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@@ -36,10 +36,13 @@ Here below find all the dataset's versions and descriptions.
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  * **SAT1_dataset_5_best_cities**: Top 5 municipalities based on Baseline method from satellite extractor
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  * **SAT2_dataset_10_best_cities**: Top 10 municipalities based on Baseline method from satellite extractor
 
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  *RGB-Version*: [[Link](https://huggingface.co/datasets/MITCriticalData/10_municipalities_RGB)]
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  * **SAT3_FULL_COLOMBIA**: Top 81 municipalities based on Baseline method from satellite extractor
 
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  *DATASET_81_CITIES_v1.0*: [[link](https://huggingface.co/datasets/MITCriticalData/DATASET_81_CITIES_v1.0)]
 
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  *DATASET_81_CITIES_v2.0*: [[link](https://huggingface.co/datasets/MITCriticalData/DATASET_81_CITIES_v2.0)]
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  * **Creating Cloud-Cloudless Paired Dataset**: This dataset, derived from imagery in five Colombian municipalities, consists of 1640 images (820 pairs), where each of the 164 images per municipality is paired with a previously identified optimal cloudless image. The Cloud2CloudlesDataset class organizes these pairs into a new folder (DATASET), with images renamed to indicate ground truth and cloud presence. The class, initialized with source and destination paths, includes tests for image count verification and folder existence confirmation.
 
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  * **SAT1_dataset_5_best_cities**: Top 5 municipalities based on Baseline method from satellite extractor
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  * **SAT2_dataset_10_best_cities**: Top 10 municipalities based on Baseline method from satellite extractor
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  *RGB-Version*: [[Link](https://huggingface.co/datasets/MITCriticalData/10_municipalities_RGB)]
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  * **SAT3_FULL_COLOMBIA**: Top 81 municipalities based on Baseline method from satellite extractor
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  *DATASET_81_CITIES_v1.0*: [[link](https://huggingface.co/datasets/MITCriticalData/DATASET_81_CITIES_v1.0)]
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  *DATASET_81_CITIES_v2.0*: [[link](https://huggingface.co/datasets/MITCriticalData/DATASET_81_CITIES_v2.0)]
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  * **Creating Cloud-Cloudless Paired Dataset**: This dataset, derived from imagery in five Colombian municipalities, consists of 1640 images (820 pairs), where each of the 164 images per municipality is paired with a previously identified optimal cloudless image. The Cloud2CloudlesDataset class organizes these pairs into a new folder (DATASET), with images renamed to indicate ground truth and cloud presence. The class, initialized with source and destination paths, includes tests for image count verification and folder existence confirmation.