Set Of Mark Save
Effective prompting for Large Multimodal Models like GPT-4 Vision, LLaVA or CogVLM. 🔥
multimodal-maestro
👋 hello
Multimodal-Maestro gives you more control over large multimodal models to get the outputs you want. With more effective prompting tactics, you can get multimodal models to do tasks you didn't know (or think!) were possible. Curious how it works? Try our HF space!
💻 install
⚠️ Our package has been renamed to maestro. Install the package in a
3.11>=Python>=3.8 environment.
pip install maestro
🔌 API
🚧 The project is still under construction. The redesigned API is coming soon.
🧑🍳 prompting cookbooks
| Description | Colab |
|---|---|
| Prompt LMMs with Multimodal Maestro | |
| Manually annotate ONE image and let GPT-4V annotate ALL of them | |
🚀 example
Find dog.
>>> The dog is prominently featured in the center of the image with the label [9].
👉 read more
-
load image
import cv2 image = cv2.imread("...") -
create and refine marks
import maestro generator = maestro.SegmentAnythingMarkGenerator(device='cuda') marks = generator.generate(image=image) marks = maestro.refine_marks(marks=marks) -
visualize marks
mark_visualizer = maestro.MarkVisualizer() marked_image = mark_visualizer.visualize(image=image, marks=marks) -
prompt
prompt = "Find dog." response = maestro.prompt_image(api_key=api_key, image=marked_image, prompt=prompt)>>> "The dog is prominently featured in the center of the image with the label [9]." -
extract related marks
masks = maestro.extract_relevant_masks(text=response, detections=refined_marks)>>> {'6': array([ ... [False, False, False, ..., False, False, False], ... [False, False, False, ..., False, False, False], ... [False, False, False, ..., False, False, False], ... ..., ... [ True, True, True, ..., False, False, False], ... [ True, True, True, ..., False, False, False], ... [ True, True, True, ..., False, False, False]]) ... }
🚧 roadmap
- Rewriting the
maestroAPI. - Update HF space.
- Documentation page.
- Add GroundingDINO prompting strategy.
- CovVLM demo.
- Qwen-VL demo.
💜 acknowledgement
- Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V by Jianwei Yang, Hao Zhang, Feng Li, Xueyan Zou, Chunyuan Li, Jianfeng Gao.
- The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) by Zhengyuan Yang, Linjie Li, Kevin Lin, Jianfeng Wang, Chung-Ching Lin, Zicheng Liu, Lijuan Wang
🦸 contribution
We would love your help in making this repository even better! If you noticed any bug, or if you have any suggestions for improvement, feel free to open an issue or submit a pull request.
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