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updated model url
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algorithm_catalog/vito/random_forest_firemapping/openeo_udp/generate.py

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@@ -29,7 +29,7 @@ def generate() -> dict:
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inference_cube = s2_feature_cube.merge_cubes(s1_feature_cube)
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# link to the trained model: this model has an expiry date
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model = "https://openeo.vito.be/openeo/1.2/jobs/j-250707130527460a823273791daa4344/results/assets/ZWNjZTlmZWEwNGI4YzljNzZhYzc2YjQ1YjZiYTAwYzIwZjIxMWJkYTQ4NTZjMTRhYTQ0NzViOGU4ZWQ0MzNjZEBlZ2kuZXU=/2c00312531cc55303c14ba68ff2472d4/randomforest.model.tar.gz?expires=1752502120"
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model = "https://openeo.vito.be/openeo/1.2/jobs/j-250707130527460a823273791daa4344/results/items/ZWNjZTlmZWEwNGI4YzljNzZhYzc2YjQ1YjZiYTAwYzIwZjIxMWJkYTQ4NTZjMTRhYTQ0NzViOGU4ZWQ0MzNjZEBlZ2kuZXU=/a57df24a856cff107494dedfbfdcc180/ml_model_metadata.json?expires=1752501082"
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# predict of training data
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inference = inference_cube.predict_random_forest(

algorithm_catalog/vito/random_forest_firemapping/openeo_udp/random_forest_firemapping.json

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"loadmlmodel1": {
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"process_id": "load_ml_model",
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"arguments": {
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"id": "https://openeo.vito.be/openeo/1.2/jobs/j-250707130527460a823273791daa4344/results/assets/ZWNjZTlmZWEwNGI4YzljNzZhYzc2YjQ1YjZiYTAwYzIwZjIxMWJkYTQ4NTZjMTRhYTQ0NzViOGU4ZWQ0MzNjZEBlZ2kuZXU=/2c00312531cc55303c14ba68ff2472d4/randomforest.model.tar.gz?expires=1752502120"
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"id": "https://openeo.vito.be/openeo/1.2/jobs/j-250707130527460a823273791daa4344/results/items/ZWNjZTlmZWEwNGI4YzljNzZhYzc2YjQ1YjZiYTAwYzIwZjIxMWJkYTQ4NTZjMTRhYTQ0NzViOGU4ZWQ0MzNjZEBlZ2kuZXU=/a57df24a856cff107494dedfbfdcc180/ml_model_metadata.json?expires=1752501082"
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}
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},
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"loadcollection1": {

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