Image Segmentation
Transformers
Safetensors
semantic-segmentation
drone
rgb
thermal
infrared
dinov3
aerial
Instructions to use markus-42/SegFly-Firefly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use markus-42/SegFly-Firefly with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="markus-42/SegFly-Firefly")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("markus-42/SegFly-Firefly", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| __pycache__/ | |
| *.py[cod] | |
| *$py.class | |
| .ipynb_checkpoints/ | |
| .vscode/ | |
| # Weights in output/scratch directories (tracked files in model subfolders use LFS via .gitattributes) | |
| eval_output/**/*.safetensors | |
| eval_output/**/*.pth | |
| eval_output/**/*.bin | |
| eval_output/**/*.ckpt | |
| # Output directories | |
| eval_output/ | |
| infer_output/ | |
| visualizations/ | |
| # Virtual environment | |
| .venv/ | |
| # External Repositories | |
| dinov3/ | |