Installations: CUDA - 9.0 CuDNN - 7.0.5 Python - 3.5+ Anaconda - 3
Python Libraries : -Tensorflow GPU enabled . -Windows version x86 exe(local). -Pillow. -Numpy.
Steps:
- Update the paths in ias.py file according to the location of the files. Use absolute paths.
- Make sure the folders in path2 and path3 (destination of the output images 256x256 and 32x32 respectively) are created beforehand.
- Run the ias_full.py file.
- Update the paths in cnn1.py and build_image_data.py files according to the location of the files. Use absolute paths.
- Run build_image_data.py. Make sure that label.txt is in the same folder as build_image_data as well as the folders(named after the classes in label.txt) are in the same folder.
- Run the build_image_data.py file. After running the file you should see "train-00000-of-00002.tfrecord" and "train-00000-of-00002.tfrecord" files created.
- Run cnn1.py. This will take a long time to run.
- Update the paths in cnn1.py and build_image_data.py files according to the location of the files. Use absolute paths.
- Run build_image_data.py. Make sure that label.txt is in the same folder as build_image_data as well as the folders(named after the classes in label.txt) are in the same folder.
- Run the build_image_data.py file. After running the file you should see "train-00000-of-00002.tfrecord" and "train-00000-of-00002.tfrecord" files created.
- Run cnn1.py. This will take a long time to run.
IEEE Paper link(base paper): http://ieeexplore.ieee.org/document/8190895/references?ctx=references