Dr. Wu, can you record a tutorial on how to use the combination of the geemap library and the TensorFlow library on your local computer? Thank you very much for your work and wish you a happy Chinese New Year!
Dr. Wu, I've been checking out your script on using locally trained ML models with Google Earth Engine. It's really cool how you train a random forest classifier with scikit-learn and then apply it in GEE. I'm curious, is there a way to use pre-trained ONNX models in a similar workflow? ONNX has some great models that could be useful for remote sensing in GEE. Any tips on how to make this work, like converting ONNX models to a format GEE can understand? Thanks for sharing your knowledge, it's super helpful!
Firstly, thank you for building geemap and all these amazing python tools - deeply appreciated from the remote sensing community! Will sklearn's GradientBoostingClassifier or xgboost work with rf_to_strings?
i have a lot of survey points (with lat and long) of particular species of trees in my region....how do i train a rf model (using temporal satellite datasets for one year ) for predicting this species in other regions. A response would be really helpful Sir.
Thanks a lot for the great video and provided code! I want to build a random forest classification with scikit learn and use the locally trained model in Earth Engine as you described. Instead of Class Labels I want Probabilities as an output of my machine learning model. Do I set the output mode with scikit learn or can I set the output mode in the already transformed ee.classifier?
Respected Sir, your tutorials are very helpful for the young learners like me. I have followed this tutorial but got "Request payload size exceeds the limit: 10485760 bytes." error each time. Even I have tried alsowith very small aoi to process but getting the same
