semvec/pypi-packages huggingface dataset:
xhs-fork 0.2.13
xiaohongshu crawl sdk.
License: MIT
Requires Python: >=3.7
Keywords: xhs crawl

<div align="center">

<h1 align="center">
🍰xhs
</h1>

[![PyPI](https://img.shields.io/pypi/v/xhs?label=xhs)](https://pypi.org/project/xhs/)
[![](https://static.pepy.tech/badge/xhs)](https://pepy.tech/project/xhs)
[![](https://img.shields.io/github/license/ReaJason/xhs)](https://github.com/ReaJason/xhs/blob/master/LICENSE)
<br /> [![](https://github.com/ReaJason/xhs/actions/workflows/doc.yml/badge.svg)](https://reajason.github.io/xhs/)
[![](https://github.com/ReaJason/xhs/actions/workflows/test.yml/badge.svg)](https://github.com/ReaJason/xhs/actions/workflows/test.yml)
[![](https://github.com/ReaJason/xhs/actions/workflows/pypi.yml/badge.svg)](https://github.com/ReaJason/xhs/actions/workflows/pypi.yml)

</div>

> **Warning**
>
> The primary purpose of this repository is to practice my Python skills. It is important to note that web crawling may
> be considered illegal, and therefore, it is crucial to refrain from exerting any pressure or engaging in unauthorized
> activities on websites.

**xhs** is a crawling tool designed to extract data from [xiaohongshu website](https://www.xiaohongshu.com/explore)

## Usage

xhs is available on PyPI:

```console
$ python -m pip install xhs
```

if you want the latest version, you can install from git:

```console
$ python -m pip install git+https://github.com/ReaJason/xhs
```

### Basic Usage

> maybe now is more complex, Thanks [@NanmiCoder](https://github.com/NanmiCoder)

Please find in the [document](https://reajason.github.io/xhs/basic)
hieuvision 0.2.0
A modular computer vision toolkit with augmentation and more.
License: MIT
Requires Python: >=3.6


# hieuvision

A modular computer vision toolkit with built-in data augmentation and extensible tools.

---

## 📦 Installation

To install the latest version from PyPI:

```bash
pip install hieuvision
```

This will also install all necessary dependencies:

- `opencv-python`
- `albumentations`
- `tqdm`

---

## 🚀 Usage

### 🧰 Supported Tools

Currently available tool:

- `augment`: Perform brightness and contrast augmentation on image datasets with YOLO-style `.txt` labels.

More tools will be added in future updates.

---

### ✨ Example: Image Augmentation

Assume your dataset is structured like this:

```
dataset/
├── image1.jpg
├── image1.txt
├── image2.jpg
├── image2.txt
...
```

You can apply augmentation using:

```python
from hieuvision import HieuVision
from hieuvision.tools.augmenter import ImageAugmenter

augmenter = ImageAugmenter(
    input_dir="dataset",
    output_dir="dataset_augmented"
)

hv = HieuVision()
hv.add_tool("augment", augmenter)
hv.run_tool("augment")
```

What this does:

- Applies random brightness and contrast adjustments to each image.
- Saves the augmented image in the output directory.
- Copies corresponding YOLO `.txt` label files.
- Logs a warning if any label or image is missing.

---

## 🔧 Developer Guide

### Extend with custom tools

You can register your own tools in `HieuVision`:

```python
class MyCustomTool:
    def run(self):
        print("Running my custom tool")

tool = MyCustomTool()
hv = HieuVision()
hv.add_tool("custom", tool)
hv.run_tool("custom")
```

Each tool must implement a `.run()` method.

---

## 🛠 Requirements

These are installed automatically via `pip install hieuvision`:

- `opencv-python`
- `albumentations`
- `tqdm`

---

## 📁 Project Structure (for developers)

```
hieuvision/
├── hieuvision/
│   ├── __init__.py
│   ├── core.py
│   └── tools/
│       ├── __init__.py
│       └── augmenter.py
├── README.md
├── pyproject.toml
├── LICENSE
└── .github/
    └── workflows/
        └── publish.yml
```

---

## 📝 License

MIT License © 2025 Hieu Nguyen