Metadata-Version: 2.4
Name: imagekit2
Version: 0.1.5
Classifier: Programming Language :: Rust
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Summary: A high-performance, Rust-powered image watermarking library. Supports text and logo watermarks, smart contrast, tiling, rotation, and precise positioning.
License: MIT
Requires-Python: >=3.7
Description-Content-Type: text/markdown

# ImageKit2

[![PyPI version](https://img.shields.io/pypi/v/imagekit2.svg)](https://pypi.org/project/imagekit2/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

[**ImageKit2**](https://github.com/hzbd/imagekit2) is a high-performance image watermarking engine built with **Rust**. It is designed for speed, memory safety, and professional typography rendering.

> [!IMPORTANT]
> **Migration Notice:**
> This is the successor to the original [`imagekit`](https://github.com/hzbd/imagekit), featuring a completely rewritten core for superior performance and modern text styling (shadows, alignment, smart contrast).

[中文文档](./README.zh.md)

## ✨ Why ImageKit2?

ImageKit2 is not just a wrapper around an image library; it is a purpose-built engine designed for high-quality watermarking tasks.

*   **🚀 Blazing Fast & Memory Safe**
    Built completely in **Rust**, ImageKit2 offers superior performance and memory safety compared to pure Python solutions (like Pillow), especially when processing large batches or high-resolution images.

*   **🧠 Smart Contrast (Auto Color)**
    Stop worrying about watermarks being invisible on dark or bright backgrounds. Use `color="auto"`, and the engine will calculate the background luminance to automatically switch between black and white text.

*   **🎨 Professional Typography**
    Go beyond simple text drawing. ImageKit2 supports:
    *   **Drop Shadows** for better readability.
    *   **Faux Bold (Stroke)** to make thin fonts stand out.
    *   **Multi-line Alignment** (Left/Center/Right).
    *   **Smart Padding** to prevent text clipping.

*   **🛡️ Production Ready**
    *   **EXIF Correction:** Automatically rotates images based on orientation tags.
    *   **Thread-Safe:** Font loaders and processing pipelines are designed for concurrent environments (e.g., multi-threaded Python web servers).
    *   **Modern Formats:** Full support for **WebP**, **AVIF**, JPEG, and PNG.

*   **🧩 One Core, Three Interfaces**
    Whether you need a **Python SDK** for your app, a **CLI** for your scripts, or a **REST API Server** for your microservices, ImageKit2 has you covered with a unified feature set.

![Demo Watermark](./assets/samples/markus-winkler_processed.webp)

---

## Choose Your Usage Scenario

ImageKit2 adapts to your workflow. Whether you are building a Python app, running batch scripts, or deploying a microservice, pick the method that fits your needs.

### Scenario 1: Python Application Integration
*Best for: Data science pipelines, Django/FastAPI apps, in-memory processing.*

**Installation:**
```bash
pip install imagekit2
```

**Usage Example:**
```python
import imagekit2

# 1. Initialize (Point to your font files for best results)
# The library will search these paths/files for fonts.
wk = imagekit2.Watermarker(["/Library/Fonts/Arial.ttf", "./assets/fonts"])

# 2. Process
with open("input.jpg", "rb") as f:
    img_bytes = f.read()

processed_bytes = wk.process(
    img_bytes,
    text="Clean Watermark",
    position="br",
    padding=20,
    size=32.0,
    color="#FFFFFF",
    opacity=0.9,
    # Tip: Set stroke to 0 for crisp, modern text.
    stroke_width=0,
    # Add depth with shadows
    shadow_x=2,
    shadow_y=2,
    shadow_color="#00000080"
)

# 3. Save
with open("output.png", "wb") as f:
    f.write(processed_bytes)
```

### Scenario 2: Local Batch Processing (CLI)
*Best for: DevOps tasks, shell scripts, processing folders of images.*

**Installation:**
1.  Download the **`imagekit2`** binary for your OS (Windows/Linux/macOS) from the **[GitHub Releases Page](https://github.com/hzbd/imagekit2/releases)**.
2.  (Optional) Add it to your system `PATH` for global access.

**Usage Example:**
```bash
# Assuming the binary is in your current folder
./imagekit2 \
  --input "./input.jpg" \
  --output "./output.jpg" \
  --text "Copyright 2024" \
  --position "center" \
  --size 40 \
  --font "/Library/Fonts/Arial.ttf" \
  --color "#FFFFFF" \
  --shadow-x 2 \
  --shadow-y 2
```

### Scenario 3: HTTP Microservice
*Best for: Cloud deployment, decoupling image processing from main logic.*

**Installation & Start:**
1.  Download the **`imagekit2-server`** binary from the **[GitHub Releases Page](https://github.com/hzbd/imagekit2/releases)**.
2.  Grant execution permissions (Linux/macOS): `chmod +x imagekit2-server`

**Running the Server:**
```bash
# Set font directory (Optional, defaults to ./assets/fonts)
export FONT_DIR="./assets/fonts"

# Start server (Listens on port 3000)
./imagekit2-server
```

**API Contract:**
*   **Endpoint:** `POST /process`
*   **Content-Type:** `multipart/form-data`
*   **Payload:**
    *   `file`: The image file.
    *   `params`: JSON string (e.g., `{"mode": "text", "text": "Hello", "size": 30}`).

