opencv/modules/dnn/src/opencl/detection_output.cl

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (c) 2016-2017 Fabian David Tschopp, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#define Dtype float
#define Dtype4 float4
__kernel void DecodeBBoxesCORNER(const int nthreads,
__global const Dtype* loc_data,
__global const Dtype* prior_data,
const int variance_encoded_in_target,
const int num_priors,
const int share_location,
const int num_loc_classes,
const int background_label_id,
const int clip_bbox,
const int locPredTransposed,
__global Dtype* bbox_data)
{
for (int index = get_global_id(0); index < nthreads; index += get_global_size(0))
{
Dtype bbox_xmin, bbox_ymin, bbox_xmax, bbox_ymax;
const int i = index % 4;
const int p = ((index / 4 / num_loc_classes) % num_priors) * 4;
const int c = (index / 4) % num_loc_classes;
int label = share_location ? -1 : c;
if (label == background_label_id)
return; // Ignore background class.
Dtype4 loc_vec = vload4(0, loc_data + index - i);
Dtype4 bbox_vec, prior_variance;
if (variance_encoded_in_target)
{
bbox_vec = loc_vec;
} else {
const int start_index = num_priors * 4 + p;
prior_variance = vload4(0, prior_data + start_index);
bbox_vec = loc_vec * prior_variance;
}
if (locPredTransposed)
{
bbox_ymin = bbox_vec.x;
bbox_xmin = bbox_vec.y;
bbox_ymax = bbox_vec.z;
bbox_xmax = bbox_vec.w;
} else {
bbox_xmin = bbox_vec.x;
bbox_ymin = bbox_vec.y;
bbox_xmax = bbox_vec.z;
bbox_ymax = bbox_vec.w;
}
Dtype4 prior_vec = vload4(0, prior_data + p);
Dtype val;
switch (i)
{
case 0:
val = prior_vec.x + bbox_xmin;
break;
case 1:
val = prior_vec.y + bbox_ymin;
break;
case 2:
val = prior_vec.z + bbox_xmax;
break;
case 3:
val = prior_vec.w + bbox_ymax;
break;
}
if (clip_bbox)
val = max(min(val, (Dtype)1.), (Dtype)0.);
bbox_data[index] = val;
}
}
__kernel void DecodeBBoxesCENTER_SIZE(const int nthreads,
__global const Dtype* loc_data,
__global const Dtype* prior_data,
const int variance_encoded_in_target,
const int num_priors,
const int share_location,
const int num_loc_classes,
const int background_label_id,
const int clip_bbox,
const int locPredTransposed,
__global Dtype* bbox_data)
{
for (int index = get_global_id(0); index < nthreads; index += get_global_size(0))
{
Dtype bbox_xmin, bbox_ymin, bbox_xmax, bbox_ymax;
const int i = index % 4;
const int p = ((index / 4 / num_loc_classes) % num_priors) * 4;
const int c = (index / 4) % num_loc_classes;
int label = share_location ? -1 : c;
if (label == background_label_id)
return; // Ignore background class.
Dtype4 loc_vec = vload4(0, loc_data + index - i);
Dtype4 bbox_vec, prior_variance;
if (variance_encoded_in_target)
{
bbox_vec = loc_vec;
} else {
const int start_index = num_priors * 4 + p;
prior_variance = vload4(0, prior_data + start_index);
bbox_vec = loc_vec * prior_variance;
}
if (locPredTransposed)
{
bbox_ymin = bbox_vec.x;
bbox_xmin = bbox_vec.y;
bbox_ymax = bbox_vec.z;
bbox_xmax = bbox_vec.w;
} else {
bbox_xmin = bbox_vec.x;
bbox_ymin = bbox_vec.y;
bbox_xmax = bbox_vec.z;
bbox_ymax = bbox_vec.w;
}
Dtype4 prior_vec = vload4(0, prior_data + p);
Dtype prior_width = prior_vec.z - prior_vec.x;
Dtype prior_height = prior_vec.w - prior_vec.y;
Dtype prior_center_x = (prior_vec.x + prior_vec.z) * .5;
Dtype prior_center_y = (prior_vec.y + prior_vec.w) * .5;
Dtype decode_bbox_center_x, decode_bbox_center_y;
Dtype decode_bbox_width, decode_bbox_height;
decode_bbox_center_x = bbox_xmin * prior_width + prior_center_x;
decode_bbox_center_y = bbox_ymin * prior_height + prior_center_y;
decode_bbox_width = exp(bbox_xmax) * prior_width;
decode_bbox_height = exp(bbox_ymax) * prior_height;
Dtype val;
switch (i)
{
case 0:
val = decode_bbox_center_x - decode_bbox_width * .5;
break;
case 1:
val = decode_bbox_center_y - decode_bbox_height * .5;
break;
case 2:
val = decode_bbox_center_x + decode_bbox_width * .5;
break;
case 3:
val = decode_bbox_center_y + decode_bbox_height * .5;
break;
}
if (clip_bbox)
val = max(min(val, (Dtype)1.), (Dtype)0.);
bbox_data[index] = val;
}
}