semvec/pypi-packages huggingface dataset:
image-processing152215 0.0.1
Um pacote simples para processamento de imagens
Requires Python: >=3.8

# image_processing

Description. 
The package image-processing152215 is used to:
	Processing:
		- Histogram matching
		- Structural similarty
		- Resize image
	Utils:
		- Read image
		- Save iamge
		- Plot image
		- Plot result
		- Plot histogram

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install image-processing152215

```bash
pip install image-processing152215
```

## Author
lfrankfrade

## License
[MIT](https://choosealicense.com/licenses/mit/)
aibo-server 0.1.7
aibo: AI partner
Requires Python: >=3.11
Keywords: emacs, aibo

![aibo](https://github.com/dmed256/aibo/assets/1812355/7ccbf83a-621d-4cad-90e3-e3a30e74f73b)

`aibo-server` is the backing Python server for the `aibo.el` Emacs package that leverages OpenAI's chat API to bring ChatGPT into Emacs

[![asciicast](https://asciinema.org/a/612765.svg)](https://asciinema.org/a/612765)

## Installation

This package requires Python 3.11 or greater

```sh
pip install aibo-server
```

## Start server

Normally the server will be run using the `aibo.cli.start` command in emacs

```sh
python -m aibo.cli.start
```

but it's also possible to run it using `uvicorn`

```sh
uvicorn aibo.server.main:app --port 5000
```

## Database

The server uses a simple sqlite database, by default stored in `~/.aibo/database.db`


## Customization

For Python environment customizations, refer to [constants.py](https://github.com/dmed256/aibo/blob/main/python/aibo/common/constants.py).
SRI-Conv 1.2.5
Official package for 'Symmetric Rotation-Invariant Convolutional Kernel'
Requires Python: >=3.8

# Official Pypi Implementation of "SRI-Conv: Symmetric Rotation-Invariant Convolutional Kernel"
*Yuexi Du, Nicha, Dvornek, John Onofrey*

*Yale University*

**This is the official release of SRI_Conv**

version: 1.2.5

### News

- [1.2.0] Gaussian Smooth Kernel is available now!
- [1.1.0] `SRI_Conv1d` and `SRI_Conv3d` are also available now.

### Installation

```bash
pip install SRI-Conv
```


### Requirement:
```bash
"scipy>=1.9.0",
"numpy>=1.22.0",
"torch>=1.8.0"
```

**Note**: Using lower version of torch and numpy should be fine given that we didn't use any new feature in the new torch version, but we do suggest you to follow the required dependencies. If you have to use the different version of torch/numpy, you may also try to install the package from source code at [project repo](https://github.com/XYPB/SRI_Conv).

### Usage
```python
>>> import torch
>>> from SRI_Conv import SRI_Conv2d, sri_resnet18
>>> x = torch.randn(2, 3, 32, 32)
>>> sri_conv = SRI_Conv2d(3, 16, 3)
>>> conv_out = sri_conv(x)
>>> sri_r18 = sri_resnet18()
>>> output = sri_r18(x)
# To reproduce the SRI-ResNet18 used in the paper, use:
>>> sri_r18 = sri_resnet18(ri_conv_size=[9, 9, 5, 5], skip_first_maxpool=True)
```