Update README.md

README.md

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----
-license: apache-2.0
----
+---
+language:
+- en
+- ru
+tags:
+- vision
+- image-classification
+- style-recognition
+- anime
+- danbooru
+- artist-identification
+- few-shot
+- aniworldai
+- onnx
+license: apache-2.0
+base_model: facebook/convnext-tiny-224
+library_name: onnxruntime
+pipeline_tag: image-classification
+---
+
+# 🎨 Author_ID — Anime Artist Style Recognition
+
+<div align="center">
+    <a href="https://aniworldai.org/">
+        <img src="https://img.shields.io/badge/AniWorldAI-Official-blue?style=for-the-badge&logo=web" alt="AniWorldAI Website">
+    </a>
+    <a href="https://t.me/aniworldai">
+        <img src="https://img.shields.io/badge/Telegram-Channel-2CA5E0?style=for-the-badge&logo=telegram" alt="Telegram Channel">
+    </a>
+    <a href="https://t.me/aniworld_bot">
+        <img src="https://img.shields.io/badge/🔥_Full_3000_Authors-Try_in_Bot-orange?style=for-the-badge&logo=telegram" alt="Try Full Version">
+    </a>
+</div>
+
+<br>
+
+## 🇬🇧 English Description
+
+**Author_ID** is an AI model that recognizes the **artistic style** of anime illustrations and identifies the most likely artist from **Danbooru** database.
+
+Think of it as **"Shazam for anime art"** — upload any illustration and instantly discover who drew it or whose style it resembles.
+
+### 🧠 Architecture: Face ID for Art
+
+This model is built using the same architectural principles as **Apple Face ID**:
+
+| Face ID | Author_ID |
+|---------|-----------|
+| Encodes facial features into embedding | Encodes artistic style into embedding |
+| Compares with stored face template | Compares with artist style centroids |
+| Works with one photo enrollment | Works with few-shot artist samples |
+
+The model generates a **512-dimensional style embedding** and compares it against precomputed artist centroids using cosine similarity.
+
+### ⚡ Few-Shot Learning
+
+Unlike traditional classifiers that require thousands of samples per class, Author_ID uses a **metric learning** approach:
+
+- **No retraining needed** to add new artists
+- Just compute centroid from **3-5 sample images**
+- Instantly searchable in the embedding space
+
+### 📦 Model Versions
+
+| Version | Authors | Availability |
+|---------|---------|--------------|
+| **Demo (this repo)** | 500 | Free download |
+| **Full** | 3000+ | [Telegram Bot](https://t.me/aniworld_bot) |
+
+### 🏷️ Output Format
+
+Returns top-5 most similar artists with confidence scores:
+```
+(artist:hiten:0.87), (artist:saitom:0.72), (artist:anmi:0.68), ...
+```
+
+---
+
+## 🇷🇺 Описание на русском
+
+**Author_ID** — это ИИ-модель, которая распознаёт **художественный стиль** аниме-иллюстраций и определяет наиболее вероятного автора из базы **Danbooru**.
+
+Можно сказать, это **"Shazam для аниме-артов"** — загрузите любую картинку и мгновенно узнайте, кто её нарисовал или чей стиль она напоминает.
+
+### 🧠 Архитектура: Face ID для арта
+
+Модель построена по тем же принципам, что и **Apple Face ID**:
+
+| Face ID | Author_ID |
+|---------|-----------|
+| Кодирует черты лица в эмбеддинг | Кодирует стиль рисунка в эмбеддинг |
+| Сравнивает с сохранённым шаблоном | Сравнивает с центроидами авторов |
+| Работает с одним фото при регистрации | Работает с few-shot примерами |
+
+Модель генерирует **512-мерный вектор стиля** и сравнивает его с предрассчитанными центроидами авторов через косинусное сходство.
