Instructions to use TheBlindMaster/yolov8n-manga-frame-seg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use TheBlindMaster/yolov8n-manga-frame-seg with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("TheBlindMaster/yolov8n-manga-frame-seg") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
YOLOV8N Manga Frame Segmentation
This model is a fine-tuned YOLOV8N-seg for detecting and segmenting frames in manga images.
Usage
from ultralytics import YOLO
from huggingface_hub import hf_hub_download
# Download and load the model
model_path = hf_hub_download(repo_id="TheBlindMaster/yolov8n-manga-frame-seg", filename="best.pt")
model = YOLO(model_path)
# Run inference
results = model.predict("manga_page.jpg")
Training Details
- Base Model: yolov8n-seg.pt
- Dataset: Manga109 with MangaSegmentation annotations
- Task: Frame instance segmentation
- Epochs: 1
- Image Size: 320
- Batch Size: 16
Categories
Trained to detect: frame
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