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--- |
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license: mit |
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task_categories: |
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- video-classification |
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tags: |
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- RGB |
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- OPTICFLOW |
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- DASHCAM |
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- ROAD |
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- BEND |
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pretty_name: RGB and Optic Flow Bend Classification Dataset |
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--- |
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[Data Viewer - View Samples](https://huggingface.co/datasets/aap9002/RGB_Optic_Flow_Bend_Classification/sql-console/djV2nZu) |
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[Data Viewer - View Sample Count](https://huggingface.co/datasets/aap9002/RGB_Optic_Flow_Bend_Classification/sql-console/Jkn-dka) |
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In our project on classifying the sharpness of bends using time-sequence data, we generated two distinct datasets: |
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- **RGB Images:** Capturing conventional color information. |
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- **Wide View Dense Optic Flow:** Providing detailed motion dynamics. |
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Notably, our latest dataset required approximately 16 hours to generate the samples using the code available in this [GitHub notebook](https://github.com/AAP9002/Third-Year-Project/blob/main/Solutions/extract_gps_data/gps_bend_finding_with_gaussian_clustering_with_catrisian_positions_and_circle_fitting_with_distance_based_angles.ipynb). |
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To enhance organization and accessibility, we have migrated the trained models to a dedicated repository. You can explore the models and find additional documentation on [Hugging Face](https://huggingface.co/aap9002/RGB_Optic_Flow_Bend_Classification/). |
