---
license: apache-2.0
tags:
- en
- image classification
- fastai
model-index:
- name: flutterby by flobbit
  results:
  - task:
      name: image classification
      type: image-classification
    metrics:
    - name: accuracy
      type: acc
      num_train_epochs: 10
      learning_rate: 0.00363
      value: 77.3
metrics:
- accuracy
pipeline_tag: image-classification
---
    
# FlutterBy ST Swallowtail Butterfly Insect Classification

## Model description

The model is used to classify images into one of the 51 North American swallowtail or cattleheart butterfly species. `resnet50` was used for training.

## Intended uses & limitations
The model was trained on 8577 insect images spread over 51 species. The model is likely biased toward some species being more commonly found in certain habitats.

## Training and evaluation data

The images used in training were obtained from GBIF:
GBIF.org (22 June 2023) GBIF Occurrence Download  https://doi.org/10.15468/dl.bqg8bw

Only the first 400 images of each species (if available) were downloaded. The image set was partially cleaned for quality to remove caterpillars, poor images or butterflies that were too far away for proper ID. After "cleaning", 200 additional images were downloaded for Battus philenor and Battus polydamas (as those species had a very high percentage of caterpillar shots).

The dataset is primarily "in the wild" shots rather than all staged poses, and includes images for which even an expert would not be able to see identifying characteristics (hence the lower overall accuracy).

The image set had 33 species had over 200 images (after cleaning). There is a minimum of 30 pics in a class for the less uncommon species (not enough for accurate training but included for completeness).