Fm01 Computer Vision Project

fm

Updated 3 years ago

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Classes (12)
0
1
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Auto Car
Ltv
bike
other
person
Description

Here are a few use cases for this project:

  1. Traffic Monitoring and Management: Fm01 can be used to analyze traffic patterns in real-time, identify vehicle types (bike, car, Ltv, Auto) and their count, and relay this information to traffic management systems to optimize traffic flow and reduce congestion.

  2. Parking Lot Occupancy Monitoring: The model can be used to track parking space usage, count available spaces, and direct drivers to open parking spots in crowded lots, as well as monitor car registrations and enforce parking rules.

  3. Pedestrian Safety and Crowd Analysis: Fm01 can be utilized to identify pedestrians and cyclists in urban environments and help improve road infrastructure to enhance safety for non-motorized road users. It can also be applied to monitor crowd levels and density in public spaces, aiding event management and emergency preparedness.

  4. Surveillance and Security Applications: The computer vision model can assist in the monitoring of public spaces and private properties, detecting unauthorized individuals or vehicles, as well as identifying suspicious activities in real-time.

  5. Transportation Planning and Research: Fm01 can be employed to collect and analyze data on vehicular and pedestrian traffic patterns, examine infrastructure usage, and support city planning initiatives that aim to develop efficient and sustainable urban environments.

Supervision

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Cite This Project

LICENSE
CC BY 4.0

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

                        @misc{
                            fm01_dataset,
                            title = { Fm01 Dataset },
                            type = { Open Source Dataset },
                            author = { fm },
                            howpublished = { \url{ https://universe.roboflow.com/fm/fm01 } },
                            url = { https://universe.roboflow.com/fm/fm01 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { apr },
                            note = { visited on 2024-11-21 },
                            }
                        
                    

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