https://github.com/plantnet/geolifeclef
GeoLifeCLEF challenge toolkit and starter code
https://github.com/plantnet/geolifeclef
challenge clef deep-learning lifeclef machine-learning species-distribution-modelling
Last synced: about 1 year ago
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GeoLifeCLEF challenge toolkit and starter code
- Host: GitHub
- URL: https://github.com/plantnet/geolifeclef
- Owner: plantnet
- License: mit
- Created: 2018-12-19T08:54:02.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2024-10-15T07:44:01.000Z (over 1 year ago)
- Last Synced: 2025-03-30T21:09:55.409Z (about 1 year ago)
- Topics: challenge, clef, deep-learning, lifeclef, machine-learning, species-distribution-modelling
- Language: Jupyter Notebook
- Homepage:
- Size: 73.9 MB
- Stars: 59
- Watchers: 6
- Forks: 27
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
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README
# GeoLifeCLEF 2023
This repository is related to the GeoLifeCLEF challenge. The details of the challenge, the data, and all other useful information are present on the challenge page: [https://www.kaggle.com/competitions/geolifeclef-2023-lifeclef-2023-x-fgvc10](https://www.kaggle.com/competitions/geolifeclef-2023-lifeclef-2023-x-fgvc10 "GeoLifeClef2023 kaggle page!")
## codes
In this repository you will find dataloaders, sample_data and example to help using the challenge's dataset.
- In ``data/sample_data/`` you will find a small sample of the dataset to try codes and loaders.
- ``example_patch_loading.ipynb`` and ``example_patch_loading.py`` give an example of pytorch dataset creation for CNN tensors taking into account different cases.
- ``example_time_series_loading.ipynb`` and ``example_time_series_loading.py`` give an example of pytorch dataset creation for time series tensors taking into account different cases.
## Environment
We provide a conda environment containing the needed libraries to use this code.
```conda env create -f environment.yml```
```conda activate glc23```