f4334277
 Hu Chunming
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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
__kernel void logistic_activ(const int count,
__global const Dtype* src,
const int cell_size,
__global Dtype* dst)
{
for (int i = get_global_id(0); i < count; i += get_global_size(0))
{
int index = cell_size * i;
Dtype x = src[index + 4];
dst[index + 4] = 1.f / (1.f + exp(-x));
}
}
__kernel void softmax_activ(const int count,
__global const Dtype* src,
__global const Dtype* biasData,
const int cell_size,
const int classes,
const int classfix,
const int rows,
const int cols,
const int anchors,
const float thresh,
__global Dtype* dst)
{
for (int index = get_global_id(0); index < count; index += get_global_size(0))
{
int box_index = index * cell_size;
float largest = -FLT_MAX;
__global const Dtype *input = src + box_index + 5;
__global Dtype *output = dst + box_index + 5;
for (int i = 0; i < classes; ++i)
largest = fmax(largest, input[i]);
float sum = 0;
for (int i = 0; i < classes; ++i)
{
float e = exp((input[i] - largest));
sum += e;
output[i] = e;
}
int y = (index / (anchors * cols)) % rows;
int x = (index / anchors) % cols;
int a = index % anchors;
float scale = dst[box_index + 4];
if (classfix == -1 && scale < .5) scale = 0;
float v1 = src[box_index + 0];
float v2 = src[box_index + 1];
float l1 = 1.f / (1.f + exp(-v1));
float l2 = 1.f / (1.f + exp(-v2));
dst[box_index + 0] = (x + l1) / cols;
dst[box_index + 1] = (y + l2) / rows;
dst[box_index + 2] = exp(src[box_index + 2]) * biasData[2 * a] / cols;
dst[box_index + 3] = exp(src[box_index + 3]) * biasData[2 * a + 1] / rows;
for (int i = 0; i < classes; ++i)
{
float prob = scale * output[i] / sum;
output[i] = (prob > thresh) ? prob : 0;
}
}
}
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