Combining the techniques of Object Detection and Instance Segmentation, using deep learning model Mask R-CNN in clothes retrieval. Various medias such as clothing image and street fashion video can be analyzed by the model. Also, ClosetAI can generate business intelligence analysis in giving you a popular fashion items report.
DeepFashion2 Dataset which contains including 191,961 training images and 32,153 validation images. Json files of image information such as annotations and category names are also provided.
https://www.youtube.com/watch?v=JSrxAmX793k
- Deep Learning: Computer Vision, Keras
- Flask: deploy the machine learning model as a web application, classifying clothes in the uploaded image
- Git LFS: upload large file greater than 100MB to GitHub using terminal command, self-written tutorial can be found here
@article{DeepFashion2,
author = {Yuying Ge and Ruimao Zhang and Lingyun Wu and Xiaogang Wang and Xiaoou Tang and Ping Luo},
title={A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images},
journal={CVPR},
year={2019}
}
@misc{matterport_maskrcnn_2017,
title={Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow},
author={Waleed Abdulla},
year={2017},
publisher={Github},
journal={GitHub repository},
howpublished={\url{https://github.com/matterport/Mask_RCNN}},
}
This project cannnot be accomplished without references from below repositories and blog post. Thank you coders for sharing your experience! =]