semvec/pypi-packages huggingface dataset:
dirhashcalc 0.0.1.dev4
Calculate directory hash
Requires Python: >=3.6

# Directory Hash Calculator
This project is a super simple Python library which can be used in both command line and library ways.

To install it:

```shell
$ pip install dirhashcalc
```

### Commandline Usage
To use it in commandline:

```shell
$ dirhashcalc path/to/dir
8907645cfe42941cf7dbc656d59ccc4f02ec2a16493c097e04ce2547ad1e5484
```

You can also pass mlutiple arguments:

```shell
$ dirhashcalc first second
first: 8907645cfe42941cf7dbc656d59ccc4f02ec2a16493c097e04ce2547ad1e5484
second: 9f29e53d60a5a8e92da03e41678374ac584c2c94a24898c0c719736412723c4d
```

Also there are some options that you can use:

```shell
$ dirhashcalc --version # shows version of the tool

# verbose output (prints name of each file when calculating hash of it)
$ dirhashcalc some/dir -v
$ dirhashcalc some/dir --verbose

# super verbose output (prints file names and hash of each one of them)
$ dirhashcalc some/dir -vv
$ dirhashcalc some/dir --super-verbose
```

### Library Usage
You can use this project in your own projects to calculate directory hash.

```python
from dirhashcalc import DirHashCalculator

dir_sha256 = DirHashCalculator('path/to/dir').calc()
```

Class `DirHashCalculator` has more methods. To see them and use it in any other way that you want, see content of `dir_hash.py` in the project and read description of each method in docstring.

### License
This project is licensed under [MIT License](LICENSE).
dataset-convertor 0.0.2
Convert Dataset from one format to another format

﻿<p align="center">
  <a href="https://github.com/codePerfectPlus/dataset-convertor"><img src="https://capsule-render.vercel.app/api?type=rect&color=009ACD&height=100&section=header&text=Dataset%20Convertor&fontSize=90%&fontColor=ffffff" alt="website title image"></a>
  <h2 align="center">👉 Convert object detection dataset format 👈</h2>
</p>

## Dataset types

`PASCAL VOC`: Pascal voc dataset have a xml file for each image.

`YOLO`: YOLO dataset have a txt file for each image.

`COCO`: COCO dataset have a json file for each image.

## Current support format

Currently, the following formats are supported:

|    from    |           to           | implemented |
| :--------: | :--------------------: | ----------- |
| PASCAL VOC |    YOLO(TXT files)     | Yes         |
|    YOLO    | PASCAL VOC (XML files) | Yes         |

## Upcoming support format

|    from    |            to             | Issue/PR(if any) |
| :--------: | :-----------------------: | ---------------- |
| PASCAL VOC |     COCO (JSON files)     | No               |
| PASCAL VOC | TFRecord (TFRecord files) | No               |
|    COCO    |  PASCAL VOC (XML files)   | No               |
|    COCO    |     YOLO (TXT files)      | No               |
|    COCO    | TFRecord (TFRecord files) | No               |
|    YOLO    |     COCO (JSON files)     | No               |
|    YOLO    | TFRecord (TFRecord files) | No               |

## Installation

### Installation from source code

```bash
git clone https://github.com/codePerfectPlus/dataset-convertor/
```

```bash
cd dataset-convertor
python -m venv venv
```

```bash
source venv/bin/activate
pip install requirements.txt
```

### Installation from PyPI

```bash
pip install dataset-convertor
```

## Usage

convert annotations from one format to another format.

dataset formatting example:

    - data/pascal_voc/JPEGImages/*.jpg
    - data/pascal_voc/Annotations/*.xml

    - data/yolo5/JPEGImages/*.jpg
    - data/yolo5/labels/*.txt

### Pascal VOC(xml) to yolo(txt)

```bash
from convert import Convertor

con = Convertor(input_folder='/home/user/data/pascal_voc', output_folder='/home/user/data/yolo5')
con.voc2yolo()
```

### from yolo(txt) to Pascal VOC(xml)

```bash
from convert import Convertor
con = Convertor(input_folder='/home/user/data/yolo5', output_folder='/home/user/data/pascal_voc')
con.yolo2voc()
```


## Contributing

create an issue/PR if any format is missing.Open-source contribution is welcome.check the [contributing guide](/CONTRIBUTING.md) for details.

## Reference

- PASCAL VOC - http://host.robots.ox.ac.uk/pascal/VOC/
- COCO - http://cocodataset.org/
- YOLO9000 - https://arxiv.org/abs/1612.08242
- YOLO4 - https://arxiv.org/abs/2004.10934v1

## License

- [MIT License](/LICENSE)

## Authors

- [CodePerfectPlus](https://github/com/CodePerfectPlus)