I apologize if I explained myself badly.
I meant that to classify the video I need every frame or at least to train a RNN, I use one frame every 5s for example, and I use the other 4 to train an RNN (like LSTM).
My goal is to train an RNN that allows me to classify 6 classes in my dataset composed of 99 videos.
My problem is that I don’t know how to upload videos since I have 99 videos tagged(like label), but all together and not divided into train, test and validation.
I don’t know how to load videos in python and how to divide them into train, validation and test.
I assumed that to classify a video I have to divide it into frames, am I wrong? How would you do it?
Initially I would like to train it using the CPU.
Could you recommend some approach for this project?
Thanks for the answer!!