?Try on the go? will provide people with an online alternative to an offline store?s try room where you can try on different outfits to see if they are the right match using your web camera. The motivation behind this project is to minimize the number of returns people make when they end up wit
“Try on the go” will provide people with an online alternative to an offline store’s try room where you can try on different outfits to see if they are the right match using your web camera. The motivation behind this project is to minimize the number of returns people make when they end up with clothes that don’t look good on them; by providing them with a virtual clothing system.
The objectives of this project are:
In the proposed work, our main goal is to implement a practical solution that can enhance customer satisfaction by providing an augmented reality experience through artificial intelligence and computer vision. The proposed system will be developed with a focus on minimizing cost and hardware components. The system will be more accessible to customers and will make use of mobile/computer web cameras to capture human motion and virtually fit clothes on them.
This application will allow users to:
This can be done by making an application where users will select or upload the picture of the outfit they like, click on the try-on button, either open their cameras and take a photo or upload it from their gallery into our application.
The system will find the key points on the human body and the outfit they want to try using OpenPose and OpenCV libraries in Python. The coordinates will be matched and the desired outfit will be overlaid on the uploaded picture of the user using computer vision. The application will be developed using Python and its frameworks and libraries. User’s photos will be secured using some encryption and access control mechanisms.
The average cloth return rate rests at around 20% while brick-and-mortar return rates averages at 8%. Most apparel companies have to deal with high return rates because of customers’ inability to try on the clothes physically before buying them as they can do in offline stores.
At present, people are living a busy lifestyle which is leading them to buy ready-to-wear clothes with or without try-on, hoping for a perfect match. Trying on clothes physically is a difficult and time-consuming process to find the best matching outfit. Also on the vendor’s side, it is a tedious process to repack all the returned or misplaced items that were taken out by the customer.
In online shopping, it is virtually impossible to find a suitable outfit that would suit them by just looking at a few images of clothes. People are unable to see if the outfit they are buying through an online shopping platform will be a perfect match. Hence, this leads to several issues like the customer is not satisfied with the product and now he wants to return it.
To overcome this problem, virtual dressing rooms come into play where it allows customers to try on different apparel virtually in front of their web cameras to choose the best-matched outfit within a shorter time from the comfort of their homes without the need of spending hours in an offline store and enhances customer satisfaction.
“Try on the go” will help both customers and online shopping platforms by allowing customers to select the best outfits for themselves by trying them virtually and thus reducing the return rates and leveraging customers’ curiosity about the product and intention towards purchasing the product.
The expected outcomes of the project are:
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| GPU | Equipment | 1 | 70000 | 70000 |
| Datasets | Miscellaneous | 1 | 10000 | 10000 |
| Total in (Rs) | 80000 |
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