| Name | pyvtools JSON |
| Version |
1.2.0
JSON |
| download |
| home_page | None |
| Summary | Python tools |
| upload_time | 2024-10-01 11:00:22 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.11.0 |
| license | MIT License |
| keywords |
deep learning
pytorch
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# PyVTools
General custom tools to work in scientific research using Python
## Getting Started
### Installation
This package can easily be installed using `pip`:
```bash
pip install pyvtools
```
An alternative installation that partially uses Anaconda would involve...
1. First, install some Anaconda distribution, in case you do not have any:
https://docs.anaconda.com/anaconda/install/
2. Then, create an Anaconda environment with Python 3.11.0
```bash
conda create -n dev python=3.11.0
```
3. Activate the environment
```bash
conda activate dev
```
3. Then, install all required packages by running the `install.sh` script:
```bash
yes | . install.sh
```
This will have executed...
```bash
conda install python=3.11.0 numpy<=1.26.4 \
matplotlib conda-forge::opencv scikit-image pillow scikit-learn conda-forge::tifffile
pip install pyvtools
```
5. That's it! You're good to go :)
That second installation procedure is designed to be overly redundant, so please feel free to follow your own installation procedure.
### Requirements
Provided installation steps are only guaranteed to work in Ubuntu 24.04.
In case you are following another installation procedure, this repository requires...
- Python 3.11.0
- Numpy <= 1.26.4
## Additional information
### Main Author Contact
Valeria Pais - @vrpais - valeriarpais@gmail.com
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