Instructions to use chainyo/segformer-sidewalk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chainyo/segformer-sidewalk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="chainyo/segformer-sidewalk")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("chainyo/segformer-sidewalk") model = SegformerForSemanticSegmentation.from_pretrained("chainyo/segformer-sidewalk") - Notebooks
- Google Colab
- Kaggle
add id2label file
Browse files- id2label.json +1 -0
id2label.json
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{"0": "unlabeled", "1": "flat-road", "2": "flat-sidewalk", "3": "flat-crosswalk", "4": "flat-cyclinglane", "5": "flat-parkingdriveway", "6": "flat-railtrack", "7": "flat-curb", "8": "human-person", "9": "human-rider", "10": "vehicle-car", "11": "vehicle-truck", "12": "vehicle-bus", "13": "vehicle-tramtrain", "14": "vehicle-motorcycle", "15": "vehicle-bicycle", "16": "vehicle-caravan", "17": "vehicle-cartrailer", "18": "construction-building", "19": "construction-door", "20": "construction-wall", "21": "construction-fenceguardrail", "22": "construction-bridge", "23": "construction-tunnel", "24": "construction-stairs", "25": "object-pole", "26": "object-trafficsign", "27": "object-trafficlight", "28": "nature-vegetation", "29": "nature-terrain", "30": "sky", "31": "void-ground", "32": "void-dynamic", "33": "void-static", "34": "void-unclear"}
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