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import json
import pickle
import os
from tqdm import tqdm
def build_referring_dataset(instance_path, refs_path, split, save_path):
assert os.path.exists(instance_path), f'Path not found: {instance_path}'
assert os.path.exists(refs_path), f'Path not found: {refs_path}'
with open(instance_path) as f:
instance = json.load(f)
with open(refs_path, 'rb') as f:
refs = pickle.load(f)
images = instance['images']
annotations = instance['annotations']
img_id2info = {}
for image in images:
img_id2info[image['id']] = image
anno_id2info = {}
for annotation in annotations:
anno_id2info[annotation['id']] = annotation
outputs = []
new_img_id = 0
for sample in tqdm(refs):
if sample['split'] != split:
continue
sample_annotation = anno_id2info[sample['ann_id']]
sample_image = img_id2info[sample['image_id']]
outputs.append(
{
'image': sample_image['file_name'],
'image_info': sample_image,
'instruction': sample['sentences'],
'anns': [sample_annotation],
'new_img_id': new_img_id,
}
)
new_img_id += 1
with open(save_path, 'w') as f:
json.dump(outputs, f)
print(f'Saving at {save_path}. Total sample: {len(outputs)}.')
if __name__ == '__main__':
# Change root path to your own directory
root_path = 'datasets/refer_seg'
datasets = ['refcoco', 'refcoco+', 'refcocog']
splits = ['train', 'val', 'testA', 'testB']
for dataset in datasets:
if dataset == 'refcocog':
splits = ['train', 'val', 'test']
for split in splits:
instance_path = os.path.join(root_path, f'{dataset}', 'instances.json')
if dataset == 'refcocog':
refs_name = 'refs(umd).p'
else:
refs_name = 'refs(unc).p'
refs_path = os.path.join(root_path, f'{dataset}', refs_name)
save_path = os.path.join(root_path, f'{dataset}', f'{split}_psalm.json')
print(f'Processing {dataset}: {split}...')
build_referring_dataset(instance_path, refs_path, split, save_path)
print(f'Done')
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