void example_explore_parameters(vx_context context, vx_kernel kernel)
{
vx_uint32 p, numParams = 0;
vx_graph graph = vxCreateGraph(context);
vx_node node = vxCreateGenericNode(graph, kernel);
vxQueryKernel(kernel, VX_KERNEL_PARAMETERS, &numParams, sizeof(numParams));
for (p = 0; p < numParams; p++)
{
//! [Getting the ref]
vx_parameter param = vxGetParameterByIndex(node, p);
vx_reference ref;
vxQueryParameter(param, VX_PARAMETER_REF, &ref, sizeof(ref));
//! [Getting the ref]
if (ref)
{
//! [Getting the type]
vx_enum type;
vxQueryParameter(param, VX_PARAMETER_TYPE, &type, sizeof(type));
/* cast the ref to the correct vx_<type>. Atomics are now vx_scalar */
//! [Getting the type]
}
vxReleaseParameter(¶m);
}
vxReleaseNode(&node);
vxReleaseGraph(&graph);
}
vx_status vxuHarrisScore(vx_context context, vx_image gx,
vx_image gy,
vx_scalar sensitivity,
vx_scalar block_size,
vx_image score)
{
vx_status status = VX_FAILURE;
vx_graph graph = vxCreateGraph(context);
if (graph)
{
vx_node node = vxHarrisScoreNode(graph, gx, gy, sensitivity, block_size, score);
if (node)
{
status = vxVerifyGraph(graph);
if (status == VX_SUCCESS)
{
status = vxProcessGraph(graph);
}
vxReleaseNode(&node);
}
vxClearLog((vx_reference)graph);
vxReleaseGraph(&graph);
}
return status;
}
//! [vxu]
vx_status vxuXYZ(vx_context context, vx_image input, vx_uint32 value, vx_image output, vx_array temp)
{
vx_status status = VX_FAILURE;
vx_graph graph = vxCreateGraph(context);
if (graph)
{
vx_node node = vxXYZNode(graph, input, value, output, temp);
if (node)
{
status = vxVerifyGraph(graph);
if (status == VX_SUCCESS)
{
status = vxProcessGraph(graph);
}
vxReleaseNode(&node);
}
vxReleaseGraph(&graph);
}
return status;
}
vx_status vxuLaplacian3x3(vx_context context, vx_image input, vx_image output)
{
vx_status status = VX_FAILURE;
vx_graph graph = vxCreateGraph(context);
if (graph)
{
vx_node node = vxLaplacian3x3Node(graph, input, output);
if (node)
{
status = vxVerifyGraph(graph);
if (status == VX_SUCCESS)
{
status = vxProcessGraph(graph);
}
vxReleaseNode(&node);
}
vxClearLog((vx_reference)graph);
vxReleaseGraph(&graph);
}
return status;
}
vx_status vxuNonMaxSuppression(vx_context context, vx_image mag, vx_image phase, vx_image edge)
{
vx_status status = VX_SUCCESS;
vx_graph graph = vxCreateGraph(context);
if (graph)
{
vx_node node = vxNonMaxSuppressionNode(graph, mag, phase, edge);
if (node)
{
status = vxVerifyGraph(graph);
if (status == VX_SUCCESS)
{
status = vxProcessGraph(graph);
}
vxReleaseNode(&node);
}
vxClearLog((vx_reference)graph);
vxReleaseGraph(&graph);
}
return status;
}
vx_status vxuSobelMxN(vx_context context, vx_image input, vx_scalar win, vx_image gx, vx_image gy)
{
vx_status status = VX_FAILURE;
vx_graph graph = vxCreateGraph(context);
if (graph)
{
vx_node node = vxSobelMxNNode(graph, input, win, gx, gy);
if (node)
{
status = vxVerifyGraph(graph);
if (status == VX_SUCCESS)
{
status = vxProcessGraph(graph);
}
vxReleaseNode(&node);
}
vxClearLog((vx_reference)graph);
vxReleaseGraph(&graph);
}
return status;
}
vx_status vxuImageLister(vx_context context, vx_image input,
vx_array arr, vx_scalar num_points)
{
vx_status status = VX_FAILURE;
vx_graph graph = vxCreateGraph(context);
if (graph)
{
vx_node node = vxImageListerNode(graph, input, arr, num_points);
if (node)
{
status = vxVerifyGraph(graph);
if (status == VX_SUCCESS)
{
status = vxProcessGraph(graph);
}
vxReleaseNode(&node);
}
vxClearLog((vx_reference)graph);
vxReleaseGraph(&graph);
}
return status;
}
int main(void) {
vx_context context = vxCreateContext();
vx_uint8 value = 8;
vx_graph graph = vxCreateGraph(context);
vx_image images[] = {
vxCreateUniformImage(context, 640, 480, VX_DF_IMAGE_U8, &value),
vxCreateImage(context, 640, 480, VX_DF_IMAGE_U8)
};
vx_image intermediate_images[] = {
vxCreateVirtualImage(graph, 0, 0, VX_DF_IMAGE_S16)
