ccs_img_22 Object Detection Dataset and Pre-Trained Model by arelis guzman

Images

969 images

Explore Dataset

Here are a few use cases for this project:

Urban Infrastructure Maintenance This model can be crucial in identifying problems in urban infrastructure like damaged pavement (pavimento), holes (huecos), faulty traffic lights (semaforo), or unattended trees (arbol). These could help urban service management teams to plan and prioritize their maintenance activities.
City Planning and Development City planners can use this model to understand the distribution and condition of city features such as trees (arbol), pedestrian crossings (cebra), sidewalk ramps (rampa), and road barriers (sep_isla). They can also identify where additional urban fixtures like kiosks (kiosko) or cabinets (armario) could be beneficial.
Traffic Flow Management Using this model, traffic management systems can identify critical road user information like the count of cars, detect traffic lights (semaforo), and identify zebra crossings (cebra). This would allow for real-time traffic flow optimization and better decision making during traffic congestion.
Autonomous Vehicle Systems In autonomous vehicle navigation systems, understanding the urban environment is crucial. Identifying objects like sewers (alcantarilla), posts (poste), manhole covers (brocal), and road islands (Int_isla) could enhance the AI decision making in complex urban environments, ensuring safe and efficient navigation.
Accessibility and Risk Assessment This model can be used to assess accessibility and safety concerns for people with disabilities by identifying sidewalk ramps (rampa), crosswalks (cebra), and sidewalks (acera). It could also potentially detect risks like open manhole covers (brocal juntos) ensuring corrective actions can be taken immediately.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            ccs_img_22_dataset,
                            title = { ccs_img_22 Dataset },
                            type = { Open Source Dataset },
                            author = { arelis guzman },
                            howpublished = { \url{ https://universe.roboflow.com/arelis-guzman/ccs_img_22 } },
                            url = { https://universe.roboflow.com/arelis-guzman/ccs_img_22 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { apr },
                            note = { visited on 2024-05-12 },
                            }