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