| Download the mappings from the Hub and create the id2label and label2id dictionaries: | |
| import json | |
| from huggingface_hub import cached_download, hf_hub_url | |
| repo_id = "huggingface/label-files" | |
| filename = "ade20k-id2label.json" | |
| id2label = json.load(open(cached_download(hf_hub_url(repo_id, filename, repo_type="dataset")), "r")) | |
| id2label = {int(k): v for k, v in id2label.items()} | |
| label2id = {v: k for k, v in id2label.items()} | |
| num_labels = len(id2label) | |
| Custom dataset | |
| You could also create and use your own dataset if you prefer to train with the run_semantic_segmentation.py script instead of a notebook instance. |