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- ## You can load this model using the following code:
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- ```python
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- from huggingface_hub import hf_hub_download
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- import torch
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-
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- # Specify the repository and the filename of the model you want to load
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- repo_id = "{organization_name}/{repo_name}" # Replace with your repo name
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- filename = "{path_name}"
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- model_path = hf_hub_download(repo_id=repo_id, filename=filename)
 
 
 
 
 
 
 
 
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- # Load the model using torch
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- model_test = torch.load(model_path)
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- model_test.eval() # Set the model to evaluation mode
 
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  ```
 
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+ Hello! You can perform inference with our Resnet model using the Resnet_inference.ipynb notebook located in this repo.
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+ Please open the notebook and navigate to the INPUTS tab, then follow the steps below in order to perform inference on your images.
 
 
 
 
 
 
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+ ## 1. Replace the latitude and longitude mean and std with your own.
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+ The latitude and longitude mean and std values are preloaded from our training data.
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+ ```python
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+ # Latitude and longitude mean and std loaded from training data
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+ lat_mean = 39.95173675925926
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+ lat_std = 0.0006117096745964738
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+ lon_mean = -75.19119498148149
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+ lon_std = 0.0007743986248108865
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+ ```
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+ ## 2. Load your images for inference
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+ Your images will be stored as 'dataset_test' in the code.
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+ ```python
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+ dataset_test = load_dataset("{YOUR ORGANIZATION NAME}/{DATASET NAME}", split="test")
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  ```