};
/*Create the depth conversion nodes*/
vx_uint32 uint_value2 = 0;
vx_scalar vx_value2 = vxCreateScalar(context, VX_TYPE_INT32, &uint_value2);
vx_uint32 uint_value1 = 0;
vx_scalar vx_value1 = vxCreateScalar(context, VX_TYPE_INT32, &uint_value1);
/* The order in which these two nodes are created should not matter. */
vxConvertDepthNode(graph, intermediate_images[0], images[1],
VX_CONVERT_POLICY_SATURATE, vx_value2);
vxConvertDepthNode(graph, images[0], intermediate_images[0],
VX_CONVERT_POLICY_SATURATE, vx_value1);
vx_status status = vxVerifyGraph(graph);
if (status == VX_SUCCESS) {
status = vxProcessGraph(graph);
}
if (status != VX_SUCCESS) {
fprintf(stderr, "badness\n");
abort ();
}
exit (0);
}
vx_status vxuEuclideanNonMax(vx_context context, vx_image input,
vx_scalar strength_thresh,
vx_scalar min_distance,
vx_image output)
{
vx_status status = VX_FAILURE;
vx_graph graph = vxCreateGraph(context);
if (graph)
{
vx_node node = vxEuclideanNonMaxNode(graph, input, strength_thresh, min_distance, output);
if (node)
{
status = vxVerifyGraph(graph);
if (status == VX_SUCCESS)
{
status = vxProcessGraph(graph);
}
vxReleaseNode(&node);
}
vxClearLog((vx_reference)graph);
vxReleaseGraph(&graph);
}
return status;
}
////////
// main() has all the OpenVX application code for this exercise.
// Command-line usage:
// % solution_exercise3 [<video-sequence>|<camera-device-number>]
// When neither video sequence nor camera device number is specified,
// it defaults to the video sequence in "PETS09-S1-L1-View001.avi".
int main( int argc, char * argv[] )
{
// Get default video sequence when nothing is specified on command-line and
// instantiate OpenCV GUI module for reading input RGB images and displaying
// the image with OpenVX results
const char * video_sequence = argv[1];
CGuiModule gui( video_sequence );
// Try grab first video frame from the sequence using cv::VideoCapture
// and check if video frame is available
if( !gui.Grab() )
{
printf( "ERROR: input has no video\n" );
return 1;
}
////////
// Set the application configuration parameters. Note that input video
// sequence is an 8-bit RGB image with dimensions given by gui.GetWidth()
// and gui.GetHeight(). The parameters for the tensors are:
// tensor_dims - 3 dimensions of tensor [3 x <width> x <height>]
// tensor_input_fixed_point_pos - fixed-point position for input tensor
// tensor_output_fixed_point_pos - fixed-point position for output tensor
vx_uint32 width = gui.GetWidth();
vx_uint32 height = gui.GetHeight();
vx_size tensor_dims[3] = { width, height, 3 }; // 3 channels (RGB)
vx_uint8 tensor_input_fixed_point_pos = 5; // input[-128..127] will be mapped to -4..3.96875
vx_uint8 tensor_output_fixed_point_pos = 7; // output[-1..1] will be mapped to -128 to 128
////////
// Create the OpenVX context and make sure returned context is valid and
// register the log_callback to receive messages from OpenVX framework.
vx_context context = vxCreateContext();
ERROR_CHECK_OBJECT( context );
vxRegisterLogCallback( context, log_callback, vx_false_e );
////////
// Register user kernels with the context.
//
// TODO:********
// 1. Register user kernel with context by calling your implementation of "registerUserKernel()".
ERROR_CHECK_STATUS( registerUserKernel( context ) );
////////
// Create OpenVX tensor objects for input and output
//
// TODO:********
// 1. Create tensor objects using tensor_dims, tensor_input_fixed_point_pos, and
// tensor_output_fixed_point_pos
vx_tensor input_tensor = vxCreateTensor( context, 3, tensor_dims, VX_TYPE_INT16, tensor_input_fixed_point_pos );
vx_tensor output_tensor = vxCreateTensor( context, 3, tensor_dims, VX_TYPE_INT16, tensor_output_fixed_point_pos );
ERROR_CHECK_OBJECT( input_tensor );
ERROR_CHECK_OBJECT( output_tensor );
////////
// Create, build, and verify the graph with user kernel node.
