video and them modified them(that code taken out), and written to another video. maybe it'll help.
import cv2
fourcc = cv2.cv.CV_FOURCC(*'XVID')
out = cv2.VideoWriter('out_video.avi', fourcc, 24, (704, 240))
c = cv2.VideoCapture('in_video.avi')
while(1):
_, f = c.read()
if f is None:
break
f2 = f.copy() #make copy of the frame
#do a bunch of stuff (missing)
out.write(f2) #write frame to the output video
out.release()
cv2.destroyAllWindows()
c.release()
If you have a bunch of images, load them in a loop and just write one image after another to your vid.

I finally got into a working version of the project that got me into this question.
Now I want to contribute with the knowledge I got.
Here is my solution for getting all pictures in current directory and converting into a video having then centralized in a black background, so this solution works for different size images.
import glob
import cv2
import numpy as np
DESIRED_SIZE = (800, 600)
SLIDE_TIME = 5 # Seconds each image
FPS = 24
fourcc = cv2.VideoWriter.fourcc(*'X264')
writer = cv2.VideoWriter('output.avi', fourcc, FPS, DESIRED_SIZE)
for file_name in glob.iglob('*.jpg'):
img = cv2.imread(file_name)
# Resize image to fit into DESIRED_SIZE
height, width, _ = img.shape
proportion = min(DESIRED_SIZE[0]/width, DESIRED_SIZE[1]/height)
new_size = (int(width*proportion), int(height*proportion))
img = cv2.resize(img, new_size)
# Centralize image in a black frame with DESIRED_SIZE
target_size_img = np.zeros((DESIRED_SIZE[1], DESIRED_SIZE[0], 3), dtype='uint8')
width_offset = (DESIRED_SIZE[0] - new_size[0]) // 2
height_offset = (DESIRED_SIZE[1] - new_size[1]) // 2
target_size_img[height_offset:height_offset+new_size[1],
width_offset:width_offset+new_size[0]] = img
for _ in range(SLIDE_TIME * FPS):
writer.write(target_size_img)
writer.release()

Is it actually important to you that the solution should use python and produce a movie file? Or are these just your expectations of what a solution would look like?
If you just want to be able to play back a bunch of jpeg files as a movie, you can do it without using python or cluttering up your computer with .avi/.mov/mp4 files by going to vidmyfigs.com and using your mouse to select image files from your hard drive. The "movie" plays back in your Web browser.