semvec/pypi-packages huggingface dataset:
biogeoloc 0.0.4
A python object package for storing and managing geographic information about biological samples.
Requires Python: >=3.5

# biogeoloc
A python object package for storing and managing geographic information about biological samples

## Installation
```
pip install biogeoloc
```

## Example
1. `Accession`

`Accession` objects are used to store information about a biological sample. This information includes the sample's geographic location, the date it was collected, and any other relevant information.

There are three main information types that can be stored in an `Accession` object:

- `Coordinates`: The geographic location of the sample
- `IDs`: You can store different types of IDs for the sample
- `passport`: Information about the sample, such as the date it was collected, the collector, and any other relevant information
- `phenotypic`: Information about the sample's phenotype
- `dataset`: Information about the dataset the sample belongs to
- `properties`: Any other relevant information about the sample

```python
from biogeoloc import Accession

acc = Accession('u0001', genesys_id='23412', pi_id=['PI628326', 'PI326387'], lib_id='333', latitude=12.345, longitude=23.456, dataset={'reseq': True})
```

2. `AccessionSet`

`AccessionSet` objects are used to store multiple `Accession` objects. This is useful when you have a collection of samples that you want to manage together.

```python
from biogeoloc import AccessionSet

acc1 = Accession('xyx1', lat=1.0, lon=2.0, alt=3.0, lib_id='lib1', pi_id='pi1')
acc2 = Accession('xyx2', lat=1.0, lon=2.0, lib_id='lib2', pi_id_list=['pi2', 'pi3'], is_id_list=['is2', 'is3'])
acc3 = Accession('xyx3', is_id='is3', lib_id='lib3', pi_id='pi3')

AS = AccessionSet('test', '2020-01-01',
                    default_ID_items={'lib_id': str, 'pi_id': list, 'is_id': list})
AS.add(acc1)
AS.add(acc2)
AS.add(acc3)

AS.build_index()

uniq_id = AS.search('lib1', 'lib_id')
acc = AS.get(uniq_id)

print(vars(acc))
```

3. `GeneSys`

`GeneSys` objects are used to parse and store information from the Genesys database. This is useful when you want to access information about a sample from the Genesys database.

Go to [GeneSys Website](https://www.genesys-pgr.org/) to download the accessions data in a zip file. Extract the zip file and use the `GeneSys` object to parse the data.

```python
from biogeoloc import GeneSys

download_genesys_dir = '/path/to/downloaded/genesys/data'
sorghumGS = GeneSys()
sorghumGS.load(download_genesys_dir)
sorghumGS.build_index()

q_id = 'PI207841'
u_id = sorghumGS.search(q_id)
acc = sorghumGS.get(u_id)
```
pro-video-ferramentas-gutierri 1.0
Este pacote irá fornecer ferramentas de processamento de video
Keywords: camera, processamento, video

# Pro video ferramentas

DescriÃ§Ã£o de como o seu pacote funciona... 

Â° Passos para a instalaÃ§Ã£o
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image-caption-editor 0.1.2
An interactive tool for editing image captions using Streamlit.

# Image-Caption-Editor
![image](https://github.com/Capybara-AI/Image-Caption-Editor/assets/11761529/b764fa1a-2878-4fd0-b74b-af93cb51afa5)


The Image Caption Editor, is a powerful tool designed for efficiently editing and managing image captions. Built using Streamlit, it provides a user-friendly interface to streamline the process of annotating images, making it ideal for AI researchers, data scientists, and anyone involved in image-related projects.

## Features
- **Ease of Use**: Intuitive interface for editing captions.
- **Image Navigation**: Easily navigate through images in a dataset.
- **Progress Tracking**: Visual progress bar to track your editing process.
- **Data Compatibility**: Currently supports images stored in a folder and captions in a JSON file. Future versions will support more annotation formats.

## Installation
Install the Image Caption Editor with a simple pip command:

```bash
pip install image-caption-editor
```

## Usage
To launch the application, simply run:

```bash
image-caption-editor
```

Once the application is running:

- Input the path to the JSON file containing the captions. This file should be in the format where each key is the image filename, and the value is the corresponding text caption.
- Input the path to the directory where the images are stored.
Configuration
- Image Directory: Path to the directory containing images.
- Caption JSON File: Path to the JSON file with image captions.
Contributing
- We welcome contributions to enhance the application further. Please consider submitting your suggestions and improvements directly via email to the address provided below.

## License
This project is licensed under the MIT License. See the LICENSE file for more details.

## Author
- Casa AI
- Email: info@delvelabs.ai