https://github.com/gitgoap/amazon-ml-challange24

https://github.com/gitgoap/amazon-ml-challange24

Last synced: about 1 month ago
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• Host: GitHub
• URL: https://github.com/gitgoap/amazon-ml-challange24
• Owner: gitgoap
• Created: 2024-09-15T12:17:46.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-09-16T07:40:11.000Z (5 months ago)
• Last Synced: 2025-01-04T17:43:45.781Z (about 1 month ago)
• Language: Jupyter Notebook
• Size: 4.81 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Support: Supporting Py Scripts/delete_extra_Index.py

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README

        
# Amazon ML Challenge 2024

We participated in Amazon ML Challenge 2024 with a solution for extracting product attributes from images.

## Team Q\*

- **Aman Prakash (Lead)**, NIAMT, Ranchi

- **Sagnik Pramanik**, Heritage Institute of Technology, Kolkata

- **Ankit Rai**, NIAMT, Ranchi

- **Abhinav Sinha**, BIT Mesra, Ranchi

## Problem: Product Attribute Extraction from Images

Our approach uses the **[Moondream Vision Language Model (VLM)](https://github.com/vikhyat/moondream)**, which processes images from the `test.csv` file to extract specific attributes like weight, dimensions, and more.

### Key Highlights:

- **Moondream VLM** (1.6B parameters) was used for lightweight image-to-text processing.

- Extracted key product attributes using targeted prompts.

- Output cleaning and standardization were done using regex for consistency.

  

For more details, refer to the main script: `main_team_qstart_amazonml.ipynb`.