Install video reader opencv for mac12/27/2023 Print ('Bad Frames Detected : ', badFrames)Īfter that, the video file played (very slowly) but it seemed to work! The next goal is to create a median background image to make it easier to spot moving objects in the video. Gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) If np.max(frame) is not None: # THIS NEEDS TO BE IMPROVED Gray0 = cv2.cvtColor(frame0, cv2.COLOR_BGR2GRAY) Ret, frame0 = cap.read() # Hopefully, the first frame is not bad! The final code block looks like this: %matplotlib inline For future plotting with matplotlib in Jupyter, I also inserted this at the top. There were also several bad frames with no numbers in the GoPro video file so I inserted a kludgey test of this. This bit of code let Anaconda find the file path: import os First, for reasons I haven’t figured out yet, Anaconda did not find the MP4 file even though it was in the same directory as the Jupyter notebook. There were lots of little things that didn’t work, though. waitKey ( 1 ) & 0xFF = ord ( 'q' ): break cap. VideoCapture ( 'vtest.avi' ) while ( cap. I started with a block of code from OpenCV-Python Tutorial for playing video from a file: import numpy as np import cv2 cap = cv2. I wasted a few minutes when I didn’t realize the file name was GOPR0213.MP4 (with the number 0) and not GOPRO 213.MP4 (with the letter O). I decided to try the test on a 1.5-minute segment of GoPro video that I shot just before the NCAE Day of Action in Raleigh. Instead, in the terminal, following a recommendation from Anaconda documentation, I typed: conda install -c conda-forge opencvĪnd it worked perfectly. Using Anaconda’s built-in Environments manager showed that opencv 4.0.1 was an option, but that installation kept stalling out. After reading a New York Times headline about a similar crowd counting project, I gave it another try. I’ve been wanting to use OpenCV to do automated crowd counting of my protest videos but the last time I started working on this, there were some minor hiccups in the installation process. Rather than abandon this WordPress site and create a new one, I’ve decided to keep it and simply change the nature of the entries…starting now. That research resulted in a paper and a few posters but I haven’t really worked on that stuff since 2015. The below code captures from a camera, flips every frame in the vertical direction, and saves the video.NOTE: Originally, I used this blog exclusively for work related to the analysis of active galaxies. In OSX: MJPG (.mp4), DIVX (.avi), X264 (.mkv).įourCC code is passed as `cv.VideoWriter_fourcc('M','J','P','G') or cv.VideoWriter_fourcc(*'MJPG')` for MJPG.In Windows: DIVX (More to be tested and added).In Fedora: DIVX, XVID, MJPG, X264, WMV1, WMV2.The list of available codes can be found in. If it is True, the encoder expect color frame, otherwise it works with grayscale frame.įourCC is a 4-byte code used to specify the video codec. Then number of frames per second (fps) and frame size should be passed. Then we should specify the FourCC code (details in next paragraph). We should specify the output file name (eg: output.avi). This time we create a VideoWriter object. For images, it is very simple: just use cv.imwrite(). So we capture a video and process it frame-by-frame, and we want to save that video. Sometimes it is a headache to work with video capture, mostly due to wrong installation of ffmpeg/gstreamer. 25 milliseconds will be OK in normal cases.Ĭv.destroyAllWindows() Note Make sure a proper version of ffmpeg or gstreamer is installed. 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). Also while displaying the frame, use appropriate time for cv.waitKey(). Playing video from file is the same as capturing it from camera, just change the camera index to a video file name. Note If you are getting an error, make sure your camera is working fine using any other camera application (like Cheese in Linux). Just use ret = cap.set( cv.CAP_PROP_FRAME_WIDTH,320) and ret = cap.set( cv.CAP_PROP_FRAME_HEIGHT,240). Value is the new value you want.įor 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). Some of these values can be modified using cap.set(propId, value). Full details can be seen here: cv::VideoCapture::get(). Each number denotes a property of the video (if it is applicable to that video). 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. You can check whether it is initialized or not by the method cap.isOpened(). Sometimes, cap may not have initialized the capture. So you can check for the end of the video by checking this returned value. If the frame is read correctly, it will be True. Cap.read() returns a bool ( True/ False).
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