Abstract:
REAL TIME OBJECT DETECTION is a desktop based application that will detect
multiple objects in an image and draw the bounding boxes around them. It comes
under the field of computer vision. It will detect the activity performed by different
entities and can be helpful in security and surveillance. The language used for this
project will be PYTHON. Mainly we will use OS, tensorflow, keras, colorsys and
yolo3. The framework used in this project is SLIMYOLOv3. SlimYOLOv3 with
fewer trainable parameters and floating point operations (FLOP) compared to the
original YOLOv3 as a promising solution for real-time object detection in UAV. The
front-end of this app is developed with tkinter framework which helps us to build an
easy and feasible desktop application. As machine learning is evolving day by day
new frameworks, models and datasets are releasing which will help us to give more
accuracy. That’s why we use SlimYOLOv3 algorithm and COCO dataset which
helps us to give result with the help of fps.
