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| # Following LVIS dataset | |
| # Copyright (c) Aishwarya Kamath & Nicolas Carion. Licensed under the Apache License 2.0. All Rights Reserved | |
| # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved | |
| import json | |
| import os | |
| import time | |
| from collections import defaultdict | |
| import pdb | |
| import pycocotools.mask as mask_utils | |
| import torchvision | |
| from PIL import Image | |
| import torch | |
| from maskrcnn_benchmark.structures.bounding_box import BoxList | |
| from maskrcnn_benchmark.structures.segmentation_mask import SegmentationMask | |
| from maskrcnn_benchmark.structures.keypoint import PersonKeypoints | |
| from maskrcnn_benchmark.config import cfg | |
| # from .coco import ConvertCocoPolysToMask, make_coco_transforms | |
| from .modulated_coco import ConvertCocoPolysToMask | |
| from .lvis import LVIS, LvisDetectionBase | |
| class PacoDetection(LvisDetectionBase): | |
| def __init__(self, img_folder, ann_file, transforms, return_masks=False, **kwargs): | |
| super(PacoDetection, self).__init__(img_folder, ann_file) | |
| self.ann_file = ann_file | |
| self._transforms = transforms | |
| self.ids = sorted(list(self.lvis.imgs.keys())) | |
| self.id_to_img_map = {k: v for k, v in enumerate(self.ids)} | |
| self.prepare = ConvertCocoPolysToMask(return_masks) | |
| def categories(self): | |
| id2cat = {c["id"]: c for c in self.lvis.dataset["categories"]} | |
| all_cats = sorted(list(id2cat.keys())) | |
| categories = {} | |
| for l in list(all_cats): | |
| categories[l] = id2cat[l]['name'] | |
| return categories | |
| def __getitem__(self, idx): | |
| pdb.set_trace() | |
| img, target = super(PacoDetection, self).__getitem__(idx) | |
| image_id = self.ids[idx] | |
| target = {"image_id": image_id, "annotations": target} | |
| img, target = self.prepare(img, target) | |
| if self._transforms is not None: | |
| img = self._transforms(img) | |
| return img, target, idx | |
| def convert_dict_anno_to_box(self, annos): | |
| pass | |
| def get_raw_image(self, idx): | |
| img, target = super(PacoDetection, self).__getitem__(idx) | |
| return img | |
| def categories(self): | |
| id2cat = {c["id"]: c for c in self.lvis.dataset["categories"]} | |
| all_cats = sorted(list(id2cat.keys())) | |
| categories = {} | |
| for l in list(all_cats): | |
| categories[l] = id2cat[l]['name'] | |
| return categories | |
| def get_img_info(self, index): | |
| img_id = self.id_to_img_map[index] | |
| img_data = self.lvis.imgs[img_id] | |
| return img_data |