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 NMS Benchmarking Framework
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 CUDA implementation of the algorithm described in the paper:
 
 "Work-Efficient Parallel Non-Maximum Suppression Kernels" 
 https://dx.doi.org/10.1093/comjnl/bxaa108
 
 The Computer Journal
 David Oro, Carles Fernández, Xavier Martorell, Javier Hernando
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* Requirements:
           1. GCC Compiler v5.0 or greater
           2. CUDA Toolkit v6.0 or greater
           3. NVIDIA GPU with Compute Capability 3.2 or greater
* Build instructions:
           1. Set the GPU_ARCH and SM_ARCH variables in the Makefile according to 
              the underlying NVIDIA GPU architecture of your computer. For further 
              details, please refer to our GitHub Wiki page:
                    https://github.com/hertasecurity/gpu-nms/wiki
           2. Set your CUDA installation path in the Makefile (CUDA_HEADERS and 
              CUDA_LIBS variables)
           3. Compile the source code:   make
* Execution:
           * You can run the GPU NMS benchmark using a comma-separated input file 
             containing the list of detected objects in the following format:
                    xcoordinate,ycoordinate,width,score
           * We provide a sample input file "detections.txt" obtained after having 
             executed a face detector over the "oscars.png" file.
           * The GPU NMS benchmark must be executed as follows:
                    ./nmstest  detections.txt  output.txt
           * The application should then return the computation time of both the MAP 
             and REDUCE GPU NMS kernels and write the results in the "output.txt" file.
           * Finally, you can visualize both the input (pre-NMS) and the output 
             (post-NMS) with the "drawrectangles" Python script. For example:
                    ./drawrectangles  detections.txt
             Or:
                    ./drawrectangles  output.txt
             The graphical output is stored in the "oscarsdets.png" file
* IMPORTANT:
           * The source code must be compiled to the microarchitecture matching the 
             GPU platform during execution (check GPU_ARCH and SM_ARCH variables 
             in the Makefile).
           * If the NMS algorithm is not capable of properly merging the candidate 
             windows, re-check the GPU_ARCH and SM_ARCH variables and then 
             recompile the code.
           * This GPU NMS benchmark is limited to a maximum of 4096 detected 
             objects per input. If you want to increase this limit, please 
             modify the MAX_DETECTIONS constant in the "nms.cu" file.