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import json |
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import os |
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from natsort import natsorted |
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import cv2 |
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import argparse |
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arg_parser = argparse.ArgumentParser(description="Process some integers.") |
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arg_parser.add_argument("--exoego", action='store_true', help="Use exoego dataset") |
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arg_parser.add_argument("--start_id", type=str, default="0", help="Take ID to start with") |
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args = arg_parser.parse_args() |
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take_id = "3c744ca5-c64a-4de3-8235-c2f542ac5056" |
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if not args.exoego: |
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json_path = "/scratch/yuqian_fu/egoexo_val_framelevel_newprompt_all_instruction.json" |
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else: |
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json_path = "/scratch/yuqian_fu/ExoQuery_val_newprompt_all_instruction.json" |
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with open(json_path, 'r') as f: |
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datas = json.load(f) |
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data_list = [] |
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for data in datas: |
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if data['video_name'] == take_id: |
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data_list.append(data) |
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for data in data_list: |
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if data['image'].split("/")[-1] == args.start_id + ".jpg": |
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first_image = data |
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break |
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print("first_image:", first_image["first_frame_image"]) |
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new_img_id = 0 |
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data_save = [] |
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root_path = "/scratch/yuqian_fu/data_imgs" |
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image_path = "/scratch/yuqian_fu/data_imgs/3c744ca5-c64a-4de3-8235-c2f542ac5056/cam03" |
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target_images = natsorted(os.listdir(image_path)) |
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for image in target_images: |
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sample_img_path = os.path.join(image_path, image) |
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sample_img_relpath = os.path.relpath(sample_img_path, root_path) |
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img_target = cv2.imread(sample_img_path) |
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height, width = img_target.shape[:2] |
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image_info = { |
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'file_name': sample_img_relpath, |
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'height': height, |
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'width': width, |
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} |
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sample = { |
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'image': sample_img_relpath, |
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'image_info': image_info, |
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'anns': first_image['anns'], |
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'first_frame_image': first_image['first_frame_image'], |
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'first_frame_anns': first_image['first_frame_anns'], |
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'new_img_id': new_img_id, |
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'video_name': first_image['video_name'], |
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'instruction': first_image['instruction'], |
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} |
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data_save.append(sample) |
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new_img_id += 1 |
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output_json_path = "/scratch/yuqian_fu/iccv_kitchen_ego_firstframe.json" |
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with open(output_json_path, 'w') as f: |
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json.dump(data_save, f) |