https://github.com/hobincar/pytorch-video-feature-extractor

A repository for extract CNN features from videos using pytorch
https://github.com/hobincar/pytorch-video-feature-extractor

Last synced: 4 months ago
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A repository for extract CNN features from videos using pytorch

• Host: GitHub
• URL: https://github.com/hobincar/pytorch-video-feature-extractor
• Owner: hobincar
• License: mit
• Created: 2019-04-14T16:28:05.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2022-11-22T04:32:47.000Z (over 1 year ago)
• Last Synced: 2023-03-03T00:52:08.637Z (over 1 year ago)
• Language: Python
• Homepage:
• Size: 3.56 MB
• Stars: 62
• Watchers: 2
• Forks: 19
• Open Issues: 8
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Lists

• awesome-video-feature-extractor - pytorch-video-feature-extractor

README

        
# pytorch-video-feature-extractor

Extract video features from pre-trained CNNs.

## Environment

* Ubuntu 16.04

* CUDA 9.0

* cuDNN 7.3.1

* Nvidia Geforce GTX Titan Xp 12GB

* Python 3.6.8

## Supported CNNs

* AlexNet

* GoogleNet

* VGGNet

* DenseNet

* MobileNet

* ResNet

* ShuffleNet

* SqueezeNet

* InceptionNet (v3 & v4)

## How to use

### Step 1. Install python packages specified in `requirements.txt`

```

$ python -m venv .env

$ source .env/bin/activate

(.env) $ pip install --upgrade pip

(.env) $ pip install -r requirements.txt

```

### Step 2. Prepare videos and put them in to a directory.

For example, for my case

```

|-- datasets

    |-- MSVD

        |-- C9LHk0AJI7U_196_205.avi

        |-- D1tTBncIsm8_248_254.avi

        ...

```

### Step 3. Extract CNN features from videos.

For example, to extract VGG19 features from 'MSVD' dataset,

```

(.env) $ python main.py \

    --video_dpath datasets/MSVD \

    --model vgg19_bn \

    --batch_size 25 \

    --stride 5 \

    --out features/MSVD_VGG19.hdf5

```

, or you can refer to the script files in the `scripts` directory.

## References

* AlexNet: https://github.com/pytorch/vision/blob/master/torchvision/models/alexnet.py

* GoogleNet: https://github.com/pytorch/vision/blob/master/torchvision/models/googlenet.py

* VGGNet: https://github.com/pytorch/vision/blob/master/torchvision/models/vgg.py

* DenseNet: https://github.com/pytorch/vision/blob/master/torchvision/models/densenet.py

* MobileNet: https://github.com/pytorch/vision/blob/master/torchvision/models/mobilenet.py

* ResNet: https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py

* ShuffleNet: https://github.com/pytorch/vision/blob/master/torchvision/models/shufflenetv2.py

* SqueezeNet: https://github.com/pytorch/vision/blob/master/torchvision/models/squeezenet.py

* InceptionNet-v3: https://github.com/pytorch/vision/blob/master/torchvision/models/inception.py

* InceptionNet-v4: https://github.com/Cadene/pretrained-models.pytorch/blob/master/pretrainedmodels/models/inceptionv4.py

## Acknowlegement

I got the codes and pre-trained models from

[pytorch/vision](https://github.com/pytorch/vision), and [Cadene/pretrained-models.pytorch](https://github.com/Cadene/pretrained-models.pytorch).

Many thanks!