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README.md

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 short_description: Using YOLO to detect comic panels and text
 ---
 
+
+# 🚀 ebookcc - AI Comic Panel & Text Detector (Demo)
+
+Welcome to the AI vision core demo for **ebookcc**! This Space hosts a custom-trained **YOLO26n-seg** instance segmentation model, optimized specifically for comics, manga, manhwa, and standard book layouts.
+
+## 🌟 Live Demo Features
+1. **Panel Detection**: Automatically identifies the boundaries of comic frames, preparing them for reading-flow re-layout.
+2. **Text Bubble Segmentation**: Pinpoints all speech bubbles and on-page text areas precisely, making them ready for seamless AI OCR integration.
+
+## 🛠️ Tech Stack & Background
+This web demo is part of the [ebookcc.com](https://ebookcc.cptd.workers.dev/) project.
+- **Backend Model**: Fine-tuned based on Ultralytics YOLO11m-seg.
+- **Frontend Deployment**: The full Web App runs on the user's browser via TF.js and deeply integrates with Cloudflare Workers to reduce server costs.
+
+## 📝 How to Use This Model Locally
+If you want to call this model in your own Python project, please check out our [Hugging Face Model Card](https://huggingface.co/Oliverdsfdsf/ComicPabelsAndTextDetect).
+
+```python
+from ultralytics import YOLO
+
+# Load the model
+model = YOLO("comic-panels-and-text-detect.pt")
+
+# Predict with optimal manga settings
+results = model.predict("manga_page.jpg", imgsz=1280, conf=0.25)
+results[0].show()
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference