aap9002/RGB_Optic_Flow_Bend_Classification
Data Viewer - View Samples Data Viewer - View Sample Count In our project on classifying the sharpness of bends using time-sequence data, we generated two distinct datasets: RGB Images: Capturing conventional color information. Wide View Dense Optic Flow: Providing detailed motion dynamics. Notably, our latest dataset required approximately 16 hours to generate the samples using the code available in this GitHub notebook. To enhance organization and accessibility, we have migrated the… See the full description on the dataset page: https://huggingface.co/datasets/aap9002/RGB_Optic_Flow_Bend_Classification.
Data Viewer - View Sample Count
In our project on classifying the sharpness of bends using time-sequence data, we generated two distinct datasets:
- RGB Images: Capturing conventional color information.
- Wide View Dense Optic Flow: Providing detailed motion dynamics.
Notably, our latest dataset required approximately 16 hours to generate the samples using the code available in this GitHub notebook.
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.