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Caption-Anything is a versatile tool combining image segmentation, visual captioning, and ChatGPT, generating tailored captions with diverse controls for user preferences.https://huggingface.co/spaces/TencentARC/Caption-Anythinghttps://huggingface.co/spaces/VIPLab/Caption-Anything
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ttengwang/Caption-Anything
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Caption-Anything is a versatile image processing tool that combines the capabilities ofSegment Anything, Visual Captioning, andChatGPT. Our solution generates descriptive captions for any object within an image, offering a range of language styles to accommodate diverse user preferences. It supports visual controls (mouse click) and language controls (length, sentiment, factuality, and language).
- Visual controls and language controls for text generation
- Chat about selected object for detailed understanding
- Interactive demo
Along the River During the Qingming Festival (清明上河图)
- 2023/04/30: support caption everything in a paragraph
- 2023/04/25: We are delighted to introduceTrack-Anything, an inventive project from our lab that offers a versatile and user-friendly solution for video object tracking and segmentation.
- 2023/04/23: support langchain + VQA, better chatbox performance
- 2023/04/20: add mouse trajectory as visual control (beta)
- 2023/04/13: add Colab Tutorial
- 2023/04/11: Release code
Explore the interactive demo of Caption-Anything, which showcases its powerful capabilities in generating captions for various objects within an image. The demo allows users to control visual aspects by clicking on objects, as well as to adjust textual properties such as length, sentiment, factuality, and language.
# Clone the repository:git clone https://github.com/ttengwang/caption-anything.gitcd caption-anything# Install dependencies (python version >= 3.8.1):pip install -r requirements.txt# Configure the necessary ChatGPT APIsexport OPENAI_API_KEY={Your_Private_Openai_Key}# Run the Caption-Anything gradio demo.python app_langchain.py --segmenter huge --captioner blip2 --port 6086 --clip_filter# requires 13G GPU memory#python app_langchain.py --segmenter base --captioner blip2 # requires 8.5G GPU memory#python app_langchain.py --segmenter base --captioner blip # requires 5.5G GPU memory# (Optional) Use the pre-downloaded SAM checkpointswget https://dl.fbaipublicfiles.com/segment_anything/sam_vit_h_4b8939.pth ./sam_vit_h_4b8939.pthpython app_langchain.py --segmenter huge --captioner blip2 --port 6086 --segmenter_checkpoint ./sam_vit_b_01ec64.pth# requires 11.7G GPU memory
Tested in Windows11 using Nvidia 3070-8G.
# Clone the repository:git clone https://github.com/ttengwang/caption-anything.gitcd caption-anything# Install dependencies:pip install -r requirements.txt# Download the [base SAM checkpoints](https://dl.fbaipublicfiles.com/segment_anything/sam_vit_b_01ec64.pth).Invoke-WebRequest https://dl.fbaipublicfiles.com/segment_anything/sam_vit_b_01ec64.pth -OutFile ./sam_vit_b_01ec64.pth# Configure the necessary ChatGPT APIs$env:OPENAI_API_KEY ='{Your_Private_Openai_Key}'# Run the Caption-Anything gradio demo.python app_langchain.py --captioner blip --port 6086 --segmenter base# better chatbox via langchain + VQApython app_langchain.py --captioner blip --port 6086 --segmenter base --segmenter_checkpoint ./sam_vit_b_01ec64.pth# Use the pre-downloaded SAM checkpointspython app.py --captioner blip --port 6086 --segmenter base
fromcaption_anythingimportCaptionAnything,parse_augmentargs=parse_augment()visual_controls= {"prompt_type":["click"],"input_point":[[500,300], [1000,500]],"input_label":[1,0],# 1/0 for positive/negative points"multimask_output":"True",}language_controls= {"length":"30","sentiment":"natural",# "positive","negative", "natural""imagination":"False",# "True", "False""language":"English"# "Chinese", "Spanish", etc.}model=CaptionAnything(args,openai_api_key)out=model.inference(image_path,visual_controls,language_controls)
If you find this work useful for your research, please cite our github repo:
@article{wang2023caption,title={Caption anything: Interactive image description with diverse multimodal controls},author={Wang, Teng and Zhang, Jinrui and Fei, Junjie and Ge, Yixiao and Zheng, Hao and Tang, Yunlong and Li, Zhe and Gao, Mingqi and Zhao, Shanshan and Shan, Ying and Zheng, Feng},journal={arXiv preprint arXiv:2305.02677},year={2023}}
The project is based onSegment Anything,BLIP/BLIP-2,ChatGPT,Visual ChatGPT,GiT. Thanks for the authors for their efforts.
Our project wouldn't be possible without the contributions of these amazing people! Thank you all for making this project better.
Teng Wang @ Southern University of Science and Technology & HKU & Tencent ARC Lab
Jinrui Zhang @ Southern University of Science and Technology
Junjie Fei @ Xiamen University
Zhe Li @ Southern University of Science and Technology
Yunlong Tang @ Southern University of Science and Technology
Mingqi Gao @ Southern University of Science and Technology & University of Warwick
Hao Zheng @ Southern University of Science and Technology
About
Caption-Anything is a versatile tool combining image segmentation, visual captioning, and ChatGPT, generating tailored captions with diverse controls for user preferences.https://huggingface.co/spaces/TencentARC/Caption-Anythinghttps://huggingface.co/spaces/VIPLab/Caption-Anything