Clothes-Recognition-and-Retrieval

Clothes recognition and retrieval on clothing retails. Please see report for more details.

Result on real data

Usage

Required package

1. tensorflow (2.0.0a0), GPU version can also be used
2. opencv (4.1.0.25)

Installation

pip install -r requirements.txt

Reproduce results

1. Run main.py to produce final classification result
2. Run cloth_detection.py to produce images with clothes detection bounding boxes.

Model weights

We trained a Yolo-v3 object detection on DeepFashion2 dataset, pre-trained model weights (tensorflow weights and darknet weights) can be download here.

Dataset

For the classifier, we use a relatively small dataset consists of only 46 clothes of 2 classes (clothes with stripes and clothes without stripes), the dataset can be download here.

System pipeline

References

1. Yannis Kalantidis, Lyndon Kennedy & Li-Jia Li. (2013) "Getting the Look: Clothing Recognition and Segmentation for Automatic Product Suggestions in Everyday Photos".

2. Yuying Ge, Ruimao Zhang, Lingyun Wu, Xiaogang Wang, Xiaoou Tang & Ping Luo. (2019) "DeepFashion2: A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images".

3. Joseph Redmon & Ali Farhadi. (2018) "YOLOv3: An Incremental Improvement".