Instructions to use google/maxim-s2-deraining-rain13k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use google/maxim-s2-deraining-rain13k with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://google/maxim-s2-deraining-rain13k") - Notebooks
- Google Colab
- Kaggle
How do I process the output of the model, i.e. the predictions?
#1
by AdvaithCA - opened
I ran the model on an image and got a list with 2 sublists made of Numpy arrays as the result, How exactly do I process this?
You can look into this Colab Notebook that shows how to post-process the predictions: https://colab.research.google.com/github/sayakpaul/maxim-tf/blob/main/notebooks/inference-dynamic-resize.ipynb