Bengali Fish Images

Bengali Fish Images

Datasets

Bengali Fish Images

File

Bengali Fish Images

Use Case

Computer Vision

Description

I planned to create a fish image recognizer that mostly get sold in bengali fish markets. So, I downloaded the data using duckdukgo search and prepared the data for 20 different types of fishes.

Bengali Fish Images

About Dataset

Context

I planned to create a recognizer that mostly get sold in markets. So, I downloaded the data using duckdukgo search and prepared the data for 20 different types of fishes. After some data cleaning and shifting data to their respective folder, there remains more data in some categories whereas some are less in number. So, It became an imbalanced dataset. Using these I created an interpretable cnn based classifier.

The githube repo containing all workings is available here.
The website integration is available here.

Dataset Containings

fish_images: It contains folders with images from 20 different categories. Such as, Ayre, Catla, Rui, Ilish and many more.
inference_images: It contains 17 different images of fishes for testing purpose.

Acknowledgements

I collected the data using DuckDuckGo search. Add a citation, if you plan to use this data.

Inspiration

This dataset can be used for deep learning workings. For example, performing image classification with different approaches using imbalanced dataset and interpretability of the models.

It showcases the rich variety of fish central to Bengali cuisine. This collection features detailed images of popular species like Hilsa, Rohu, and Pabda, highlighting their unique textures and appearances. Ideal for culinary enthusiasts and researchers, these high-resolution images provide a visual feast that complements the vibrant flavors of Bengali fish dishes. Whether you’re a chef, a food blogger, or a seafood lover, Bengali Fish Images offers a captivating glimpse into the heart of Bengal’s culinary heritage. Dive into the world of Bengali fish and experience the essence of this beloved cuisine.

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