Instructions to use vikp/line_detector_math with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vikp/line_detector_math with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForRegressionMask processor = AutoImageProcessor.from_pretrained("vikp/line_detector_math") model = SegformerForRegressionMask.from_pretrained("vikp/line_detector_math", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from vikp/line_detector_math: direct link, hf CLI and curl.
- Browser
- Download file 430 Bytes
-
https://huggingface.co/vikp/line_detector_math/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://vikp/line_detector_math/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/vikp/line_detector_math/resolve/main/preprocessor_config.json
430 Bytes
| { | |
| "do_normalize": true, | |
| "do_reduce_labels": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "SegformerFeatureExtractor", | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_processor_type": "SegformerImageProcessor", | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 1200, | |
| "width": 1200 | |
| } | |
| } | |