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Traffic Violations Detector using object detection -part2
This document presents a traffic violation detection system using object detection. It discusses introducing object detection and its applications like self-driving cars and optical character recognition. It describes problems with manual traffic management and the COCO dataset used. The proposed solution uses a TensorFlow object detection API to detect violations from uploaded images on a web application. It concludes that the anticipated algorithm can efficiently detect vehicle number plates with room for improving low light detection accuracy.
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Traffic Violations Detector using object detection -part2
- 1. Traffic Violation Detectorusing object Detection A Presentation On Department Of Computer Science & Engineering Shri Ram Murti Smarak College Of Engineering , Technology & Research,Bareilly Presented by:- Shraddha Kasaudhan Deeksha Gangwar Tarang Jain
- 2. Outlines 1. Introduction ofproject 2. Introduction of object detection 3. Applications 4. Problem 5. Data set 6. Solutions 7. Output of OCR 8. Work in progress second (II) 9. Conclusion 10.References
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- 4. Traffic Violation Detector: •Basically traffic violation is an act when a vehicle violates the traffic rules. •With the growth of the number of vehicles, the number of traffic accidents is rapidly rising. • The traffic violation detector can ensure a smooth traffic flow.
- 5. • A completetraffic violation detection system is realized in python with OpenCV. • It can detect violations, such as running red lights, speeding etc. in real time.
- 6. Artificial Intelligence•Object detection isa computer technology that deals with detecting objects of a certain class in images and videos. •Object detection has applications in many areas of computer vision, including image retrieval and video surveillance Introduction of object detection
- 7. Applications Self driving cars:- Oneof the best examples of why you need object detection is for autonomous driving is In order for a car to decide what to do in next step whether accelerate, apply brakes or turn, it needs to know. Optical Character Recognition (OCR):- OCR is a method that converts the images into machine-encoded text. Tracking objects:- Object detection system is also used in tracking the objects, for example tracking a ball during a football match, tracking movement of a cricket bat Applications
- 8. Human Diligence Man Power ManualLabour Corruption Problems: Due to increasing growth of population and vehicles in smart and metropolitan cities people face lot of problem at the traffic management of the business towns.
- 9. Data set :- CommonObject in Context(COCO):- • It is a dataset which contains 2,00,000 images and more than 5,00,000 object annotations in 80 categories. • The average number of objects is 7.2 per images.
- 10. Solution Step 1:- •Creating anObject Detection Web application Using Visual Studio code. •Create Webpage •Create main file by Python as a backend •Create Database •Connectivity of WebPages and database
- 11. Step 2:- •Creating anObject Detection using Tensor flow. •Create a virtual machine using Anaconda. •Install the Object Detection API Library. •Install and launch an object detection web application. •Test the web application with uploaded images.
- 12. Step 3:- Creating anOptical Character Recognition using Nanonet API . • Clone the Repo. •Get your free API Key. • Set the API key as an Environment Variable. • Create a New Model. • Add Model Id as Environment Variable. • Upload the Training Data. • Train Model. • Get Model State. • Make Prediction.
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- 14. Work progress second(II) 1.Upload and result
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- 17. Project output onweb application
- 18. Conclusion •An efficient lesstime consuming vehicle number plate detection method is projected which performed on multifaceted image. •Our anticipated algorithm is mainly based on Indian automobile number plate system. Extraction of number plate accuracy may be increased for low ambient light image.
- 19. References • https://cloud.google.com/solutions/creating-object-detection- application-tensorflow • https://en.wikipedia.org/wiki/Object_detection •https://www.analyticsvidhya.com/blog/2018/12/guide- convolutional-neural-network-cnn/ • https://www.academia.edu/Documents/in/Object_Detection •https://www.researchgate.net/publication/271545712_A_video- based_traffic_violation_detection_system/link/54d2248c0cf28370d0e1c44 6/do wnload
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