//
// TODO:********
// 1. Build a graph with just one node created using userTensorCosNode()
vx_graph graph = vxCreateGraph( context );
ERROR_CHECK_OBJECT( graph );
vx_node cos_node = userTensorCosNode( graph, input_tensor, output_tensor );
ERROR_CHECK_OBJECT( cos_node );
ERROR_CHECK_STATUS( vxReleaseNode( &cos_node ) );
ERROR_CHECK_STATUS( vxVerifyGraph( graph ) );
////////
// Process the video sequence frame by frame until the end of sequence or aborted.
cv::Mat bgrMatForOutputDisplay( height, width, CV_8UC3 );
for( int frame_index = 0; !gui.AbortRequested(); frame_index++ )
{
////////
// Copy input RGB frame from OpenCV into input_tensor with UINT8 to Q10.5 (INT16) conversion.
// In order to do this, vxMapTensorPatch API (see "vx_ext_amd.h").
//
// TODO:********
// 1. Use vxMapTensorPatch API for access to input tensor object for writing
// 2. Copy UINT8 data from OpenCV RGB image to tensor object
// 3. Use vxUnmapTensorPatch API to return control of buffer back to framework
vx_uint8 * cv_rgb_image_buffer = gui.GetBuffer();
vx_size rgb_stride = gui.GetStride();
vx_size zeros[3] = { 0 };
vx_size tensor_stride[3];
vx_map_id map_id;
vx_uint8 * buf;
ERROR_CHECK_STATUS( vxMapTensorPatch( input_tensor,
3, zeros, tensor_dims,
&map_id, tensor_stride,
(void **)&buf, VX_WRITE_ONLY, VX_MEMORY_TYPE_HOST, 0 ) );
for( vx_size c = 0; c < 3; c++ )
{
for( vx_size y = 0; y < height; y++ )
{
const vx_uint8 * img = cv_rgb_image_buffer + y * rgb_stride + c;
vx_int16 * inp = (vx_int16 *)(buf + y * tensor_stride[1] + c * tensor_stride[2]);
for( vx_size x = 0; x < width; x++ )
{
// convert 0..255 to Q10.5 [-4..3.96875 range] fixed-point format
inp[x] = (vx_int16)img[x * 3] - 128;
}
}
}
ERROR_CHECK_STATUS( vxUnmapTensorPatch( input_tensor, map_id ) );
////////
// Now that input tensor is ready, just run the graph.
//
// TODO:********
// 1. Call vxProcessGraph to execute the tensor_cos kernel in graph
ERROR_CHECK_STATUS( vxProcessGraph( graph ) );
////////
// Display the output tensor object as RGB image
//
// TODO:********
// 1. Use vxMapTensorPatch API for access to output tensor object for reading
// 2. Copy tensor object data into OpenCV RGB image
// 3. Use vxUnmapTensorPatch API to return control of buffer back to framework
ERROR_CHECK_STATUS( vxMapTensorPatch( output_tensor,
3, zeros, tensor_dims,
&map_id, tensor_stride,
(void **)&buf, VX_WRITE_ONLY, VX_MEMORY_TYPE_HOST, 0 ) );
vx_uint8 * cv_bgr_image_buffer = bgrMatForOutputDisplay.data;
vx_size bgr_stride = bgrMatForOutputDisplay.step;
for( vx_size c = 0; c < 3; c++ )
{
for( vx_size y = 0; y < height; y++ )
{
const vx_int16 * out = (const vx_int16 *)(buf + y * tensor_stride[1] + c * tensor_stride[2]);
vx_uint8 * img = cv_bgr_image_buffer + y * bgr_stride + (2 - c); // (2 - c) for RGB to BGR conversion
for( vx_size x = 0; x < width; x++ )
{
// scale convert Q8.7 [-1..1 range] fixed-point format to 0..255 with saturation
vx_int16 value = out[x] + 128;
value = value > 255 ? 255 : value; // saturation needed
img[x * 3] = (vx_uint8)value;
}
}
}
#if ENABLE_DISPLAY
cv::imshow( "Cosine", bgrMatForOutputDisplay );
#endif
ERROR_CHECK_STATUS( vxUnmapTensorPatch( output_tensor, map_id ) );
////////
// Display the results and grab the next input RGB frame for the next iteration.
