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:
- Caries
- Crown
- Filling
- Implant
- Missing-tooth-between
- Periapical-lesion
- Root Piece
- 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
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model has no library tag.