• Ashutosh Madhav
• Tanmay Chaudhari
• Prof. Nilima Patil

Style is innately friendly and public. Style is like eating, you shouldn't adhere to a similar menu. We dress not just for ourselves yet in addition for the fittingness of the climate we are in. Now and again when we purchase garments online we might want to give them a shot first before purchasing however since it's web-based we can't do such. We propose a full-stack web platform that allows you to take trials of the garments you need to purchase virtually. The article of clothing move issue contains two errands: figuring out how to separate an individual's body (present, shape, shading) from their dress (article of clothing type, shape, style) and afterward creating new pictures of the wearer wearing erratic articles of clothing. It works by extracting fabric from the source picture and squeezing it into your profile picture. In the engine, it utilizes two separate profound learning models: Material division model: Custom Deeplab model to extricate fabric from source picture. Present assessor model: Pretrained Openpose body_25 model was used to find shoulder focuses. The removed material is mixed into a profile picture given the shoulder area. Highlights: Upholds a wide range of upper wear garments for all kinds of people. Precise fabric extraction and fitting. Straightforward, elegant, and simple to utilize web application.

Deep Learning, Machine Learning, Fashion Technology

"A Minimal Virtual Cloth Tryon System using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 4, page no.f598-f605, April-2022, Available :http://www.jetir.org/papers/JETIR2204576.pdf

"A Minimal Virtual Cloth Tryon System using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 4, page no. ppf598-f605, April-2022, Available at : http://www.jetir.org/papers/JETIR2204576.pdf