Abstract:
In this days online shopping is playing a big role in our world as it is more easy to buy things online with using any device the connects to the internet and in any place without spending a lot of time in moving from one place to another also you can buy thing online from any place around the world but one major problem in the online shopping is testing the clothes before you buy how can this be possible with using only your phone , that’s what our project was aiming for to help the process of testing the cloth which in our case we tried testing shoes in your place only by using a camera we were able to develop a two deep learning model the first one is able to detect if there was a shoes in an image or not and the other model is able to trace the shoes angle from an image the study included a data of 300 images was collecting by taking photos of different shoes types from different angles and different leg angles also in order to use It in a deep learning we had to do some augmentation on the data to make it larger so we reached the number of 1500 image then the data was divided to train and test , the CNN model was trained to learn the different angles of the shoes image to have the best accuracy , the trained model was evaluated by getting the angles that the model outputs and put it on a unity program to that tests the angle on a 3D shoes model to see if it rotates the same angle as the image or not , the results we got for the final model showed that the model can trace the shoes angle from an image with accuracy equals to 75.3% which is a good result considering the number od data that we got the model can help in the future to be connected to a AR application to trace the angles automatically
