nsitnov/8024-yolov8-model

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library_name: ultralytics tags: - yolo - instance-segmentation - pytorch

YOLOv8 Instance Segmentation Model - Dental X-ray

This is a YOLOv8 instance segmentation model trained for dental X-ray analysis. The model can detect and segment the following classes in X-ray images:

1. Caries
2. Crown
3. Filling
4. Implant
5. Missing-tooth-between
6. Periapical-lesion
7. Root Piece
8. Root-Canal-Treatment

Model Details

• Model Name: YOLOv8 for Dental X-ray Analysis
• Model Type: Instance Segmentation
• Number of Classes: 8
• Classes: Caries, Crown, Filling, Implant, Missing-tooth-between, Periapical-lesion, Root Piece, Root-Canal-Treatment

Usage

Model Details

• Model Type: Instance Segmentation
• Library: Ultralytics (YOLOv8)
• Framework: PyTorch

This model was trained using the YOLOv8 framework provided by the ultralytics library. It is designed for instance segmentation tasks, particularly in the context of dental X-ray images.

Model Framework

This model was trained using the YOLOv8 framework, which is part of the ultralytics library.

• Library: ultralytics
• Framework: PyTorch

Load the Model

You can load the model using the ultralytics package:

from ultralytics import YOLO

# Load the model
model = YOLO("nsitnov/8024-yolov8-model/8024.pt")

# Perform inference on an image
results = model("path/to/your/image.jpg")
results.show()  # Display the results