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README.md
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## Description
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### A very fast reverse image search webapp in streamlit using NVIDIA's EfficientNet and
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Upload a picture, and AI powered by deep learning will instantly show you visually related matches. Explore and discover connections through the magic of image recognition.
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- Explore retrieved images to discover related content.
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- Adjust the number of matches displayed for visual comparisons.
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- Utilizes a pre-trained image feature extractor model (EfficientNet-b0) for accurate image similarity.
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- Employs
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- Offers a user-friendly interface powered by Streamlit.
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## Getting Started
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Streamlit: Framework for building and deploying web apps in Python.
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Torch: Powerful deep learning framework.
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OpenDatasets: Library for convenient dataset downloading.
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NVIDIA EfficientNet-b0: Pre-trained image classification model for feature extraction.
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## Usage
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## Description
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### A very fast reverse image search webapp in streamlit using NVIDIA's EfficientNet and Facebook's Faiss library over approx 70000 images (224x224). (Trains turbo fast (4.30 miuntes) on 4GB GTX1650 GPU)
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Upload a picture, and AI powered by deep learning will instantly show you visually related matches. Explore and discover connections through the magic of image recognition.
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- Explore retrieved images to discover related content.
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- Adjust the number of matches displayed for visual comparisons.
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- Utilizes a pre-trained image feature extractor model (EfficientNet-b0) for accurate image similarity.
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- Employs FAISS index for fast approximate nearest neighbor search.
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- Offers a user-friendly interface powered by Streamlit.
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## Getting Started
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Streamlit: Framework for building and deploying web apps in Python.
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Torch: Powerful deep learning framework.
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OpenDatasets: Library for convenient dataset downloading.
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FAISS: Facebook's fast AI vector similarity search
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NVIDIA EfficientNet-b0: Pre-trained image classification model for feature extraction.
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## Usage
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