lookAt

Requirements

• Tensorflow v2.0 or upper
• Python v3.8 or upper

Description

LookAt is based on two Tensorflow models, Fashion-MNIST and YOLOv3, which was created and trained to predict clothes on images. Fashion-MNIST has 10 clothes classes

• 0: T-shirt/top
• 1: Trouser
• 2: Pullover
• 3: Dress
• 4: Coat
• 5: Sandal
• 6: Shirt
• 7: Sneaker
• 8: Bag
• 9: Ankle boot

App predicts cropped images based on these 10 classes. Model has 60.000 train images and 10.000 test images.

All images are represented in 28x28x1 shape with gray color, so for predict images input images should be in the same shape and color

YOLOv3

YOLOv3 a basic object detection model, but we use it to detect clothes in images and crop them.

API

API created using Fast-API python framework. Users upload images on API, models start to predict.

API has two parameters in body - user_id and url.

/api/load_image/

method is a POST. This method uses the Fashion-MNIST model for non-person images, and YOLOv3 model for images with persons, and returns predicted images with dominant color.