This project includes the whole training process. Specifically, I use PyTorch 1.7 VideoIO / Video Datasets Loading API / Video Transform to process the Data. More Details：How to use Video Datasets，Video IO，Video Classification Models，Video Transform in PyTorch
The C3D's paper：Learning Spatiotemporal Features with 3D Convolutional Networks. download
The C3D model's definition code refers to jfzhang95
| Accuracy |
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| -- Still Training Now -- |
- Ubuntu 16.04.7 LTS
- CUDA Version: 10.1
- PyTorch 1.7.1
- torchvision 0.8.2
- numpy 1.19.2
- pillow 8.1.0
- python 3.8.5
- av 8.0.3
- matplotlib 3.3.4
Original Dataset：UCF101
After downloading the UCF101 dataset: UCF101.rar and UCF101TrainTestSplits-RecognitionTask.zip, you should seperately unrar them. Then put it into the directory named data
Project
│--- data
│------ UCF101
│------ UCF101TrainTestSplits-RecognitionTask
│--- other files
Before training, make sure you have a directory named model in the root project to save checkpoint file.
python3 train.py
I recorded some problems and solutions when writing the code. Really so sorry that I only write in Chinese! Here is the Link