R-CNN VGG nail plate detect model

Requirements- Linux (Ubuntu) - NVIDIA GPU (GTX-1050 or better) - BVLC PyCaffe - py-faster RCNNs Download- VGG-16 nail part detection model : - demo_nail.py : #1 Main Server; US East How to use1. It is difficult to compile a CPU-mode faster-rcnn on Windows operating system at present. NVidia GPU with CUDA and cuDNN is required because it takes too much time to conduct CNNs training without GPU We recommend to install py-faster-rcnn program (https://github.com/rbgirshick/py-faster-rcnn) which operated on Linux (http://ubuntu.com). Installation Tutorial by Huangying : https://huangying-zhan.github.io/2016/09/22/detection-faster-rcnn.html 2. Download (VGG-16 nail part detection model) : #1 OneDrive (483 Mbytes) Model - VGG-16 nail part detection ; 2 outputs(class) : #0 background #1 nail The VGG-16 nail part model was trained using information about the crop location on the nail part from the Asan A2 dataset as instructed by the following tutorials. http://sgsai.blogspot.kr/2016/02/training-faster-r-cnn-on-custom-dataset.html https://github.com/deboc/py-faster-rcnn/tree/master/help 3. We modified demo.py of py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn/blob/master/tools/demo.py) to get the following image. Download our demo_nail.py ( #1 Main Server; US East )