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StableV2V: Stablizing Shape Consistency in Video-to-Video Editing
Chang Liu, Rui Li, Kaidong Zhang, Yunwei Lan, Dong Liu
[Paper
] / [Project
] / [GitHub
] / [Models (Huggingface)
] / [Models (wisemodel)
] / [DAVIS-Edit (wisemodel)
] / [Models (ModelScope)
] / [DAVIS-Edit (ModelScope)
]
HuggingFace repo of the testing benchmark DAVIS-Edit
proposed in the paper titled "StableV2V: Stablizing Shape Consistency in Video-to-Video Editing".
Data Structure
We follow the same data structure as the one of DAVIS
, as is shown below:
DAVIS-Edit
βββ Annotations <----- Official annotated masks of DAVIS
βββ bear
βββ blackswan
βββ ...
βββ train
βββ JPEGImages <----- Official video frames of DAVIS
βββ bear
βββ blackswan
βββ ...
βββ train
βββ ReferenceImages <----- Annotated reference images for image-based editing on DAVIS-Edit
βββ bear.png
βββ blackswan.png
βββ ...
βββ train.png
βββ .gitattributes
βββ README.md
βββ edited_video_caption_dict_image.json <----- Annotated text descriptions for image-based editing on DAVIS-Edit
βββ edited_video_caption_dict_text.json <----- Annotated text descriptions for text-based editing on DAVIS-Edit
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
:
{
"bear": {
"original": "a bear walking on rocks in a zoo",
"similar": "A panda walking on rocks in a zoo",
"changing": "A rabbit walking on rocks in a zoo"
},
...
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
.
How to use DAVIS-Edit?
We highly recommend you to index different elements in DAVIS-Edit
through the annotation files. Particularly, you may refer to the script below:
import os
import json
from tqdm import tqdm
from PIL import Image
# TODO: Modify the configurations here to your local paths
frame_root = 'JPEGImages'
mask_root = 'Annotations'
reference_image_root = 'ReferenceImages/similar' # Or 'ReferenceImages/changing'
annotation_file_path = 'edited_video_caption_dict_text.json'
# Load the annotation file
with open(annotation_file_path, 'r') as f:
annotations = json.load(f)
# Iterate all data samples in DAVIS-Edit
for video_name in tqdm(annotations.keys()):
# Load text prompts
original_prompt = annotations[video_name]['original']
similar_prompt = annotations[video_name]['similar']
changing_prompt = annotations[video_name]['changing']
# Load reference images
reference_image = Image.open(os.path.join(reference_image_root, video_name + '.png'))
# Load video frames
video_frames = []
for path in sorted(os.listdir(os.path.join(frame_root, video_name))):
if path != 'Thumbs.db' and path != '.DS_store':
video_frames.append(Image.open(os.path.join(frame_root, path)))
# Load masks
masks = []
for path in sorted(os.listdir(os.path.join(mask_root, video_name))):
if path != 'Thumbs.db' and path != '.DS_store':
masks.append(Image.open(os.path.join(frame_root, path)))
# (add further operations that you expect in the lines below)
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