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import json
from collections import defaultdict
# Function to process the input JSON into desired structure
# Now groups by video_id with a single caption per video and list of frame entries
def process_ego4d_annotations(json_file_path, output_json_path=None):
# Load the JSON data from file
with open(json_file_path, 'r') as f:
data = json.load(f)
# Temporary storage for grouping
grouped = {}
for entry in data:
vid = entry['video_id']
# initialize video entry if not exists
if vid not in grouped:
# store caption once per video
grouped[vid] = {
'caption': entry['caption'],
'frames': []
}
# replace prefix "ego4d-data" with "ego4d" in paths
frame_path = entry['image_path'].replace('robotic_videos', 'robotics').replace('videos',"frames")
mask_path = entry['mask'].replace('robotic_videos', 'robotics')
# append frame-level info
grouped[vid]['frames'].append({
'frame_path': frame_path,
'mask_path': mask_path,
'points': entry['clicked_points']
})
# Optionally save to output JSON file
if output_json_path:
with open(output_json_path, 'w') as outf:
json.dump(grouped, outf, indent=2)
return grouped
# Example usage
if __name__ == '__main__':
input_json = '/share/data/drive_1/heakl/benchmark/annotated/robotics/robotics_annot.json'
output_json = '/share/data/drive_1/heakl/benchmark/annotated/robotics/annotations.json'
grouped_dict = process_ego4d_annotations(input_json, output_json)
# Print nicely for verification
import pprint
pprint.pprint(grouped_dict)
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