Instructions to use hf-internal-testing/tiny-random-DetrForSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DetrForSegmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="hf-internal-testing/tiny-random-DetrForSegmentation")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageSegmentation processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-DetrForSegmentation") model = AutoModelForImageSegmentation.from_pretrained("hf-internal-testing/tiny-random-DetrForSegmentation") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_normalize": true, | |
| "do_resize": true, | |
| "feature_extractor_type": "DetrFeatureExtractor", | |
| "format": "coco_detection", | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "max_size": 1333, | |
| "size": 800 | |
| } | |