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Update README.md #19

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Expand Up @@ -14,7 +14,7 @@ ambiguity and a long-tailed distribution"***.

In order to train a model on the PlantNet-300K dataset, you first have to [download the dataset on Zenodo](https://zenodo.org/record/5645731#.Yuehg3ZBxPY).

## Scientific Publication
## Scientific publication

You can find detailed information about the dataset as well as extensive experiments in the [NeurIPS 2021 paper](https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/file/7e7757b1e12abcb736ab9a754ffb617a-Paper-round2.pdf).
If you use this work for your research, please cite the paper:
Expand Down Expand Up @@ -46,7 +46,7 @@ The images are split into a train, val and test set, each containing the followi

</div>

### Dataset Version & Meta-data files
### Dataset, versions & meta-data

Make sure you download the latest version of the dataset in Zenodo (version 1.1 as in the link above, not 1.0).
The difference lies in the metadata files, the images are the same.
Expand Down Expand Up @@ -78,7 +78,8 @@ model = resnet18(num_classes=1081) # 1081 classes in Pl@ntNet-300K
load_model(model, filename=filename, use_gpu=use_gpu)
```

Note that if you want to fine-tune the model on another dataset, you have to change the last layer. You can find examples in the `get_model` function in `utils.py.
Note that if you want to fine-tune the model on another dataset, you have to change the last layer. You can find examples in the `get_model` function in `utils.py`.

### Requirements

Only pytorch, torchvision are necessary for the code to run.
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