Image processing is used to extract important data from an image through processing and by using that information, machines can provide the understanding, interpretation, and description of the scene. Classifier allows us to process the image and map it to the provided classes. Our classifier allows
Wearable Recognition Using Artificial Intelligence
Image processing is used to extract important data from an image through processing and by using that information, machines can provide the understanding, interpretation, and description of the scene. Classifier allows us to process the image and map it to the provided classes. Our classifier allows the user to input an image, then the classifier identifies the wearables from the image using object detection techniques and classifies that wearable in provided classes. Object detection and classification is an important domain of artificial intelligence. Advancement in technologies provides the facility of building solutions, to automate recurring processes and eliminate human labor. Classification of products is a wider branch of object detection and computer vision, building the solution for the fashion industry to improve the workflow and for commercial use in the application of this solution. The basic categorization of wearable and apparel is done manually with the help of an attribute set of products. Each of these products lies in a class e.g. T-shirts, shirts, lower, shorts, dress, shoes, shades, caps, bags, etc. and each of them has an attribute set e.g. color, texture, color pattern, etc. The basic purpose of building the solution is to automate the classification process of these wearables by using advanced technologies. These classifications will be done by the classes of wearables and their attribute set provided in the dataset. Virtual Wardrobe is a concept of building a wardrobe of wearables or clothes a person owns, most of the time people do not know what they have and what to wear? So, using this solution, there might be an application that can facilitate people in building their virtual wardrobe.
The final deliverable will be a model which can identify the class of the wearable present in the picture. The model can be used as a basic building block for the implementation of advance application as discussed in the Benefits of the Project Section, or any other application which will propose in future. This model will be a pretrained model by a large amount of data with approximately 250,000 high resolution images. The model will be trained with the help of high-performance GPU named NVIDIA GTX 1050ti 4GB OC Edition which has capability of process high resolution images.
An application will also be included in the final deliverable. This application will provide functionality of building a virtual wardrobe, Virtual Wardrobe is a concept of building a wardrobe of outfits a person owns, there are some applications providing the functionality of virtual wardrobe but they use simple techniques like clicking the photos and storing it also provide the list of outfits and ask from user about the outfit he/she owns, these application lacks to provide the fully automated solution and ease to the user. Our solution will automate the entire process of building the wardrobe. In this scenario Azure Kinect DK will help us, Azure Kinect DK has a depth camera which has a capability to take the physical measurements of the object (wearables in our case). Also, the body tracking functionality of Azure Kinect DK helps to predict the best pose of the person present in the picture. The Azure Kinect DK also has some AI capabilities with pretrained models and computational powers which will help us in the future extension of the project like Augmented Reality Try room etc.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Azure Kinect Developer Kit | Equipment | 1 | 55000 | 55000 |
| NVIDIA GTX 1050TI 4GB OC Edition | Equipment | 1 | 15000 | 15000 |
| Total in (Rs) | 70000 |
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