**Example (cURL):**
```bash
curl -X POST http://localhost:3000/process \
  -F "file=@input.jpg" \
  -F "params={\"mode\":\"text\",\"text\":\"API Test\",\"position\":\"br\",\"shadow_x\":2}" \
  --output result.jpg
```

---

## Font Configuration (Recommended)

### 1. Default (Latin/English Support)

If your watermark text consists **only of Latin characters** (English, Numbers, Punctuation), you do **not** need to configure a font.

ImageKit2 embeds **Inter Regular** (`Inter_24pt-Regular.ttf`) by default—a high-quality, modern sans-serif font that looks professional out of the box.

### 2. Custom Fonts (Required for CJK / Styling)
You **MUST** provide a custom font file (`.ttf` / `.otf`) in the following cases:
*   **Non-Latin Characters:** If your text contains Chinese, Japanese, Korean (CJK), or other non-Latin characters (the default Inter font does not contain these glyphs).
*   **Specific Styles:** If you need a **Bold**, *Italic*, or Serif look (e.g., `Roboto-Bold.ttf`).

**Where to get fonts?**
*   **[Google Fonts](https://fonts.google.com/)**: A massive collection of free fonts.
    *   *Recommendations:* **Roboto**, **Open Sans**, **Montserrat**, or **Lato**.
    *   *Tip:* Download the `Medium` or `Bold` weights for better visibility on images.

**How to load a custom font:**
*   **Python:** `Watermarker(["/path/to/YourFont-Bold.ttf"])`
*   **CLI:** `--font "/path/to/YourFont-Bold.ttf"`
*   **Server:** Place the file in the `FONT_DIR` folder.

---

## Appendix: Parameter Reference

### 1. Common Parameters (Text & Logo)
| Parameter | Default | Description |
| :--- | :--- | :--- |
| `position` | `br` | `tl`, `tr`, `bl`, `br`, `center`, `tile`, or manual coords. |
| `padding` | `20` | Distance from the edge (pixels). |
| `opacity` | `0.8` | 0.0 to 1.0. |
| `angle` | `0.0` | Rotation angle in degrees. |
| `resize_width` | `None` | Resize input width before processing. |
| `output_format` | `png` | `jpg`, `png`, `webp`, etc. |
| `quality` | `80` | Compression quality (1-100). |

### 2. Text Parameters
| Parameter | Default | Description |
| :--- | :--- | :--- |
| `text` | - | The watermark content. |
| `size` | `24.0` | Font size in pixels. |
| `color` | `#FFFFFF` | Hex color. Use `"auto"` for smart contrast. |
| `align` | `left` | `left`, `center`, `right`. |
| `stroke_width` | `0` | Outline width. **Keep 0 for clean modern style.** |
| `stroke_color` | `#000000` | Outline color. |
| `shadow_x` | `0` | Horizontal shadow offset. |
| `shadow_y` | `0` | Vertical shadow offset. |
| `shadow_color` | `#000000` | Shadow color (supports alpha). |

### 3. Logo Parameters
| Parameter | Default | Description |
| :--- | :--- | :--- |
| `logo` | - | The source image path/bytes. |
| `scale` | `None` | Scale relative to background width (e.g., `0.1` = 10%). |

---

## Development & Contribution

We welcome contributions! Whether it's fixing bugs, adding features, or improving documentation, here's how to set up your environment.

### 1. Prerequisites
*   **Rust**: Install via [rustup.rs](https://rustup.rs/) (Stable channel).
*   **Python**: Version 3.8+ (Required for building bindings).
*   **Maturin**: Required for compiling the Python extension (`pip install maturin`).

### 2. Build the Workspace
This project is organized as a Cargo workspace containing `core`, `cli`, `server`, and `bindings/python`.

```bash
# Clone the repository
git clone https://github.com/hzbd/imagekit2.git
cd imagekit2

# Build Core, CLI, and Server
cargo build --workspace

# Run tests (Core logic)
cargo test --workspace
```

### 3. Developing Python Bindings
To test changes in the Python SDK, you need to build the wheel locally using `maturin`.

```bash
# Navigate to the bindings directory (Optional, or run from root with -m)
# Recommended: Create a virtual environment first
python -m venv .venv
source .venv/bin/activate

# Build and install into the current environment
maturin develop -m bindings/python/Cargo.toml --release
```

### 4. Contribution Workflow
1.  **Fork** the repository on GitHub.
2.  Create a new **Feature Branch** (`git checkout -b feature/amazing-feature`).
3.  Commit your changes.
4.  **Push** to the branch and open a **Pull Request**.

---

## License

This project is licensed under the [MIT License](LICENSE).

