This project try to understand the Traffic by detecting different objects using computer vision technology.
car_chase_01.mp4
In my Btech final year project my team worked on a thesis on an AI Based Traffic management system(TrafficAI) on the basis of an idea to automate the traffic system . Our goal was to perform research on whether it is possible to automate the traffic system, advantages and disadvantages of having it , how it should be built , is it cost feasible . We have used the YOLO model and opencvโs DarkNet algo to detect , differentiate the transport objects separately .
Python, Jupyter Notebook, Computer Vision, OpenCV, MoviePy
Clone the project
git clone https://github.com/LordSomen/Traffic-Analysis my_project
Go to the project directory
cd my-project
Install dependencies
# make sure to install python
# numpy
# pandas
# opencv
install the yolov3 model from this link.
running the code in local
# for analyzing traffic in image file
python yolo.py -i [local_path_to_image_file] -y [local_path_to_yolov3_model]
# for analyzing traffic in video file
python yolo.py -i [local_path_to_video_file] -y [local_path_to_yolov3_model]
We have Learned how to use yolov3 model to detect different objects in any digital picture or videofeed.
one of the main challenges is to optimize our model to detect diffrent traffic objects in a crowd, in that scenario we have to tune the model a bit and run it couple of times to understand how to detect different as much possible
Python, Machine Learning, Computer Vision, research, analytics.
Software Developer with experience of almost 2 Years working in different software roles. Very much Enthusiast about DataScience | AI | ML | DL . Skilled in Python , Data Analysis, Software Engineering, Github, Linux, Algorithms, SQL, and Object-Oriented Programming (OOP)
For any queries feell free to contact me at soumyajit637@gmail.com .