leeboykt/albion-online-fiber-detection

Albion Online Fiber Detection Model

A custom-trained YOLOv8 model for detecting fiber resources (cotton, flax, hemp) in Albion Online. This model is designed for game automation and resource gathering assistance.

Model Details

• Model Type: YOLOv8 (Ultralytics)
• Task: Object Detection
• Training Data: Albion Online Fiber Detection Dataset
• Classes: 10 fiber resource types (cotton, flax, hemp, skyflower, and rarity variants)
• Model Size: 22 MB
• Framework: PyTorch
• Training Images: 12 images
• Validation Images: 3 images

Installation

pip install ultralytics huggingface-hub

Usage

Quick Start - Load from HuggingFace Hub

from ultralytics import YOLO
from huggingface_hub import hf_hub_download

# Download model from HuggingFace
model_path = hf_hub_download(
    repo_id="leeboykt/albion-online-fiber-detection",
    filename="model.pt"
)

# Load the model
model = YOLO(model_path)

# Run inference on an image
results = model.predict('screenshot.jpg')

# Process results
for result in results:
    boxes = result.boxes  # Bounding boxes
    for box in boxes:
        print(f"Class: {box.cls}, Confidence: {box.conf}, Coordinates: {box.xyxy}")

Advanced Usage - Screen Capture Detection

from ultralytics import YOLO
from huggingface_hub import hf_hub_download
import pyautogui
from PIL import Image

# Load model
model_path = hf_hub_download(
    repo_id="leeboykt/albion-online-fiber-detection",
    filename="model.pt"
)
model = YOLO(model_path)

# Capture screen and detect resources
screenshot = pyautogui.screenshot()
results = model.predict(screenshot)

# Get detections
for result in results:
    for box in result.boxes:
        x1, y1, x2, y2 = box.xyxy[0].tolist()
        confidence = box.conf[0].item()
        class_id = int(box.cls[0].item())

        print(f"Detected resource at ({x1}, {y1}) with confidence {confidence:.2f}")

Using with Real-time Detection

from ultralytics import YOLO
from huggingface_hub import hf_hub_download
import cv2

# Load model
model_path = hf_hub_download(
    repo_id="leeboykt/albion-online-fiber-detection",
    filename="model.pt"
)
model = YOLO(model_path)

# Real-time detection with streaming
model.predict(source=0, show=True)  # Use webcam
# or
model.predict(source='video.mp4', show=True)  # Use video file

Model Output

The model returns detection results with:

• Bounding boxes: (x1, y1, x2, y2) coordinates
• Confidence scores: Detection confidence (0-1)
• Class IDs: Resource type identifiers
• Class names: Human-readable resource names

Use Cases

• Automated resource gathering in Albion Online
• Game bot development
• Computer vision research for game automation
• Educational purposes for object detection

Limitations

• Trained specifically for Albion Online graphics
• Performance may vary with different screen resolutions
• May not work well with game UI updates or visual changes
• Intended for educational and research purposes

Citation

If you use this model, please cite:

@misc{albion-fiber-detection,
  author = {leeboykt},
  title = {Albion Online Fiber Detection Model},
  year = {2024},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/leeboykt/albion-online-fiber-detection}}
}

License

This model is released under CC-BY-NC-ND-4.0 license.

Disclaimer

This model is for educational and research purposes only. Use of automation tools may violate the Terms of Service of Albion Online. Use at your own risk.