Rgb Language Cap
R
Rgb Language Cap
Developed by sadassa17
This is a spatially-aware vision-language model capable of recognizing spatial relationships between objects in images and generating descriptive text.
Downloads 15
Release Time : 1/26/2024
Model Overview
The model is trained on the COCO dataset, combining ViT encoder and GPT2 decoder architectures, specifically designed for generating image descriptions that include object spatial relationships.
Model Features
Spatial Relationship Recognition
Accurately identifies and describes spatial relationships (e.g., left-right, up-down) between objects in images.
Structured Output
Output consistently follows a fixed format: 'Object1' is located 'direction' of 'Object2', facilitating subsequent processing.
Lightweight Deployment
Requires only 4GB GPU memory to run, suitable for resource-constrained environments.
Model Capabilities
Image Understanding
Spatial Relationship Description Generation
Multi-object Relationship Analysis
Use Cases
Assistive Technology
Visual Impairment Assistance
Generates environment descriptions with spatial relationships for visually impaired individuals.
Helps users understand the relative positions of objects.
Content Generation
Automatic Image Annotation
Generates detailed descriptions with spatial relationships for images.
Improves accuracy in image retrieval and classification.
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