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- # Examples
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+ # Performing an inference task with TerraTorch
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+
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+ ## Step 1: Download the test case from HuggingFace
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+ We will use the burn scars identification test case, in which we are interested in estimating the area
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+ affected by wildfires using a finetuned model (Prithvi-EO backbone + CNN decoder). To download the complete
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+ example, do:
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+ ``` sh
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+ git clone https://huggingface.co/ibm-nasa-geospatial/Prithvi-EO-2.0-300M-BurnScars/
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+ ```
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+ ## Step 2: Run the default inference case
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+ The example you download already contains some sample images to be used as input, so you just need to go to
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+ the local repository and create a directory to save the outputs:
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+ ``` sh
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+ cd Prithvi-EO-2.0-300M-BurnScars
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+ mkdir outputs
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+ ```
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+ and to execute a command line like:
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+ ``` sh
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+ terratorch predict -c burn_scars_config.yaml --predict_output_dir outputs/ --data.init_args.predict_data_root examples/ --ckpt_path Prithvi_EO_V2_300M_BurnScars.pt
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+ ```
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+ You will see the outputs being saved in the ` outputs ` directory.
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+
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+ ### Input image (RGB components)
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+
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+ ![ ] ( figs/input.png )
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+
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+ ### Predicted mask
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+
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+ ![ ] ( figs/mask.png ) }
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+
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+ # More examples
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For some examples of training using the existing tasks, check out the following pages on our github repo:
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