• LAKSHMI PRASHANTHI
• SUSHMITHAA
• YOGESWARI

The proposed mini project is an image to cartoon python OpenCV machine learning that converts uploaded images to cartoon style versions using machine learning algorithms. The main objective of the project is to provide an easy to use and accessible tool for users to convert their images to cartoons. The major goal is to produce a final product that may be used to transform real-world images or videos into animated prints (cartoon images) or videotapes. The idea behind the paper is built around original images and videos that are then transformed into an artistic form akin to oil. Among all the techniques available, the operation of a Generative Adversarial Network (GAN) dubbed Cartoon GAN may be employed for the styling of real-world images that employ two loss functions—happy loss and hostile loss—to obtain a clean and clear image. While creating the layout, this project would use the OpenCV library in Python. Python is a library collection with multiplex libraries for operations in the real world. OpenCV is one suitable library.

Image to cartoon , Machine Learning , Deep learning, Convolutional Neural Network (CNN) , User Interface(UI) , User Experience (UX), High Availability ,Scalability , Image Quality , Python , Input Image , cartoon style images , colour quantization , edges , blurred images , openCV

"IMAGE TO CARTOON USING PYTHON OPENCV", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.m276-m282, May-2023, Available :http://www.jetir.org/papers/JETIR2305C40.pdf

"IMAGE TO CARTOON USING PYTHON OPENCV", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppm276-m282, May-2023, Available at : http://www.jetir.org/papers/JETIR2305C40.pdf