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Python library for solving computer vision tasks specifically for satellite imagery

Project description

earth-vision

Earth Vision is a python library for solving computer vision tasks specifically for satellite imagery.

Objective

To ease researcher to run ML pipelines for AI or Deep Learning Applications in solving Earth Observation (EO) tasks.

Examples

Dataset Download

from torch.utils.data import DataLoader
from earthvision.datasets import DeepSat

train_dataset = DeepSat(root='./', dataset_type='SAT-4', download=True, data_mode=0)
test_dataset = DeepSat(root='./', dataset_type='SAT-4', download=False, data_mode=1)

train_dataloader = DataLoader(train_dataset, batch_size=64, shuffle=True)
test_dataloader = DataLoader(test_dataset, batch_size=64, shuffle=True)

train_data, train_label = next(iter(train_dataloader))
test_data, test_label = next(iter(test_dataloader))

Features

  1. Wrapper to download open sourced EO dataset for ML tasks:
  • AerialCactus
  • COWC
  • DeepSat
  • DroneDeploy
  • EuroSat
  • L8SPARCS
  • LandCover
  • RESISC45
  • UCMercedLand

Project details


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Source Distribution

earth-vision-0.0.1.tar.gz (23.0 kB view hashes)

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