semvec/pypi-packages huggingface dataset:
video-vit 0.0.4
Paper - Pytorch
License: MIT
Requires Python: >=3.6.1,<4.0.0
Keywords: artificial intelligence,deep learning,optimizers,Prompt Engineering

[![Multi-Modality](agorabanner.png)](https://discord.gg/qUtxnK2NMf)

# Video Vit
Open source implementation of a vision transformer that can understand Videos using max vit as a foundation. This uses max vit as the backbone vit and then packs the video tensor into a 4d tensor which is the input to the maxvit model. Implementing this because the new McVit came out and I need more practice. This is fully ready to train and I believe would perform amazingly.

## Installation
`$ pip install video-vit`

## Usage
```python
import torch
from video_vit.main import VideoViT

# Instantiate the VideoViT model with the specified parameters
model = VideoViT(
    num_classes=10,                 # Number of output classes
    dim=64,                         # Dimension of the token embeddings
    depth=(2, 2, 2),                # Depth of each stage in the model
    dim_head=32,                    # Dimension of the attention head
    window_size=7,                  # Size of the attention window
    mbconv_expansion_rate=4,        # Expansion rate of the Mobile Inverted Bottleneck block
    mbconv_shrinkage_rate=0.25,     # Shrinkage rate of the Mobile Inverted Bottleneck block
    dropout=0.1,                    # Dropout rate
    channels=3,                     # Number of input channels
)

# Create a random tensor with shape (batch_size, channels, frames, height, width)
x = torch.randn(1, 3, 10, 224, 224)

# Perform a forward pass through the model
output = model(x)

# Print the shape of the output tensor
print(output.shape)


```


# License
MIT
image-resize-python-script 1.0.9
A small python script to resize images in a folder
License: MIT
Keywords: image,resize,python,script,png,opencv,numpy

# image-resize-python-script

This repository contains a Python script for batch processing of images (PNG). The script allows you to resize multiple images at once, making it convenient for tasks such as creating thumbnails or resizing images for web applications.

## Usage

1. Clone the repository to your local machine.
2. Install the required dependencies by running `pip install -r requirements.txt`.
3. Place the images you want to resize in the `input` folder.
4. Open a terminal or command prompt and navigate to the project directory.
5. Run the script using the command `python resize_images.py`.
6. The resized images will be saved in the `output` folder.

Feel free to customize the script according to your specific requirements. Happy image resizing!

## License

This project is licensed under the MIT License - see the [MIT LICENSE](https://github.com/mayjoantony/image-resize-python-script/blob/main/LICENSE) file for details.