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| # Copyright (c) Facebook, Inc. and its affiliates. | |
| import os | |
| import numpy as np | |
| from detectron2.data import DatasetCatalog, MetadataCatalog | |
| from detectron2.data.datasets import load_sem_seg | |
| from . import openseg_classes | |
| PASCAL_CTX_459_CATEGORIES=openseg_classes.get_pascal_ctx_459_categories_with_prompt_eng() | |
| PASCAL_CTX_459_COLORS = [k["color"] for k in PASCAL_CTX_459_CATEGORIES] | |
| MetadataCatalog.get("openvocab_pascal_ctx459_sem_seg_train").set( | |
| stuff_colors=PASCAL_CTX_459_COLORS[:], | |
| ) | |
| MetadataCatalog.get("openvocab_pascal_ctx459_sem_seg_val").set( | |
| stuff_colors=PASCAL_CTX_459_COLORS[:], | |
| ) | |
| def _get_ctx459_meta(): | |
| # Id 0 is reserved for ignore_label, we change ignore_label for 0 | |
| # to 255 in our pre-processing, so all ids are shifted by 1. | |
| stuff_ids = [k["id"] for k in PASCAL_CTX_459_CATEGORIES] | |
| assert len(stuff_ids) == 459, len(stuff_ids) | |
| # For semantic segmentation, this mapping maps from contiguous stuff id | |
| # (in [0, 91], used in models) to ids in the dataset (used for processing results) | |
| stuff_dataset_id_to_contiguous_id = {k: i for i, k in enumerate(stuff_ids)} | |
| stuff_classes = [k["name"] for k in PASCAL_CTX_459_CATEGORIES] | |
| ret = { | |
| "stuff_dataset_id_to_contiguous_id": stuff_dataset_id_to_contiguous_id, | |
| "stuff_classes": stuff_classes, | |
| } | |
| return ret | |
| def register_all_ctx459(root): | |
| root = os.path.join(root, "pascal_ctx_d2") | |
| meta = _get_ctx459_meta() | |
| for name, dirname in [("train", "training"), ("val", "validation")]: | |
| image_dir = os.path.join(root, "images", dirname) | |
| gt_dir = os.path.join(root, "annotations_ctx459", dirname) | |
| name = f"openvocab_pascal_ctx459_sem_seg_{name}" | |
| DatasetCatalog.register( | |
| name, lambda x=image_dir, y=gt_dir: load_sem_seg(y, x, gt_ext="tif", image_ext="jpg") | |
| ) | |
| MetadataCatalog.get(name).set( | |
| stuff_classes=meta["stuff_classes"][:], | |
| thing_dataset_id_to_contiguous_id={}, # to make Mask2Former happy | |
| stuff_dataset_id_to_contiguous_id=meta["stuff_dataset_id_to_contiguous_id"], | |
| image_root=image_dir, | |
| sem_seg_root=gt_dir, | |
| evaluator_type="sem_seg", | |
| ignore_label=65535, # NOTE: gt is saved in 16-bit TIFF images | |
| gt_ext="tif", | |
| ) | |
| _root = os.getenv("DETECTRON2_DATASETS", "datasets") | |
| register_all_ctx459(_root) |