Image Feature Extraction
Transformers
Safetensors
dinov2
thermal-imaging
computer-vision
knowledge-distillation
robotics
multi-modal
Instructions to use theairlabcmu/AnyThermal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use theairlabcmu/AnyThermal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="theairlabcmu/AnyThermal")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("theairlabcmu/AnyThermal") model = AutoModel.from_pretrained("theairlabcmu/AnyThermal", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "crop_size": { | |
| "height": 224, | |
| "width": 224 | |
| }, | |
| "do_center_crop": false, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_processor_type": "CustomDinov2Processor", | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "shortest_edge": 14 | |
| }, | |
| "auto_map": { | |
| "AutoImageProcessor": "custom_processor.CustomDinov2Processor" | |
| } | |
| } |