Name: Butterfly & Moths Image Classification 100 Species
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Butterfly & Moths Image Classification 100 Species

This version corrects issues found in the previous version of the dataset. To see those issues you can look at my notebook at https://www.kaggle.com/code/gpiosenka/dataset-quality-evaluation-tool.
Train, Test. Validation data set for 100 butterfly or moth species. All images are 224 X 224 X 3 in jpg format .
Train set consists of 12594 images partitioned into 100 sub directories one for each species.
Test set consists of 500 images partitioned into 100 sub directories with 5 test images per species.
Valid set consists of 500 images partitioned into 100 sub directories with 5 validation images per species.
A CSV files is included. The butterflies and moths .csv file consists of 4 columns with 13595 rows. The first row is the header, the remaining rows are for each of the image files in the train, test and validation datasets,
The columns are class id, filepaths, labels and data set. The filepaths column contains the relative path to the image.
The labels column contains the text species label associated with the image file. The data set column specifies which
dataset (train, test or valid) the associated image belongs to. The class id column contains the numerical class index for the image file.

Tables

Butterflies And Moths

@kaggle.gpiosenka_butterfly_images40_species.butterflies_and_moths

95.35 KB
13594 rows
4 columns


CREATE TABLE butterflies_and_moths (
  "class_id" BIGINT,
  "filepaths" VARCHAR,
  "labels" VARCHAR,
  "data_set" VARCHAR
);

Training

@kaggle.gpiosenka_butterfly_images40_species.training

6.04 KB
15 rows
7 columns


CREATE TABLE training (
  "epoch" BIGINT,
  "loss" DOUBLE,
  "accuracy" DOUBLE,
  "f1_score" DOUBLE,
  "val_loss" DOUBLE,
  "val_accuracy" DOUBLE,
  "val_f1_score" DOUBLE
);