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BigEarthNet S2 Vision Models

An experimental repo for classifiying BigEarthNet with Sentinel-2 Image Patches.

Used as a learning resource for building a selection of image models.

I wanted to train locally so all models were trained on a Nvidia 4070 Super.

ViT

ViT model from scratch based on this guide.

Total Parameters: 6,401,811

Metric Value
Precision 0.7254
Recall 0.7819
F1 Score 0.7526
Exact Match Ratio 0.2725
Images per second (Test) 81,546
Training time 8.52 hrs

CNN

A fine tuned CNN based model using ResNet18.

Total Parameters: 10,506,195

Metric Value
Precision 0.7946
Recall 0.6919
F1 Score 0.7397
Exact Match Ratio 0.2881
Images per second (Test) 57,467
Training time 20.46 hrs

ConvNeXt

A fine tuned ConvNeXt model using ConvNeXt

Total Parameters: 46,763,827

Metric Value
Precision 0.7451
Recall 0.7906
F1 Score 0.7672
Exact Match Ratio 0.2949
Images per second (Test) 25,040
Training time 6 hrs

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