char text[128];
sprintf( text, "Keyboard ESC/Q-Quit SPACE-Pause [FRAME %d] [fixed_point_pos input:%d output:%d]", frame_index, tensor_input_fixed_point_pos, tensor_output_fixed_point_pos );
gui.DrawText( 0, 16, text );
gui.Show();
if( !gui.Grab() )
{
// Terminate the processing loop if the end of sequence is detected.
gui.WaitForKey();
break;
}
}
////////
// To release an OpenVX object, you need to call vxRelease<Object> API which takes a pointer to the object.
// If the release operation is successful, the OpenVX framework will reset the object to NULL.
//
// TODO:****
// 1. Release graph and tensor objects
ERROR_CHECK_STATUS( vxReleaseGraph( &graph ) );
ERROR_CHECK_STATUS( vxReleaseTensor( &input_tensor ) );
ERROR_CHECK_STATUS( vxReleaseTensor( &output_tensor ) );
ERROR_CHECK_STATUS( vxReleaseContext( &context ) );
return 0;
}
int main(int argc, char *argv[]) {
vx_status status = VX_FAILURE;
vx_context context = vxCreateContext();
if (argc < 2) {
usage(argv[0]);
goto relCtx;
}
vx_char *srcfilename = argv[1];
printf("src img: %s\n", srcfilename);
FILE *fp = fopen(srcfilename, "r");
if (!fp) {
goto relCtx;
}
char pgmstr[1024];
unsigned int n;
n = fread(pgmstr, 1, sizeof(pgmstr), fp);
if (n != sizeof(pgmstr)) {
goto relClose;
}
const char delim = '\n';
const char *token = NULL;
unsigned int width, height;
// PGM P5 magic string
token = strtok(pgmstr, &delim);
// PGM author
token = strtok(NULL, &delim);
// PGM image size
token = strtok(NULL, &delim);
sscanf(token, "%u %u", &width, &height);
printf("width:%u height:%u\n", width, height);
status = vxGetStatus((vx_reference)context);
if (status != VX_SUCCESS) {
fprintf(stderr, "error: vxCreateContext\n");
goto relClose;
}
vx_rectangle_t rect = {1, 1, width + 1, height + 1};
vx_uint32 i = 0;
vx_image images[] = {
vxCreateImage(context, width + 2, height + 2, VX_DF_IMAGE_U8), // 0:input
vxCreateImageFromROI(images[0], &rect), // 1:ROI input
vxCreateImage(context, width, height, VX_DF_IMAGE_U8), // 2:box
vxCreateImage(context, width, height, VX_DF_IMAGE_U8), // 3:gaussian
vxCreateImage(context, width, height, VX_DF_IMAGE_U8), // 4:alpha
vxCreateImage(context, width, height, VX_DF_IMAGE_S16),// 5:add
};
vx_float32 a = 0.5f;
vx_scalar alpha = vxCreateScalar(context, VX_TYPE_FLOAT32, &a);
status |= vxLoadKernels(context, "openvx-tiling");
status |= vxLoadKernels(context, "openvx-debug");
if (status != VX_SUCCESS) {
fprintf(stderr, "error: vxLoadKernels %d\n", status);
goto relImg;
}
vx_graph graph = vxCreateGraph(context);
status = vxGetStatus((vx_reference)context);
if (status != VX_SUCCESS) {
fprintf(stderr, "error: vxGetStatus\n");
goto relKern;
}
ax_node_t axnodes[] = {
{ vxFReadImageNode(graph, srcfilename, images[1]), "Read" },
{ vxTilingBoxNode(graph, images[1], images[2], 5, 5), "Box" },
{ vxFWriteImageNode(graph, images[2], "ot_box.pgm"), "Write" },
{ vxTilingGaussianNode(graph, images[1], images[3]), "Gaussian" },
{ vxFWriteImageNode(graph, images[3], "ot_gauss.pgm"), "Write" },
