Muthukumaran HamedAlemo commited on
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Link to the baseline model repo (#4)

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- Link to the baseline model repo (25f43d21e0b9082d7583d56cae7808971907feb8)


Co-authored-by: Hamed Alemohammad <HamedAlemo@users.noreply.huggingface.co>

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  1. README.md +2 -0
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@@ -64,6 +64,8 @@ The experiment by running the mmseg stack for 80 epochs using the above config l
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  It is important to acknowledge that the CDL (Crop Data Layer) labels employed in this process are known to contain noise and are not entirely precise, thereby influencing the model's performance. Fine-tuning the model with more accurate labels is expected to further enhance its overall effectiveness, leading to improved results.
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  ### Inference
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  The github repo includes an inference script an inference script that allows to run the hls-cdl crop classification model for inference on HLS images. These input have to be geotiff format, including 18 bands for 3 time-step, and each time-step includes the channels described above (Blue, Green, Red, Narrow NIR, SWIR, SWIR 2) in order. There is also a **demo** that leverages the same code **[here](https://huggingface.co/spaces/ibm-nasa-geospatial/Prithvi-100M-multi-temporal-crop-classification-demo)**.
 
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  It is important to acknowledge that the CDL (Crop Data Layer) labels employed in this process are known to contain noise and are not entirely precise, thereby influencing the model's performance. Fine-tuning the model with more accurate labels is expected to further enhance its overall effectiveness, leading to improved results.
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+ ### Baseline
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+ The baseline model along with its results can be accessed [here](https://github.com/ClarkCGA/multi-temporal-crop-classification-baseline).
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  ### Inference
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  The github repo includes an inference script an inference script that allows to run the hls-cdl crop classification model for inference on HLS images. These input have to be geotiff format, including 18 bands for 3 time-step, and each time-step includes the channels described above (Blue, Green, Red, Narrow NIR, SWIR, SWIR 2) in order. There is also a **demo** that leverages the same code **[here](https://huggingface.co/spaces/ibm-nasa-geospatial/Prithvi-100M-multi-temporal-crop-classification-demo)**.