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Object Detection with Voice Sensor and Cartoonizing the Image

Journal: International Journal of Advanced Trends in Computer Science and Engineering (IJATCSE) (Vol.10, No. 4)

Publication Date:

Authors : ;

Page : 2762-2767

Keywords : Object Detection; YOLO-You Look Only Once; NMS- Non-Max Suppression; IoU-Intersection of Union; Cartoonizing; Voice Sensor-win32com.client.;

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Object detection is a general term to describe a collection of related computer vision tasks that involve activities like identifying objects in digital photographs, identifying objects in live captured images. Object detection combines these two tasks and localizes and classifies one or more objects in an image. Object localization refers to identifying the location of one or more objects in an image and drawing abounding box around their extent. Image classification involves predicting the class of one object in an image. In this application SAPI.spVoice is used inorder to add voice. Voice sensor is used especially for the people who cannot see objects in a particular image. We present YOLO, a new approach to object detection. YOLO, is a technique for object recognition designed for speed and real-time use. YOLO model processes images in real-time at 45 frames per second. A smaller version of the network, Fast YOLO, processes an astounding 155 frames per second. Cartoonizing an image will transforms the image into a cartoon image. Today we can find countless numbers of photo editing applications on the internet that allow us to transforms images into cartoons on the internet. It's similar to BEAUTIFY or AI effect in cameras of modern mobile phones. It can be taken as smoothening of an image to an extent. It makes an image look vicious and like water paint, removing the roughness in colors. So, this application will allow us to detect and identify the objects in an image along with voice sensor which converts annotated text to speech and transforms an image into a cartoon image without using any external tool.

Last modified: 2021-08-10 17:49:10