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@@ -36,7 +36,7 @@ DAVIS-Edit
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  β”œβ”€β”€ edited_video_caption_dict_image.json <----- Annotated text descriptions for image-based editing on DAVIS-Edit
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  └── edited_video_caption_dict_text.json <----- Annotated text descriptions for text-based editing on DAVIS-Edit
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  ```
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- Specifically, `edited_video_caption_dict_image.json` and `edited_video_caption_dict_text.json` are constructed as Python dictionaries. For example in `edited_video_caption_dict_text.json`:
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  ```json
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  {
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  "bear": {
@@ -46,22 +46,48 @@ Specifically, `edited_video_caption_dict_image.json` and `edited_video_caption_d
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  },
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  ...
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  ```
 
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  # How to use DAVIS-Edit?
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  We highly recommend you to index different elements in `DAVIS-Edit` through the *annotation files*. Particularly, you may refer to the script below:
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  ```python
 
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  import json
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  from tqdm import tqdm
 
 
 
 
 
 
 
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  # Load the annotation file
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- with open('edited_video_caption_dict_text.json', 'r') as f:
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  annotations = json.load(f)
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  # Iterate all data samples in DAVIS-Edit
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  for video_name in tqdm(annotations.keys()):
 
 
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  original_prompt = annotations[video_name]['original']
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  similar_prompt = annotations[video_name]['similar']
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  changing_prompt = annotations[video_name]['changing']
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  # (add further operations that you expect in the lines below)
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  ```
 
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  β”œβ”€β”€ edited_video_caption_dict_image.json <----- Annotated text descriptions for image-based editing on DAVIS-Edit
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  └── edited_video_caption_dict_text.json <----- Annotated text descriptions for text-based editing on DAVIS-Edit
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  ```
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+ Specifically, `edited_video_caption_dict_image.json` and `edited_video_caption_dict_text.json` are constructed as Python dictionary, with its keys as the names of video folders in `JPEGImages`. For example in `edited_video_caption_dict_text.json`:
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  ```json
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  {
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  "bear": {
 
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  },
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  ...
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  ```
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+ The annotations of reference images contain two sub-folders, i.e., `similar` and `changing`, corresponding to the annotations for `DAVIS-Edit-S` and `DAVIS-Edit-C`, respectively, where the structure are constructed in the same folder name as that in `JPEGImages`.
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  # How to use DAVIS-Edit?
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  We highly recommend you to index different elements in `DAVIS-Edit` through the *annotation files*. Particularly, you may refer to the script below:
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  ```python
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+ import os
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  import json
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  from tqdm import tqdm
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+ from PIL import Image
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+
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+ # TODO: Modify the configurations here to your local paths
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+ frame_root = 'JPEGImages'
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+ mask_root = 'Annotations'
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+ reference_image_root = 'ReferenceImages/similar' # Or 'ReferenceImages/changing'
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+ annotation_file_path = 'edited_video_caption_dict_text.json'
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  # Load the annotation file
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+ with open(annotation_file_path, 'r') as f:
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  annotations = json.load(f)
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  # Iterate all data samples in DAVIS-Edit
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  for video_name in tqdm(annotations.keys()):
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+
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+ # Load text prompts
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  original_prompt = annotations[video_name]['original']
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  similar_prompt = annotations[video_name]['similar']
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  changing_prompt = annotations[video_name]['changing']
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+ # Load reference images
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+ reference_image = Image.open(os.path.join(reference_image_root, video_name + '.png'))
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+
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+ # Load video frames
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+ video_frames = []
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+ for path in sorted(os.listdir(os.path.join(frame_root, video_name))):
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+ if path != 'Thumbs.db' and path != '.DS_store':
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+ video_frames.append(Image.open(os.path.join(frame_root, path)))
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+
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+ # Load masks
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+ masks = []
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+ for path in sorted(os.listdir(os.path.join(mask_root, video_name))):
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+ if path != 'Thumbs.db' and path != '.DS_store':
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+ video_frames.append(Image.open(os.path.join(frame_root, path)))
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+
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  # (add further operations that you expect in the lines below)
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  ```