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Python opencv web camera
Often, we have to capture live stream with a camera. OpenCV provides a very simple interface to do this. Let’s capture a video from the camera (I am using the built-in webcam on 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. A 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.
cap.read() returns a bool ( True / False ). If the frame is read correctly, it will be True . So you can check for the end of the video by checking this returned value.
Sometimes, cap may not have initialized the capture. In that case, this code shows an 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). Full details can be seen here: cv::VideoCapture::get(). 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(cv.CAP_PROP_FRAME_WIDTH) and cap.get(cv.CAP_PROP_FRAME_HEIGHT) . It gives me 640×480 by default. But I want to modify it to 320×240. Just use ret = cap.set(cv.CAP_PROP_FRAME_WIDTH,320) and ret = cap.set(cv.CAP_PROP_FRAME_HEIGHT,240) .
Note If you are getting an error, make sure your camera is working fine using any other camera application (like Cheese in Linux).
Playing Video from file
Playing video from file is the same as capturing it from camera, just change the camera index to a video file name. Also while displaying the frame, use appropriate time for cv.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.