Update README.md

c5469f5 verified 5 months ago

1.18 kB

---
license: apache-2.0
task_categories:
- image-segmentation
tags:
- yolo
- ultralytics
- comic
- manga
- ocr
---
# YOLO26n-seg for Comic Panels and Text Detection

This model is a fine-tuned version of **YOLO26n-seg** specifically designed for detecting and segmenting **Panels** and **Text Bubbles** in Comics, Manga, and Manhwa.

## 🚀 Usage in ebookcc
This model powers [ebookcc](https://ebookcc.com), an automated tool for create and convert Ebook.

## Predict
![predict](https://cdn-uploads.huggingface.co/production/uploads/67eabd4349483d8622917d4e/EzS3q31K3h9TwJoxtKMNJ.jpeg)
![image](https://cdn-uploads.huggingface.co/production/uploads/67eabd4349483d8622917d4e/Y1F5AiTeXdifYIgSJkJiN.png)

## 📊 Model Details
- **Task**: Instance Segmentation
- **Classes**: 
  - `Panel`: Comic frame borders.
  - `Text`: Speech bubbles and on-page text.
- **Input Size**: 1280px (optimized for high-res scans).

## 🛠 How to use (Ultralytics)
```python
from ultralytics import YOLO
# Load the model
model = YOLO('comic-panels-and-text-detect.safetensors')
# Predict
results = model.predict(source='comic_page.jpg', conf=0.25, imgsz=1280)
# Show results
results[0].show()

	---
	license: apache-2.0
	task_categories:
	- image-segmentation
	tags:
	- yolo
	- ultralytics
	- comic
	- manga
	- ocr
	---

	# YOLO26n-seg for Comic Panels and Text Detection

	This model is a fine-tuned version of YOLO26n-seg specifically designed for detecting and segmenting Panels and Text Bubbles in Comics, Manga, and Manhwa.

	## 🚀 Usage in ebookcc
	This model powers [ebookcc](https://ebookcc.com), an automated tool for create and convert Ebook.

	## Predict
	![predict](https://cdn-uploads.huggingface.co/production/uploads/67eabd4349483d8622917d4e/EzS3q31K3h9TwJoxtKMNJ.jpeg)
	![image](https://cdn-uploads.huggingface.co/production/uploads/67eabd4349483d8622917d4e/Y1F5AiTeXdifYIgSJkJiN.png)

	## 📊 Model Details
	- Task: Instance Segmentation
	- Classes:
	- `Panel`: Comic frame borders.
	- `Text`: Speech bubbles and on-page text.
	- Input Size: 1280px (optimized for high-res scans).

	## 🛠 How to use (Ultralytics)
	```python
	from ultralytics import YOLO

	# Load the model
	model = YOLO('comic-panels-and-text-detect.safetensors')

	# Predict
	results = model.predict(source='comic_page.jpg', conf=0.25, imgsz=1280)

	# Show results
	results[0].show()