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Product Browse Node Classification

A machine learning solution for extracting key entity values (weight, volume, dimensions) from product images.

submission for Amazon ML challenge'23

The repo consists of Amazon ML challenge 2024, It is about detecting specific text (specific features) from image based dataset. It is a combination of OCR+NLP, then Naive Bayes classification is done.

This repo contains the winning code for Amazon ML Challenge 2024. The challenge was to develop a Machine Learning model to extract product entity details directly from the product images.

Image-entity-extractor is an OCR based model for extraction of information given entity type from product images

Utilizes PaddleOCR and advanced image pre-processing techniques to extract product attributes from images.

This is our submission to the amazon ML challange to the final round

Utilizes PaddleOCR and advanced image pre-processing techniques to extract product attributes from images.

Built a smart OCR pipeline using EasyOCR, PyTesseract, and OpenCV to extract key product information (name, dimensions, specifications) directly from raw product images enabling structured data generation for unstructured visual content. Designed for scalability and real-world application in catalog automation and inventory intelligence.

Utilizes PaddleOCR and advanced image pre-processing techniques to extract product attributes from images.

Final Submission of Team DBkaScam for Amazon ML Challenge 2024 (Rank 6)