semvec/pypi-packages huggingface dataset:
codexregius 1.0.2
A simple debugging library
Requires Python: >=3.10

<h1 align='center'> Codex </h1>

<a href='https://pypi.org/project/codexregius/'>
<p align = 'center'>A simple debugging library for python.</p></a>


---

### Installation

Install using pip:
```bash
pip install codexregius
```

### Usage

```python
from codex import *
#There are 4 main functions; dblog, error, warning, ok

somevar = someotherfunc()
dblog(somevar)
#logs to stdout...
```

---

## Authors <a name = "authors"></a>
[![Foo](https://img.shields.io/badge/Made_with_❤️_by-@stealthypanda🐼-orange?style=for-the-badge&logo=python&link=)](https://sites.google.com/iitj.ac.in/stealthypanda/home)
vnhtr 0.1.8
Encoder-Decoder base for Vietnamese handwriting recognition
Requires Python: >=3.6
Keywords: ocr,vnocr,htr,vnhtr

# Vietnamese Handwriting Text Recognition (aka vnhtr package)

This project deploys and improves two foundational models within [TrOCR](https://huggingface.co/docs/transformers/model_doc/trocr) and [VietOCR](https://github.com/pbcquoc/vietocr).

## Proposal Architecture
### VGG Transformer with Rethinking Head
![VGG Transformer with Rethinking Head](https://github.com/nguyenhoanganh2002/vnhtr/assets/79850337/82876cdd-b84a-47da-9339-6362bd0400d1)
### TrOCR with Rethinking Head
![TrOCR with Rethinking Head](https://github.com/nguyenhoanganh2002/vnhtr/assets/79850337/9295c94f-5059-4a03-a3f3-950e0ab92e30)
## Usage
### `vnhtr` package
```bash
pip install vnhtr
```
```python
from PIL import Image
from vnhtr.vnhtr_script.tools import *

vta_predictor = VGGTransformer("cuda:0")
tra_predictor = TrOCR("cuda:0")

vta_predictor.predict([Image.open("/content/out_sample_2.jpg")])
tra_predictor.predict([Image.open("/content/out_sample_2.jpg")])
```
### Fully implemented
```bash
git clone https://github.com/nguyenhoanganh2002/vnhtr
cd ./vnhtr/vnhtr/source
pip install -r requirements.txt
```
* Pretrain/Fintune VGG Transformer/TrOCR (pretraining on a large dataset and then finetuning on a wild dataset) 
```bash
python VGGTransformer/train.py
python VisionEncoderDecoder/train.py
```
* Pretrain VGG Transformer/TrOCR with Rethinking Head (large dataset)
```bash
python VGGTransformer/adapter_trainer.py
python VisionEncoderDecoder/adapter_trainer.py
```
* Finetune VGG Transformer with Rethinking Head (wild dataset)
```bash
python VGGTransformer/finetune.py
python VisionEncoderDecoder/finetune.py
```
* Access the model without going through the training or finetuning phases.
```python
from VGGTransformer.config import config as vggtransformer_cf
from VGGTransformer.models import VGGTransformer, AdapterVGGTransformer
from VisionEncoderDecoder.config import config as trocr_cf
from VisionEncoderDecoder.model import VNTrOCR, AdapterVNTrOCR

vt_base = VGGTransformer(vggtransformer_cf)
vt_adapter = AdapterVGGTransformer(vggtransformer_cf)
tr_base = VNTrOCR(trocr_cf)
tr_adapter = AdapterVNTrOCR(trocr_cf)
```

For access to the full dataset and pretrained weights, please contact: [anh.nh204511@gmail.com](mailto:anh.nh204511@gmail.com)
WatsonExplorer 2.0.1
Look into the data of your DataFrames with Watson Explorer
Requires Python: >=3.8
Keywords: pandas,polars,explorer,watson

# Watson Explorer

Explore the data in your Pandas DataFrames using Watson Explorer.

## Installation

Use the package manager [pip](https://pypi.org/project/WatsonExplorer/) to install Watson Explorer.

```bash
pip install WatsonExplorer
```

<p align="right">(<a href="#readme-top">back to top</a>)</p>

## Usage

```python
from WatsonExplorer import Explorer

"""Place the following statement at the end of your Python file."""
Explorer()

"""
After running the script, it will extract all the dataframes from the file, delete all old HTML files, create new HTML files, and open a local host to display the DataFrames. 
You can access the DataFrames using the dropdown menu. To stop the local host, click on the 'Stop Server' button, and the tab sheet will automatically close.
"""

"""REMARK:
It is not possible to view data from dataframes that are not linked to variables.
For example:
"""

example_dict = {'A' : [1,2,3,4], 'B' : [5,6,7,8]}

class Example():
    def __init__(self, dictionary=None):
        self.dataframe = pd.DataFrame(example_dict)
    
    def return_df_1(self):
        return self.dataframe
    
    def return_df_2(self):
        self.dataframe2 = self.dataframe.assign(D='Test')
        return self.dataframe2

example = Example(example_dict)
example.return_df_1() # The explorer will not include this dataframe.
example_df = example.return_df_2() # The explorer will include this dataframe.

"""REMARK 2:
This library is not designed to load more than 20,000 rows (yet). We recommend using .head() to reduce the size of your dataframe before using this library.
"""
```
<p align="right">(<a href="#readme-top">back to top</a>)</p>

## Contributing

### General
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. <br>
Please make sure to update tests as appropriate.

<p align="right">(<a href="#readme-top">back to top</a>)</p>

### CSS
Feel free to adjust the CSS file if you don't like the styling.<br>
Also, if you are a very gifted front-end developer, please let me know. I'm open to upgrading the interface.

<p align="right">(<a href="#readme-top">back to top</a>)</p>

## License
Distributed under the MIT License. See `LICENSE.txt` for more information.

<p align="right">(<a href="#readme-top">back to top</a>)</p>

## Contact
Contact: https://heinburgmans.com <br>
Project Link: https://github.com/HeintjeB/watson

<p align="right">(<a href="#readme-top">back to top</a>)</p>

## Acknowledgments
The creation of this explorer was inspired by Spyder's Variable Explorer.
Shout-out to DataTables.net whose code heavily improved this library!

<p align="right">(<a href="#readme-top">back to top</a>)</p>