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license: apache-2.0
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license: apache-2.0
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---
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# HYPERVIEW - Vision Transformer Model (https://ai4eo.eu/challenge/hyperview-challenge/):
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This repository is based on the original code from:
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[ridvansalihkuzu/hyperview_eagleeyes (experimental_1 branch)]:
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https://github.com/ridvansalihkuzu/hyperview_eagleeyes/tree/master/experimental_1
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Below are the instructions to set up the environment and run the code:
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## Table of Contents
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- [Setup and Usage](#setup-and-usage)
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- [Loading the Pre-Trained Model](#loading-the-pre-trained-model)
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- [Loading the Training Data](#loading-the-training-data)
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- [Code Modifications](#code-modifications)
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- [Environment Setup](#environment-setup)
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## Setup and Usage
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### Loading the Pre-Trained Model
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To load a pre-trained model ("VisionTransformer.pt"), use the following code snippet:
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```python
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import clip
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from clip.downstream_task import TaskType
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import torch # Make sure to import torch
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device = "cpu" # Change to 'cuda' if you have a GPU
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num_classes = 4 # Number of classes in the original HYPERVIEW dataset
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# Load the CLIP model with the downstream task configuration
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model, _ = clip.load(
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"ViT-L/14", device, downstream_task=TaskType.HYPERVIEW,
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class_num=num_classes
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)
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# Load the pre-trained weights
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model.load_state_dict(torch.load("VisionTransformer.pt"))
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model.eval() # Set the model to evaluation mode
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```
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