{ vxTilingAlphaNode(graph, images[1], alpha, images[4]), "Alpha" },
{ vxFWriteImageNode(graph, images[4], "ot_alpha.pgm"), "Write" },
{ vxTilingAddNode(graph, images[1], images[4], images[5]), "Add" },
{ vxFWriteImageNode(graph, images[5], "ot_add.pgm"), "Write" },
};
for (i = 0; i < dimof(axnodes); i++) {
if (axnodes[i].node == 0) {
fprintf(stderr, "error: Failed to create node[%u]\n", i);
status = VX_ERROR_INVALID_NODE;
goto relNod;
}
}
status = vxVerifyGraph(graph);
if (status != VX_SUCCESS) {
fprintf(stderr, "error: vxVerifyGraph %d\n", status);
goto relNod;
}
status = vxProcessGraph(graph);
if (status != VX_SUCCESS) {
fprintf(stderr, "error: vxProcessGraph %d\n", status);
goto relNod;
}
// perf timings
vx_perf_t perf_node;
vx_perf_t perf_graph;
vxQueryGraph(graph, VX_GRAPH_ATTRIBUTE_PERFORMANCE, &perf_graph, sizeof(perf_graph));
axPrintPerf("Graph", &perf_graph);
for (i = 0; i < dimof(axnodes); ++i) {
vxQueryNode(axnodes[i].node, VX_NODE_ATTRIBUTE_PERFORMANCE, &perf_node, sizeof(perf_node));
axPrintPerf(axnodes[i].name, &perf_node);
}
relNod:
for (i = 0; i < dimof(axnodes); i++) {
vxReleaseNode(&axnodes[i].node);
}
vxReleaseGraph(&graph);
relKern:
relImg:
for (i = 0; i < dimof(images); i++) {
vxReleaseImage(&images[i]);
}
relClose:
fclose(fp);
relCtx:
vxReleaseContext(&context);
printf("%s::main() returns = %d\n", argv[0], status);
return (int)status;
}
static vx_status VX_CALLBACK vxHarrisInitializer(vx_node node, vx_reference parameters[], vx_uint32 num)
{
vx_status status = VX_FAILURE;
if (num == dimof(harris_kernel_params))
{
vx_image src = (vx_image)parameters[0];
vx_scalar str = (vx_scalar)parameters[1];
vx_scalar min = (vx_scalar)parameters[2];
vx_scalar sen = (vx_scalar)parameters[3];
vx_scalar win = (vx_scalar)parameters[4];
vx_scalar blk = (vx_scalar)parameters[5];
vx_array arr = (vx_array)parameters[6];
vx_scalar num_corners = (vx_scalar)parameters[7];
vx_context c = vxGetContext((vx_reference)node);
vx_graph g = vxCreateGraph(c);
vxLoadKernels(c, "openvx-extras");
vxLoadKernels(c, "openvx-debug");
if (g)
{
vx_uint32 i = 0;
vx_int32 ds = 4;
vx_scalar shift = vxCreateScalar(c, VX_TYPE_INT32, &ds);
vx_image virts[] = {
vxCreateVirtualImage(g, 0, 0, VX_DF_IMAGE_VIRT), // Gx
vxCreateVirtualImage(g, 0, 0, VX_DF_IMAGE_VIRT), // Gy
vxCreateVirtualImage(g, 0, 0, VX_DF_IMAGE_VIRT), // Score
vxCreateVirtualImage(g, 0, 0, VX_DF_IMAGE_VIRT), // Suppressed
vxCreateVirtualImage(g, 0, 0, VX_DF_IMAGE_U8), // Shifted Suppressed Log10
};
vx_node nodes[] = {
vxSobelMxNNode(g, src, win, virts[0], virts[1]),
vxHarrisScoreNode(g, virts[0], virts[1], sen, blk, virts[2]),
vxEuclideanNonMaxNode(g, virts[2], str, min, virts[3]),
vxImageListerNode(g, virts[3], arr, num_corners),
#if defined(OPENVX_DEBUGGING)
vxConvertDepthNode(g,virts[3],virts[4],VX_CONVERT_POLICY_WRAP,shift),
vxFWriteImageNode(g,virts[4],"oharris_strength_power_up4.pgm"),
#endif
};
status = VX_SUCCESS;
status |= vxAddParameterToGraphByIndex(g, nodes[0], 0); // src
