Instructions to use kiheh85202/yolo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kiheh85202/yolo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="kiheh85202/yolo")# Load model directly from transformers import AutoImageProcessor, DPTForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("kiheh85202/yolo") model = DPTForSemanticSegmentation.from_pretrained("kiheh85202/yolo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 284 Bytes
2bc54e3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"do_normalize": true,
"do_resize": true,
"ensure_multiple_of": 1,
"feature_extractor_type": "DPTFeatureExtractor",
"image_mean": [
0.5,
0.5,
0.5
],
"image_std": [
0.5,
0.5,
0.5
],
"keep_aspect_ratio": false,
"resample": 2,
"size": 480
} |