Often, we have to capture live stream with camera. OpenCV provides a very simple interface to this. Let’s capture a video from the camera (I am using the in-built webcam of my laptop), convert it into grayscale video and display it. Just a simple task to get started.
To capture a video, you need to create a VideoCapture object. Its argument can be either the device index or the name of a video file. Device index is just the number to specify which camera. Normally one camera will be connected (as in my case). So I simply pass 0 (or -1). You can select the second camera by passing 1 and so on. After that, you can capture frame-by-frame. But at the end, don’t forget to release the capture.
import numpy as np import cv2 cap = cv2.VideoCapture(0) while(True): # Capture frame-by-frame ret, frame = cap.read() # Our operations on the frame come here gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # Display the resulting frame cv2.imshow('frame',gray) if cv2.waitKey(1) & 0xFF == ord('q'): break # When everything done, release the capture cap.release() cv2.destroyAllWindows()
cap.read() returns a bool (True/False). If frame is read correctly, it will be True. So you can check end of the video by checking this return value.
Sometimes, cap may not have initialized the capture. In that case, this code shows error. You can check whether it is initialized or not by the method cap.isOpened(). If it is True, OK. Otherwise open it using cap.open().
You can also access some of the features of this video using cap.get(propId) method where propId is a number from 0 to 18. Each number denotes a property of the video (if it is applicable to that video) and full details can be seen here: Property Identifier. Some of these values can be modified using cap.set(propId, value). Value is the new value you want.
For example, I can check the frame width and height by cap.get(3) and cap.get(4). It gives me 640x480 by default. But I want to modify it to 320x240. Just use ret = cap.set(3,320) and ret = cap.set(4,240).
If you are getting error, make sure camera is working fine using any other camera application (like Cheese in Linux).
It is same as capturing from Camera, just change camera index with video file name. Also while displaying the frame, use appropriate time for cv2.waitKey(). If it is too less, video will be very fast and if it is too high, video will be slow (Well, that is how you can display videos in slow motion). 25 milliseconds will be OK in normal cases.
import numpy as np import cv2 cap = cv2.VideoCapture('vtest.avi') while(cap.isOpened()): ret, frame = cap.read() gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) cv2.imshow('frame',gray) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()
Make sure proper versions of ffmpeg or gstreamer is installed. Sometimes, it is a headache to work with Video Capture mostly due to wrong installation of ffmpeg/gstreamer.
So we capture a video, process it frame-by-frame and we want to save that video. For images, it is very simple, just use cv2.imwrite(). Here a little more work is required.
This time we create a VideoWriter object. We should specify the output file name (eg: output.avi). Then we should specify the FourCC code (details in next paragraph). Then number of frames per second (fps) and frame size should be passed. And last one is isColor flag. If it is True, encoder expect color frame, otherwise it works with grayscale frame.
FourCC is a 4-byte code used to specify the video codec. The list of available codes can be found in fourcc.org. It is platform dependent. Following codecs works fine for me.
FourCC code is passed as cv2.VideoWriter_fourcc('M','J','P','G') or cv2.VideoWriter_fourcc(*'MJPG) for MJPG.
Below code capture from a Camera, flip every frame in vertical direction and saves it.
import numpy as np import cv2 cap = cv2.VideoCapture(0) # Define the codec and create VideoWriter object fourcc = cv2.VideoWriter_fourcc(*'XVID') out = cv2.VideoWriter('output.avi',fourcc, 20.0, (640,480)) while(cap.isOpened()): ret, frame = cap.read() if ret==True: frame = cv2.flip(frame,0) # write the flipped frame out.write(frame) cv2.imshow('frame',frame) if cv2.waitKey(1) & 0xFF == ord('q'): break else: break # Release everything if job is finished cap.release() out.release() cv2.destroyAllWindows()