BDFreshFish: A Comprehensive Image Dataset for Machine Learning Applications on Bangladeshi Freshwater Fishes

The "BDFreshFish" dataset contains a set of image data for eight different categories of native freshwater fish from various parts of Bangladesh. The eight distinct classes of fish have the following scientific names: Anabas Testudineus, Batasio Tengana, Channa Punctata, Marcrobrachium malcoimsonii, Heteropneustes Fossilis, Mastacembelus Armatus, Ompok Bimaculatus, and Puntius Sophore. Our collection comprises 3100+ images across these eight classes, with 300 augmented images and approximately 100 raw images in each class. The majority of raw images originate from rivers in Bangladesh. The dataset has four primary fish species characteristics: head, body, scales, and fins. Each original image was taken in adequate natural light against the right backdrop. Each image was properly organized into an appropriate folder, allowing different machine learning and deep learning models to make the best use of the images. Utilizing this enormous dataset and various traditional machine learning (TML) and deep learning (DL) techniques, researchers could make significant advancements in analyzing particular fish category classifications to analyze the freshwater environment and fish movement."BDFreshFish"数据集收录了一组图像数据，涵盖孟加拉国不同地区的8类本土淡水鱼类。该数据集包含8个鱼类类别，其对应拉丁学名依次为：Anabas Testudineus、Batasio Tengana、Channa Punctata、Macrobrachium malcoimsonii、Heteropneustes Fossilis、Mastacembelus Armatus、Ompok Bimaculatus以及Puntius Sophore。本数据集共收录8个类别下的3100余幅图像，每类分别包含300幅增强图像与约100幅原始图像，其中绝大多数原始图像拍摄自孟加拉国境内的河流。该数据集涵盖鱼类的四大核心特征：头部、躯干、鳞片与鱼鳍。所有原始图像均在充足自然光下，于适配的背景中拍摄完成。所有图像均已按规范整理至对应文件夹，可支持各类机器学习与深度学习模型充分利用该数据集开展研究。研究人员可借助该大型数据集及各类传统机器学习（Traditional Machine Learning, TML）与深度学习（Deep Learning, DL）技术，在鱼类类别分类分析领域取得显著进展，进而开展淡水生态环境与鱼类活动规律的相关研究。

搜集汇总

背景与挑战

背景概述

BDFreshFish数据集是一个专注于孟加拉国本地淡水鱼类的图像数据集，包含八种不同鱼类的超过3100张图像，每类提供约100张原始图像和300张增强图像，原始图像主要采集自河流环境。数据集强调鱼类的头部、身体、鳞片和鳍等关键特征，图像在自然光下拍摄并组织有序，适用于机器学习和深度学习模型，旨在促进鱼类分类分析和淡水环境研究。