VISION BASED MISPLACED BOOK DETECTION SYSTEM USING DEEP CONVOLUTIONAL NEURAL NETWORKS

To obtain project files

Windows PC
CMake >= 3.8 for modern CUDA support: https://cmake.org/download/
CUDA 10.0: https://developer.nvidia.com/cuda-toolkit-archive (on Linux do Post-installation Actions)
OpenCV >= 2.4: use your preferred package manager (brew, apt), build from source using vcpkg or download from OpenCV official site (on Windows set system variable OpenCV_DIR = C:\opencv\build - where are the include and x64 folders image)
cuDNN >= 7.0 for CUDA 10.0 https://developer.nvidia.com/rdp/cudnn-archive (on Linux copy cudnn.h,libcudnn.so... as desribed here https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#installlinux-tar , on Windows copy cudnn.h,cudnn64_7.dll, cudnn64_7.lib as desribed here https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#installwindows )
GPU with CC >= 3.0: https://en.wikipedia.org/wiki/CUDA#GPUs_supported
Python >=3.5
Pytesseract

Run : darknet.exe detector train cfgk/obj.data cfgk/yolov3.cfg darknet19_448.conv.23
For object detection using pretrained weights : darknet.exe detector test cfgk/obj.data cfgk/yolov3.cfg backup/yolov3_6000.weights file_name.jpg