Precise Descriptions with DAM's Focal Prompting Technology
Traditional image annotation tools often fail to take into account both global context and local details.Describe Anything solves this problem with the following three-step solution:
- Multiple Annotation Support: Provides four labeling methods: dot/box/graffiti/mask, with mask labeling having the highest accuracy (can be automatically generated by SAM).
- Technology portfolio applications::
- Activate Focal Prompting mode (enabled by default) to automatically optimize prompt words
- Enable Gated Cross-Attention mechanism to avoid irrelevant information interference
- Adjust max_new_tokens=512 to get full description
- Parameter fine-tuning program: When the description doesn't match expectations:
- Reduced temperature ≤ 0.2 Reduced randomness
- Set top_p=0.9 to maintain diversity
- Real-time validation of tweaks using demo_simple.py
Typical application example: When labeling medical images, DAM can generate a professional description of "2.3cm×1.8cm elliptical lesion with burr-like edges and a CT value of about 35HU".
This answer comes from the articleDescribe Anything: Open source tool for generating detailed descriptions of images and video regionsThe
May not be reproduced without permission:AI productivity tools " How to solve the problem that image annotation tools cannot accurately describe local details?
