CaBuAr_Pipeline_predict_post_fire_from_pre_fire_npy – 1 MCP server offers this tool
What it usually takes
file– in 1 of 1guidance_scale– in 1 of 1seed– in 1 of 1steps– in 1 of 1
No server marks it as only reading: treat it as able to change data.
From each publisher's own tool list. We never call a tool.
Servers
| Server | Inputs | Read-only? |
|---|---|---|
CaBuAr Wildfire Spread Prediction co.huggingface.amar-atoum/cabuar-pipeline Project the post-fire Sentinel-2 scene and the burn scar from a pre-fire Sentinel-2 image of an area in which a fire later occurs, using the CaBuAr V4 latent diffusion model. The burn scar is derived with the Normalized Burn Ratio difference, ΔNBR = NBR(pre-fire) - NBR(predicted post-fire), and a pixel counts as burned when ΔNBR > 0.05. The model does not predict whether or where a fire will ignite; it assumes a fire occurs in the scene. If a user passes a file as an input, use the upload_file_to_gradio tool, if present, to upload the file to the gradio app and create a Gradio File Input. Then use the returned path as the input to the tool. Returns: Tuple of (pre_fire_false_colour_image, predicted_post_fire_false_colour_image, delta_nbr_map_image, summary_markdown with the predicted burned fraction). | file,guidance_scale,seed,steps | Not stated |