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MIVisionX

MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. Khronos OpenVX is also delivered with MIVisionX.

Inference Generator

caffe2openvx: Convert a pre-trained CAFFE model into a C library for use by applications.

The generated C code will have two functions in annmodule.h:

void annGetTensorDimensions(
        vx_size dimInput[4],    // input tensor dimensions
        vx_size dimOutput[4]    // output tensor dimensions
    );

vx_graph annCreateGraph(
        vx_context context,     // OpenVX context
        vx_tensor input,        // input tensor
        vx_tensor output,       // output tensor
        const char * dataFolder // folder with weights and biases
    );
or
vx_graph annCreateGraphWithInputImage(
        vx_context context,     // OpenVX context
        vx_image input,         // input image (RGB or U8)
        vx_tensor output,       // output tensor
        const char * dataFolder // folder with weights and biases
    );
or
vx_graph annCreateGraphWithInputImageWithArgmaxTensor(
        vx_context context,     // OpenVX context
        vx_image input,         // input image (RGB or U8)
        vx_tensor output,       // output tensor
        const char * dataFolder // folder with weights and biases
    );
or
vx_graph annCreateGraphWithInputImageWithArgmaxImage(
        vx_context context,     // OpenVX context
        vx_image input,         // input image (RGB or U8)
        vx_image output,        // output image (U8)
        const char * dataFolder // folder with weights and biases
    );
or
vx_graph annCreateGraphWithInputImageWithArgmaxImageWithLut(
        vx_context context,     // OpenVX context
        vx_image input,         // input image (RGB or U8)
        vx_image output,        // output image (RGB)
        const char * dataFolder // folder with weights and biases
    );

Command-line Usage

  % caffe2openvx
        [options]
        <net.prototxt|net.caffemodel>
        [n c H W [type fixed-point-position [convert-policy round-policy]]]

option|description ——|———– –[no-]error-messages | do/don’t enable error messages (default: ON) –[no-]virtual-buffers | do/don’t use virtual buffers (default: ON) –[no-]generate-gdf | do/don’t generate RunVX GDF with weight/bias initialization (default: ON) –[no-]generate-vx-code | do/don’t generate OpenVX C Code with weight/bias initialization (default: ON) –output-dir | specify output folder for weights/biases, GDF, and OpenVX C Code (default: current) --input-rgb | convert input from RGB image into tensor using (a*x+b) conversion: rev=(BGR?1:0) --input-u8 | convert input from U8 image into tensor using (a*x+b) conversion --argmax-tensor u8|u16 k | return argmax output with specified tensor type and top_k --argmax-image u8|u16 | return argmax output with specified image type --argmax-lut | argmax color table: one R G B entry per label --flags | specify custom flags (default: 0)

Example

Make sure that all executables and libraries are in PATH and LD_LIBRARY_PATH environment variables.

% export PATH=$PATH:/opt/rocm/mivisionx/bin
% export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/rocm/mivisionx/lib

Below log outlines a simple use-case with inference generator.

% caffe2openvx weights.caffemodel 1 3 32 32
% caffe2openvx deploy.prototxt 1 3 32 32
% ls
CMakeLists.txt   annmodule.txt   cmake              weights
annmodule.cpp    anntest.cpp     deploy.prototxt    weights.caffemodel
annmodule.h      bias            net.gdf
% mkdir build
% cd build
% cmake ..
% make
% cd ..
% ls build
CMakeCache.txt  Makefile        cmake_install.cmake
CMakeFiles      anntest         libannmodule.so
% ./build/anntest
OK: annGetTensorDimensions() => [input 32x32x3x32] [output 1x1x10x32]

The anntest.cpp is a simple program to initialize and run neural network using the annmodule library.