| import sys |
| sys.path.insert(0, '../') |
| from lavis.datasets.data_utils import load_video_demo |
| import json |
| import os.path as osp |
|
|
| def fid2time(vid_dir, res_file, map_file): |
| with open(res_file, 'r') as fp: |
| data = json.load(fp) |
| with open(map_file, 'r') as fp: |
| mapID = json.load(fp) |
| image_size = 224 |
| gqa = {} |
| for cnt, item in enumerate(data): |
| qid = item['qid'] |
| pred = item['prediction'] |
| target = item['target'] |
| frame_index = item['frame_idx'] |
| vid = qid.split('_')[1] |
| qs_id = qid.split('_')[-1] |
| vpath = f'{vid_dir}/{mapID[vid]}.mp4' |
| raw_clip, indice, fps, vlen = load_video_demo( |
| video_path=vpath, |
| n_frms=32, |
| height=image_size, |
| width=image_size, |
| sampling="uniform", |
| clip_proposal=None |
| ) |
| tspan = [] |
| video_len = vlen/fps |
| for i in frame_index: |
| select_i = indice[i] |
| time = round((select_i / vlen) * video_len, 2) |
| tspan.append(time) |
| key_id = vid+'_'+qs_id |
| gqa[key_id] = {'prediction':pred, 'answer':target, 'location':tspan} |
| if cnt % 500 == 0: |
| print(gqa[key_id]) |
| |
| with open(osp.dirname(res_file)+'/test_ground.json', 'w') as fp: |
| json.dump(gqa, fp) |
| |
|
|
| def main(): |
| res_dir = '../../data/sevila/results/nextqa_infer/result/' |
| vid_dir = '/storage/jbxiao/workspace/data/nextqa/videos/' |
| map_file = '../../data/datasets/nextqa/map_vid_vidorID.json' |
| res_file = f'{res_dir}/test_epochbest.json' |
| fid2time(vid_dir, res_file, map_file) |
|
|
| if __name__ == "__main__": |
| main() |
|
|