status |= vxAddParameterToGraphByIndex(g, nodes[2], 1); // str
status |= vxAddParameterToGraphByIndex(g, nodes[2], 2); // min
status |= vxAddParameterToGraphByIndex(g, nodes[1], 2); // sen
status |= vxAddParameterToGraphByIndex(g, nodes[0], 1); // win
status |= vxAddParameterToGraphByIndex(g, nodes[1], 3); // blk
status |= vxAddParameterToGraphByIndex(g, nodes[3], 1); // arr
status |= vxAddParameterToGraphByIndex(g, nodes[3], 2); // num_corners
for (i = 0; i < dimof(nodes); i++)
{
vxReleaseNode(&nodes[i]);
}
for (i = 0; i < dimof(virts); i++)
{
vxReleaseImage(&virts[i]);
}
vxReleaseScalar(&shift);
status |= vxVerifyGraph(g);
VX_PRINT(VX_ZONE_INFO, "Status from Child Graph = %d\n", status);
if (status == VX_SUCCESS)
{
status = vxSetChildGraphOfNode(node, g);
}
else
{
vxReleaseGraph(&g);
}
}
}
return status;
}
static VALUE Graph_init(VALUE self)
{
Check_Type(self, T_DATA);
DATA_PTR(self) = (void *)vxCreateGraph(context);
return Qnil;
}
static vx_status VX_CALLBACK vxHalfscaleGaussianInitializer(vx_node node, const vx_reference *parameters, vx_uint32 num)
{
vx_status status = VX_ERROR_INVALID_PARAMETERS;
if (num == 3)
{
vx_image input = (vx_image)parameters[0];
vx_image output = (vx_image)parameters[1];
vx_int32 kernel_size = 3;
vx_convolution convolution = 0;
vx_context context = vxGetContext((vx_reference)node);
vx_graph graph = vxCreateGraph(context);
if (vxGetStatus((vx_reference)graph) == VX_SUCCESS)
{
vx_uint32 i;
/* We have a child-graph; we want to make sure the parent
graph is recognized as a valid scope for sake of virtual
image parameters. */
graph->parentGraph = node->graph;
vxReadScalarValue((vx_scalar)parameters[2], &kernel_size);
if (kernel_size == 3 || kernel_size == 5)
{
if (kernel_size == 5)
{
convolution = vxCreateGaussian5x5Convolution(context);
}
if (kernel_size == 3 || convolution)
{
vx_image virt = vxCreateVirtualImage(graph, 0, 0, VX_DF_IMAGE_U8);
vx_node nodes[] = {
kernel_size == 3 ? vxGaussian3x3Node(graph, input, virt) : vxConvolveNode(graph, input, convolution, virt),
vxScaleImageNode(graph, virt, output, VX_INTERPOLATION_TYPE_NEAREST_NEIGHBOR),
};
vx_border_mode_t borders;
vxQueryNode(node, VX_NODE_ATTRIBUTE_BORDER_MODE, &borders, sizeof(borders));
for (i = 0; i < dimof(nodes); i++) {
vxSetNodeAttribute(nodes[i], VX_NODE_ATTRIBUTE_BORDER_MODE, &borders, sizeof(borders));
}
status = VX_SUCCESS;
status |= vxAddParameterToGraphByIndex(graph, nodes[0], 0); /* input image */
status |= vxAddParameterToGraphByIndex(graph, nodes[1], 1); /* output image */
status |= vxAddParameterToGraphByIndex(graph, node, 2); /* gradient size - refer to self to quiet sub-graph validator */
status |= vxVerifyGraph(graph);
/* release our references, the graph will hold it's own */
for (i = 0; i < dimof(nodes); i++) {
vxReleaseNode(&nodes[i]);
}
if (convolution) vxReleaseConvolution(&convolution);
vxReleaseImage(&virt);
status |= vxSetChildGraphOfNode(node, graph);
}
}
vxReleaseGraph(&graph);
}
}
return status;
}
/*!
* \brief An example of an super resolution algorithm.
