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import logging |
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import os |
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from fvcore.common.timer import Timer |
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from detectron2.structures import BoxMode |
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from fvcore.common.file_io import PathManager |
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from detectron2.data import DatasetCatalog, MetadataCatalog |
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from detectron2.data.datasets.lvis import get_lvis_instances_meta |
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logger = logging.getLogger(__name__) |
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__all__ = ["custom_load_lvis_json", "custom_register_lvis_instances"] |
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def custom_register_lvis_instances(name, metadata, json_file, image_root): |
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""" |
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""" |
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DatasetCatalog.register(name, lambda: custom_load_lvis_json( |
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json_file, image_root, name)) |
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MetadataCatalog.get(name).set( |
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json_file=json_file, image_root=image_root, |
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evaluator_type="lvis", **metadata |
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) |
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def custom_load_lvis_json(json_file, image_root, dataset_name=None): |
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''' |
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Modifications: |
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use `file_name` |
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convert neg_category_ids |
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add pos_category_ids |
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''' |
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from lvis import LVIS |
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json_file = PathManager.get_local_path(json_file) |
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timer = Timer() |
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lvis_api = LVIS(json_file) |
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if timer.seconds() > 1: |
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logger.info("Loading {} takes {:.2f} seconds.".format( |
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json_file, timer.seconds())) |
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catid2contid = {x['id']: i for i, x in enumerate( |
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sorted(lvis_api.dataset['categories'], key=lambda x: x['id']))} |
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if len(lvis_api.dataset['categories']) == 1203: |
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for x in lvis_api.dataset['categories']: |
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assert catid2contid[x['id']] == x['id'] - 1 |
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img_ids = sorted(lvis_api.imgs.keys()) |
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imgs = lvis_api.load_imgs(img_ids) |
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anns = [lvis_api.img_ann_map[img_id] for img_id in img_ids] |
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ann_ids = [ann["id"] for anns_per_image in anns for ann in anns_per_image] |
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assert len(set(ann_ids)) == len(ann_ids), \ |
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"Annotation ids in '{}' are not unique".format(json_file) |
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imgs_anns = list(zip(imgs, anns)) |
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logger.info("Loaded {} images in the LVIS v1 format from {}".format( |
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len(imgs_anns), json_file)) |
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dataset_dicts = [] |
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for (img_dict, anno_dict_list) in imgs_anns: |
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record = {} |
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if "file_name" in img_dict: |
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file_name = img_dict["file_name"] |
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if img_dict["file_name"].startswith("COCO"): |
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file_name = file_name[-16:] |
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record["file_name"] = os.path.join(image_root, file_name) |
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elif 'coco_url' in img_dict: |
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file_name = img_dict["coco_url"][30:] |
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record["file_name"] = os.path.join(image_root, file_name) |
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elif 'tar_index' in img_dict: |
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record['tar_index'] = img_dict['tar_index'] |
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record["height"] = img_dict["height"] |
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record["width"] = img_dict["width"] |
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record["not_exhaustive_category_ids"] = img_dict.get( |
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"not_exhaustive_category_ids", []) |
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record["neg_category_ids"] = img_dict.get("neg_category_ids", []) |
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record["neg_category_ids"] = [ |
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catid2contid[x] for x in record["neg_category_ids"]] |
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if 'pos_category_ids' in img_dict: |
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record['pos_category_ids'] = [ |
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catid2contid[x] for x in img_dict.get("pos_category_ids", [])] |
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if 'captions' in img_dict: |
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record['captions'] = img_dict['captions'] |
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if 'caption_features' in img_dict: |
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record['caption_features'] = img_dict['caption_features'] |
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image_id = record["image_id"] = img_dict["id"] |
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objs = [] |
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for anno in anno_dict_list: |
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assert anno["image_id"] == image_id |
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if anno.get('iscrowd', 0) > 0: |
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continue |
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obj = {"bbox": anno["bbox"], "bbox_mode": BoxMode.XYWH_ABS} |
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obj["category_id"] = catid2contid[anno['category_id']] |
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if 'segmentation' in anno: |
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segm = anno["segmentation"] |
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valid_segm = [poly for poly in segm \ |
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if len(poly) % 2 == 0 and len(poly) >= 6] |
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if not len(segm) == len(valid_segm): |
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print('Annotation contains an invalid polygon with < 3 points') |
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assert len(segm) > 0 |
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obj["segmentation"] = segm |
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objs.append(obj) |
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record["annotations"] = objs |
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dataset_dicts.append(record) |
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return dataset_dicts |
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_CUSTOM_SPLITS_LVIS = { |
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"lvis_v1_train+coco": ("coco/", "lvis/lvis_v1_train+coco_mask.json"), |
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"lvis_v1_train_norare": ("coco/", "lvis/lvis_v1_train_norare.json"), |
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} |
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for key, (image_root, json_file) in _CUSTOM_SPLITS_LVIS.items(): |
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custom_register_lvis_instances( |
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key, |
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get_lvis_instances_meta(key), |
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os.path.join("datasets", json_file) if "://" not in json_file else json_file, |
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os.path.join("datasets", image_root), |
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) |
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def get_lvis_22k_meta(): |
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from .lvis_22k_categories import CATEGORIES |
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cat_ids = [k["id"] for k in CATEGORIES] |
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assert min(cat_ids) == 1 and max(cat_ids) == len( |
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cat_ids |
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), "Category ids are not in [1, #categories], as expected" |
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lvis_categories = sorted(CATEGORIES, key=lambda x: x["id"]) |
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thing_classes = [k["name"] for k in lvis_categories] |
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meta = {"thing_classes": thing_classes} |
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return meta |
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_CUSTOM_SPLITS_LVIS_22K = { |
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"lvis_v1_train_22k": ("coco/", "lvis/lvis_v1_train_lvis-22k.json"), |
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} |
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for key, (image_root, json_file) in _CUSTOM_SPLITS_LVIS_22K.items(): |
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custom_register_lvis_instances( |
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key, |
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get_lvis_22k_meta(), |
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os.path.join("datasets", json_file) if "://" not in json_file else json_file, |
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os.path.join("datasets", image_root), |
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) |