Deep learning video exercise classification
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Sir, it is possible by using Matlab's deep learning model. We train through our desired video and later test it with another video. Please guide me on how it is possible.
6 commentaires
Christopher Stapels
le 18 Oct 2022
Ok thanks, I rremoved the ThingSpeak tag to help other users. Good luck with your project.
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Rahul
le 12 Oct 2022
There are variety of application you can do with deep learning. As per your question, the outcome that you want to achieve is not clear. I am assuming you want to classify by giving the video input as training. In supervised classification, I assume you have labeled video that you can use for training. You can extract the frames of a recorded video and then based on the extracted images, you can train your CNN model. Below is the code for how to extract frames from a recorded video file. The variable "all_frames" contains alll the frames present in a video. Use these frames to train your CNN model. The related documentation links are given below:
Once the training is complete, you can use the same code to extract images of a test video and predict your outcome using a trained model. Hope this helps.
P.S.: Use MATLAB R2016a or later.
vidObj = VideoReader('xylophone.mp4');
if contains(vidObj.VideoFormat, 'RGB')
% This is created if the video is of format RGB.
all_frames = zeros( vidObj.Height, vidObj.Width, 3, vidObj.NumFrames, 'uint8' );
else
% This is created if the video is of format grayscale.
all_frames = zeros( vidObj.Height, vidObj.Width, vidObj.NumFrames, 'uint8' );
end
ii = 1;
while( hasFrame( vidObj ) )
frame = readFrame( vidObj );
if length( size( all_frames ) ) == 4
all_frames(:, :, :, ii) = frame;
else
all_frames(:, :, ii) = frame;
end
ii = ii + 1;
end
imshow( all_frames( :, :, :, 1 ) ) % displaying 1st frame
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