Comments (2)
If you don't have multiple gpu's it may be better to finetune a kinetics pre-trained model. A P100 or V100 may be enough for quick finetuning if your sign language dataset is not too big.
Regarding whether the model is the right choice, being a 3d convnet it is a more natural fit for offline processing (it processes the time dimension in parallel, similar to the space dimensions).
If you want to do real time processing you either need to break the incoming video into temporal chunks and pass these through the model, or will have to convert the model graph such that it processes frame by frame but keeps internal state of previous activations (e.g. see https://arxiv.org/abs/1806.03863).
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thank you for the response... I want to know what is the fps for offline processing video or how much time will take it to proccess 2 sec video for example?
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Related Issues (20)
- Optical flow rescaling HOT 5
- How to create a custom action recognition model HOT 2
- Inflating pre-trained models HOT 1
- Trying to create frozen graph, so i can convert it into tflite for android
- Training with different architectures
- customize actions class in the model HOT 1
- offline usage
- rgb.npy and flow.npy HOT 3
- training from scratch HOT 2
- which one is the checkpoint? HOT 5
- The problem of receptive field in I3D paper
- missing videos
- Does the video need to be cropped? HOT 11
- Calculation of TV L1 flow HOT 1
- dependencies issues HOT 1
- Struggling to learn using Opt. Flow HOT 2
- Incompatibility issues
- Run time of I3D on edge decives
- Is there Model File(.pth or .pt) that pretrained with Imagenet+Kinetics?
- I found the pth file which pretrained on Kinetics400 HOT 1
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