+
+### ⚡ Few-Shot обучение
+
+В отличие от классических классификаторов, Author_ID использует **metric learning**:
+
+- **Не требует переобучения** для новых авторов
+- Достаточно **3-5 примеров** для создания центроида
+- Мгновенный поиск в пространстве эмбеддингов
+
+### 📦 Версии модели
+
+| Версия | Авторов | Доступность |
+|--------|---------|-------------|
+| **Demo (этот репо)** | 500 | Бесплатно |
+| **Full** | 3000+ | [Telegram Bot](https://t.me/aniworld_bot) |
+
+---
+
+## 🚀 How to Use / Как использовать
+
+### Installation / Установка
+```bash
+pip install onnxruntime onnx pillow numpy
+# or for GPU / или для GPU:
+pip install onnxruntime-gpu onnx pillow numpy
+```
+
+### Inference / Инференс
+
+```python
+import onnxruntime as ort
+import onnx
+import numpy as np
+from PIL import Image
+import json
+
+class AuthorID:
+    """
+    Author_ID: Anime Artist Style Recognition
+    Single ONNX file contains: model + centroids + author names
+    """
+    
+    def __init__(self, onnx_path):
+        # Load metadata (author names embedded in ONNX)
+        model_onnx = onnx.load(onnx_path)
+        self.names = []
+        self.input_size = 384
+        
+        for prop in model_onnx.metadata_props:
+            if prop.key == "author_names":
+                self.names = json.loads(prop.value)
+            elif prop.key == "input_size":
+                self.input_size = int(prop.value)
+        
+        # Create inference session
+        providers = ['CUDAExecutionProvider', 'CPUExecutionProvider']
+        self.session = ort.InferenceSession(onnx_path, providers=providers)
+        
+        # ImageNet normalization
+        self.mean = np.array([0.485, 0.456, 0.406], dtype=np.float32).reshape(1, 3, 1, 1)
+        self.std = np.array([0.229, 0.224, 0.225], dtype=np.float32).reshape(1, 3, 1, 1)
+
+    def preprocess(self, image_path):
+        img = Image.open(image_path)
+        
+        # Handle transparency
+        if img.mode in ('RGBA', 'LA') or (img.mode == 'P' and 'transparency' in img.info):
+            bg = Image.new('RGB', img.size, (255, 255, 255))
+            img = img.convert('RGBA')
+            bg.paste(img, mask=img.split()[3])
+            img = bg
+        else:
+            img = img.convert('RGB')
+        
+        img = img.resize((self.input_size, self.input_size), Image.BILINEAR)
+        
+        img_np = np.array(img, dtype=np.float32) / 255.0
+        img_np = img_np.transpose(2, 0, 1)[np.newaxis, ...]
+        img_np = (img_np - self.mean) / self.std
+        
+        return img_np
+
+    def predict(self, image_path, top_k=5):
+        """Returns list of (author_name, similarity_score)"""
+        img_np = self.preprocess(image_path)
+        top_indices, top_scores = self.session.run(None, {'image': img_np})
+        
+        results = []
+        for idx, score in zip(top_indices[0][:top_k], top_scores[0][:top_k]):
+            results.append((self.names[idx], float(score)))
+        
+        return results
+
+    def predict_tags(self, image_path, top_k=5):
+        """Returns formatted tags: (artist:name:score)"""
+        results = self.predict(image_path, top_k)
+        return [f"(artist:{name}:{score:.2f})" for name, score in results]
+
+
+# === Example Usage ===
+if __name__ == "__main__":
+    # Initialize (once)
+    model = AuthorID("author_id_500.onnx")
+    
+    # Predict
+    results = model.predict("your_image.jpg", top_k=5)
+    
+    print("🎨 Detected artist styles:")
+    for author, score in results:
+        print(f"   {author}: {score:.1%}")
+    
+    # Or get formatted tags
+    tags = model.predict_tags("your_image.jpg")
+    print("\n📝 Tags:", ", ".join(tags))
+```
+
+### Expected Output / Пример вывода
+```
+🎨 Detected artist styles:
+   hiten_(hitenkei): 87.3%
+   saitom: 71.8%
+   anmi: 68.2%
+   kantoku: 65.1%
+   mishima_kurone: 62.4%
+
+📝 Tags: (artist:hiten_(hitenkei):0.87), (artist:saitom:0.72), (artist:anmi:0.68), (artist:kantoku:0.65), (artist:mishima_kurone:0.62)
+```
+
+---
+
+## 📊 Technical Details / Технические детали
+
+| Parameter | Value |
+|-----------|-------|
+| Backbone | ConvNeXt-Tiny |
+| Embedding dim | 512 |
+| Input size | 384×384 |
+| Training data | Danbooru (filtered) |
+| Metric | Cosine similarity |
+| Format | ONNX (opset 17) |
+
+---
+
+## ⚠️ Limitations / Ограничения
+
+- Works best on **anime/manga style** illustrations
+- May confuse artists with very similar styles
+- Confidence drops on **heavily cropped** or **low-quality** images
+- Demo version limited to **500 authors**
+
+---
+
+<div align="center">
+
+## 🔥 Want the full 3000+ artist version?
+
+<a href="https://t.me/aniworld_bot">
+    <img src="https://img.shields.io/badge/Try_Full_Version-Telegram_Bot-2CA5E0?style=for-the-badge&logo=telegram&logoColor=white" alt="Telegram Bot">
+</a>
+
+<br><br>
+
+**More AI Models & News:**
+
+<a href="https://aniworldai.org/">
+    <img src="https://img.shields.io/badge/🌐_AniWorldAI.org-Website-blue?style=flat&logo=google-chrome" alt="Website">
+</a>
+<a href="https://t.me/aniworldai">
+    <img src="https://img.shields.io/badge/📢_Subscribe-Telegram_Channel-2CA5E0?style=flat&logo=telegram" alt="Channel">
+</a>
+<a href="https://huggingface.co/AniWorldAI">
+    <img src="https://img.shields.io/badge/🤗_More_Models-HuggingFace-yellow?style=flat" alt="HuggingFace">
+</a>
+
+</div>