![]() (Note: batch conversion is supported, so you can load more than one file to save time.) Step 2. I’m confused about how I can do this, regarding backprop and again, dataloader. Load the recorded videos Run EaseFab Video Converter, after that, simply drag and drop Action recorded AVI or MP4 files to the program.For example if the GPU is capable of processing 5k frames at a time, a 40k frame long network will be started for 8 times, and at the end the prediction will be generated. I thought about feeding a part of the frames and saving the hidden outputs, then restart the network with the hidden outputs as hidden inputs now and a new set of the frames. Any suggestions on how to load this type of datasets into GPU, without having memory and time problems?. ![]() In the custom dataloader function, I read all the preprocessed frames of one video at once, and expectedly, GPU memory cannot handle it and besides, data loading can take a long time. ![]() I am trying to feed every video as one batch (batch_size=1) to a recurrent network for a regression task. Several other improvements accelerate and stabilize your editing process. I have a dataset of multiple videos, consisting of ~40,000 frames. With this update, create multiple smart masks on one image for creative editing, transfer text properties between text events, and dock windows far more easily and intuitively.
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