* \ingroup group_example
*/
int example_super_resolution(int argc, char *argv[])
{
vx_status status = VX_SUCCESS;
vx_uint32 image_index = 0, max_num_images = 4;
vx_uint32 width = 640;
vx_uint32 i = 0;
vx_uint32 winSize = 32;
vx_uint32 height = 480;
vx_int32 sens_thresh = 20;
vx_float32 alpha = 0.2f;
vx_float32 tau = 0.5f;
vx_enum criteria = VX_TERM_CRITERIA_BOTH; // lk params
vx_float32 epsilon = 0.01;
vx_int32 num_iterations = 10;
vx_bool use_initial_estimate = vx_true_e;
vx_int32 min_distance = 5; // harris params
vx_float32 sensitivity = 0.04;
vx_int32 gradient_size = 3;
vx_int32 block_size = 3;
vx_context context = vxCreateContext();
vx_scalar alpha_s = vxCreateScalar(context, VX_TYPE_FLOAT32, &alpha);
vx_scalar tau_s = vxCreateScalar(context, VX_TYPE_FLOAT32, &tau);
vx_matrix matrix_forward = vxCreateMatrix(context, VX_TYPE_FLOAT32, 3, 3);
vx_matrix matrix_backwords = vxCreateMatrix(context, VX_TYPE_FLOAT32, 3, 3);
vx_array old_features = vxCreateArray(context, VX_TYPE_KEYPOINT, 1000);
vx_array new_features = vxCreateArray(context, VX_TYPE_KEYPOINT, 1000);
vx_scalar epsilon_s = vxCreateScalar(context, VX_TYPE_FLOAT32, &epsilon);
vx_scalar num_iterations_s = vxCreateScalar(context, VX_TYPE_INT32, &num_iterations);
vx_scalar use_initial_estimate_s = vxCreateScalar(context, VX_TYPE_BOOL, &use_initial_estimate);
vx_scalar min_distance_s = vxCreateScalar(context, VX_TYPE_INT32, &min_distance);
vx_scalar sensitivity_s = vxCreateScalar(context, VX_TYPE_FLOAT32, &sensitivity);
vx_scalar sens_thresh_s = vxCreateScalar(context, VX_TYPE_INT32, &sens_thresh);
vx_scalar num_corners = vxCreateScalar(context, VX_TYPE_SIZE, NULL);
if (vxGetStatus((vx_reference)context) == VX_SUCCESS)
{
vx_image images[] =
{ vxCreateImage(context, width, height, VX_DF_IMAGE_UYVY), // index 0:
vxCreateImage(context, width, height, VX_DF_IMAGE_U8), // index 1: Get Y channel
vxCreateImage(context, width * 2, height * 2, VX_DF_IMAGE_U8), // index 2: scale up to high res.
vxCreateImage(context, width * 2, height * 2, VX_DF_IMAGE_U8), // index 3: back wrap: transform to the original Image.
vxCreateImage(context, width * 2, height * 2, VX_DF_IMAGE_U8), // index 4: guassian blur
vxCreateImage(context, width, height, VX_DF_IMAGE_U8), // index 5: scale down
vxCreateImage(context, width, height, VX_DF_IMAGE_S16), // index 6: Subtract the transformed Image with original moved Image
vxCreateImage(context, width * 2, height * 2, VX_DF_IMAGE_S16), // index 7: Scale Up the delta image.
vxCreateImage(context, width * 2, height * 2, VX_DF_IMAGE_S16), // index 8: Guassian blur the delta Image
vxCreateImage(context, width * 2, height * 2, VX_DF_IMAGE_S16), // index 9: forward wrap: tranform the deltas back to the high res Image
vxCreateImage(context, width * 2, height * 2, VX_DF_IMAGE_U8), // index 10: accumulate sum?
vxCreateImage(context, width, height, VX_DF_IMAGE_U8), // index 11: Get U channel
vxCreateImage(context, width * 2, height * 2, VX_DF_IMAGE_U8), // index 12: scale up to high res.
vxCreateImage(context, width, height, VX_DF_IMAGE_U8), // index 13: Get V channel
vxCreateImage(context, width * 2, height * 2, VX_DF_IMAGE_U8), // index 14: scale up to high res.
vxCreateImage(context, width, height, VX_DF_IMAGE_UYVY), // index 15: output image
vxCreateImage(context, width * 2, height * 2, VX_DF_IMAGE_U8), // index 16: original y image scaled
vxCreateImage(context, width * 2, height * 2, VX_DF_IMAGE_U8), // index 17: difference image for last calculation
};
vx_pyramid pyramid_new = vxCreatePyramid(context, 4, 2, width, height, VX_DF_IMAGE_U8);
vx_pyramid pyramid_old = vxCreatePyramid(context, 4, 2, width, height, VX_DF_IMAGE_U8);
vx_graph graphs[] =
{ vxCreateGraph(context), vxCreateGraph(context), vxCreateGraph(context), vxCreateGraph(context), };
vxLoadKernels(context, "openvx-debug");
