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sehaba95/
ResNet-152-DocFigure

pytorch

image-classification

mit

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📊 ResNet_152_DocFig : Paper Figure Classification Using ResNet-152 and DocFigure

Dataset for Scientific Document Figure Classification

This project implements a deep learning model using ResNet-152 to classify figures from scientific documents, leveraging the DocFigure dataset. The goal is to accurately categorize figures (e.g., Line graph, Natural image, Table, 3D object) from academic papers to assist in document understanding and search.

🔧 Technologies Used

Python: 3.11
PyTorch: 2.7.0
TorchVision: 0.22.0

📦 Features

Custom dataset loader for DocFigure
Pretrained ResNet-152 architecture fine-tuned on DocFigure dataset

🚀 Getting Started

Here is an example on how to use ResNet_152_DocFig model

python

from X import ResNet_152_DocFig

# Load the model
model = ResNet_152_DocFig()

# Load the image 
image = Image.open("image.png").convert('RGB')

# Get Predicted Label 
pred_label = model(image)
print(f"Predicted Label: {pred_label}")

👥 Author

This project is developed and maintained by Sehaba95.

sehaba95/ResNet-152-DocFigure