UniNet-Pytorch:虹膜识别的准确，通用的深度学习框架

# UniNet-Pytorch Pytorch port of [UniNet](https://www4.comp.polyu.edu.hk/~csajaykr/myhome/papers/ICCV2017.pdf). An accurate and generalizable deep learning framework for iris recognition. **Reference**: Zijing Zhao and Ajay Kumar, "Towards More Accurate Iris Recognition Using Deeply Learned Spatially Corresponding Features", Internation Conference on Computer Vision (ICCV), Spotlight, Venice, Italy, 2017. - [Paper](https://www4.comp.polyu.edu.hk/~csajaykr/myhome/papers/ICCV2017.pdf) - [Code](http://www.comp.polyu.edu.hk/~csajaykr/deepiris.htm) ## Install - Python 3.6 - Pytorch 1.0+ - torchvision 0.2.2+ - opencv 3.4 - caffe(Optional) - tqdm(Optional) ## Code structure - *ICCV17_release* - Source code and caffe model attached to the paper - *models* - Source code and caffe model attached to the paper - *util* - **caffemodel2pth.py** - Export the network parameters from caffemodel to pytorch pth format - **normalize.py** - Function of iris image normalization. - **normalize_tool.py** - Tool for iris normalization. - Left click to mark, right click to draw a circle (at least 3 points),'q' key to confirm, other keys to cancel - Iris first, pupil rear - **segment.py** - Iris image segmentation - **enroll_dataset.py** - Register all images in the folder - **enroll_single.py** - Register single image in the folder - **evaluation.py** - Evaluation - **match.py** - Match - **verify.py** - Identify - Compare the extracted mat file with all mat files in the folder