if (vxGetStatus((vx_reference)graphs[0]) == VX_SUCCESS)
{
vxChannelExtractNode(graphs[0], images[0], VX_CHANNEL_Y, images[1]); // One iteration of super resolution calculation
vxScaleImageNode(graphs[0], images[1], images[2], VX_INTERPOLATION_TYPE_BILINEAR);
vxWarpPerspectiveNode(graphs[0], images[2], matrix_forward, 0, images[3]);
vxGaussian3x3Node(graphs[0], images[3], images[4]);
vxScaleImageNode(graphs[0], images[4], images[5], VX_INTERPOLATION_TYPE_BILINEAR);
vxSubtractNode(graphs[0], images[5], images[16], VX_CONVERT_POLICY_SATURATE, images[6]);
vxScaleImageNode(graphs[0], images[6], images[7], VX_INTERPOLATION_TYPE_BILINEAR);
vxGaussian3x3Node(graphs[0], images[7], images[8]);
vxWarpPerspectiveNode(graphs[0], images[8], matrix_backwords, 0, images[9]);
vxAccumulateWeightedImageNode(graphs[0], images[9], alpha_s, images[10]);
}
if (vxGetStatus((vx_reference)graphs[1]) == VX_SUCCESS)
{
vxChannelExtractNode(graphs[1], images[0], VX_CHANNEL_Y, images[1]); // One iteration of super resolution calculation
vxGaussianPyramidNode(graphs[1], images[1], pyramid_new);
vxOpticalFlowPyrLKNode(graphs[1], pyramid_old, pyramid_new, old_features, old_features, new_features,
criteria, epsilon_s, num_iterations_s, use_initial_estimate_s, winSize);
}
if (vxGetStatus((vx_reference)graphs[2]) == VX_SUCCESS)
{
vxChannelExtractNode(graphs[2], images[0], VX_CHANNEL_Y, images[1]); // One iteration of super resolution calculation
vxHarrisCornersNode(graphs[2], images[1], sens_thresh_s, min_distance_s, sensitivity_s, gradient_size,
block_size, old_features, num_corners);
vxGaussianPyramidNode(graphs[2], images[1], pyramid_old);
vxScaleImageNode(graphs[2], images[1], images[16], VX_INTERPOLATION_TYPE_BILINEAR);
}
if (vxGetStatus((vx_reference)graphs[3]) == VX_SUCCESS)
{
vxSubtractNode(graphs[3], images[10], images[16], VX_CONVERT_POLICY_SATURATE, images[17]);
vxAccumulateWeightedImageNode(graphs[3], images[17], tau_s, images[16]);
vxChannelExtractNode(graphs[3], images[16], VX_CHANNEL_U, images[11]);
vxScaleImageNode(graphs[3], images[11], images[12], VX_INTERPOLATION_TYPE_BILINEAR); // upscale the u channel
vxChannelExtractNode(graphs[3], images[0], VX_CHANNEL_V, images[13]);
vxScaleImageNode(graphs[3], images[13], images[14], VX_INTERPOLATION_TYPE_BILINEAR); // upscale the v channel
vxChannelCombineNode(graphs[3], images[10], images[12], images[14], 0, images[15]); // recombine the channels
}
status = VX_SUCCESS;
status |= vxVerifyGraph(graphs[0]);
status |= vxVerifyGraph(graphs[1]);
status |= vxVerifyGraph(graphs[2]);
status |= vxVerifyGraph(graphs[3]);
if (status == VX_SUCCESS)
{
/* read the initial image in */
status |= vxuFReadImage(context, "c:\\work\\super_res\\superres_1_UYVY.yuv", images[0]);
/* compute the "old" pyramid */
status |= vxProcessGraph(graphs[2]);
/* for each input image, read it in and run graphs[1] and [0]. */
for (image_index = 1; image_index < max_num_images; image_index++)
{
char filename[256];
sprintf(filename, "c:\\work\\super_res\\superres_%d_UYVY.yuv", image_index + 1);
status |= vxuFReadImage(context, filename, images[0]);
status |= vxProcessGraph(graphs[1]);
userCalculatePerspectiveTransformFromLK(matrix_forward, matrix_backwords, old_features, new_features);
status |= vxProcessGraph(graphs[0]);
}
/* run the final graph */
status |= vxProcessGraph(graphs[3]);
/* save the output */
status |= vxuFWriteImage(context, images[15], "superres_UYVY.yuv");
}
vxReleaseGraph(&graphs[0]);
vxReleaseGraph(&graphs[1]);
vxReleaseGraph(&graphs[2]);
vxReleaseGraph(&graphs[3]);
for (i = 0; i < dimof(images); i++)
{
vxReleaseImage(&images[i]);
}
vxReleasePyramid(&pyramid_new);
vxReleasePyramid(&pyramid_old);
}
vxReleaseMatrix(&matrix_forward);
vxReleaseMatrix(&matrix_backwords);
vxReleaseScalar(&alpha_s);
vxReleaseScalar(&tau_s);
/* Release the context last */
vxReleaseContext(&context);
return status;
}
