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")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("markus-42/SegFly-Firefly", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download Firefly_Thermal/preprocessor_config.json from markus-42/SegFly-Firefly: direct link, hf CLI and curl.
- Browser
- Download file 425 Bytes
-
https://huggingface.co/markus-42/SegFly-Firefly/resolve/main/Firefly_Thermal/preprocessor_config.json
- Command line
-
hf download hf://markus-42/SegFly-Firefly/Firefly_Thermal/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/markus-42/SegFly-Firefly/resolve/main/Firefly_Thermal/preprocessor_config.json
425 Bytes
| { | |
| "processor_class": "SegformerImageProcessor", | |
| "do_normalize": true, | |
| "do_reduce_labels": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.3990, | |
| 0.3990, | |
| 0.3990 | |
| ], | |
| "image_processor_type": "SegformerImageProcessor", | |
| "image_std": [ | |
| 0.2009, | |
| 0.2009, | |
| 0.2009 | |
| ], | |
| "resample": 0, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 640, | |
| "width": 640 | |
| } | |
| } | |