Instructions to use dcarpintero/fastai-interstellar-class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastai
How to use dcarpintero/fastai-interstellar-class with fastai:
from huggingface_hub import from_pretrained_fastai learn = from_pretrained_fastai("dcarpintero/fastai-interstellar-class") - Notebooks
- Google Colab
- Kaggle
Astronomical Classifier
Classify images of astronomical objects such as galaxies, nebulae, comets, asteroids, quasars, and star clusters.
Built for the fast.ai Practical Deep Learning Course by:
- creating a custom dataset (less than 150 images per label) using Bing search API;
- augmenting the dataset; and,
- fine tuning ResNet50 (1 + 3 epochs) in paperspace.com.
Try at: https://huggingface.co/spaces/dcarpintero/fastai-interstellar
Two versions of the model are provided:
Class Model
This version fastai-interstellar-class
Classifies an image under an astronomy class:
asteroidcometgalaxynebulaeplanetquasar in spacestar cluster
Accuracy: 84%
Object Model
Available at fastai-interstellar-object
Recognizes a (limited) set of specific astronomical objects:
m31 andromedam33 triangulumm81 bodem82 cigarngc 1300m104 sombrerom51 whirlpoolm42 orion nebulam17 omega nebulam45 pleiades star cluster
Accuracy: 94.1%