🏙️ BLIP Image Captioning for Municipality Use (Graduation Project)

This is a fine-tuned version of Salesforce's BLIP base model, customized for generating captions on images related to street infrastructure and urban environments.
The model was developed as part of a Graduation Project at the College of Information Systems.

🎓 Graduation Project Information

Project Title: Smart Captioning for Urban Monitoring Using AI
Student Name: Saja
University Major: Information Systems
Semester: Final Year – Graduation Project 1
Purpose: This model aims to assist municipalities in automatically generating descriptive captions for street and infrastructure images using AI.

🧠 Model Overview

Base Model: Salesforce/blip-image-captioning-base
Architecture: BLIP (Bootstrapped Language Image Pretraining)
Task: Image Captioning (with a focus on municipality-related data)

🏙️ Dataset

This model was fine-tuned on a custom dataset consisting of images captured in urban environments (e.g., roads, signs, sidewalks) for the purpose of city infrastructure monitoring.

⚠️ The dataset is not publicly released due to privacy and data ownership considerations.

✅ Intended Use

This model is designed for:

Generating captions for street-level and city infrastructure images.
Assisting municipalities in monitoring, analyzing, and documenting visual data.

❌ Limitations

May not generalize well to domains outside of urban/street imagery.
Captions might be biased by the dataset or lack context in unfamiliar scenes.
Does not include object detection – focuses on captioning only.

📜 License

This model is released under the MIT License.
It is based on the Salesforce BLIP model, which is licensed under the BSD-3-Clause License.
Please ensure appropriate credit is given to the original authors when using or redistributing this model.

🤝 Acknowledgements

Special thanks to Salesforce Research for the original BLIP model.
Developed as part of a university graduation project with guidance from faculty members.

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