darknet/src/im2col.c

172 lines
5.7 KiB
C
Raw Normal View History

2014-05-10 02:14:52 +04:00
#include "mini_blas.h"
#include <stdio.h>
2014-05-10 02:14:52 +04:00
2014-07-14 09:07:51 +04:00
inline float im2col_get_pixel(float *im, int height, int width, int channels,
int row, int col, int channel, int pad)
{
row -= pad;
col -= pad;
if (row < 0 || col < 0 ||
row >= height || col >= width) return 0;
return im[col + width*(row + channel*height)];
}
2014-05-10 02:14:52 +04:00
//From Berkeley Vision's Caffe!
//https://github.com/BVLC/caffe/blob/master/LICENSE
2014-07-17 21:14:59 +04:00
void im2col_cpu_batch(float* data_im,
2014-05-10 02:14:52 +04:00
const int batch, const int channels, const int height, const int width,
2014-07-14 09:07:51 +04:00
const int ksize, const int stride, int pad, float* data_col)
2014-05-10 02:14:52 +04:00
{
int c,h,w,b;
int height_col = (height - ksize) / stride + 1;
int width_col = (width - ksize) / stride + 1;
2014-07-14 09:07:51 +04:00
if (pad){
height_col = 1 + (height-1) / stride;
width_col = 1 + (width-1) / stride;
pad = ksize/2;
}
2014-05-10 02:14:52 +04:00
int channels_col = channels * ksize * ksize;
int im_size = height*width*channels;
//int col_size = height_col*width_col*channels_col;
2014-07-14 09:07:51 +04:00
for (b = 0; b < batch; ++b) {
for (c = 0; c < channels_col; ++c) {
2014-05-10 02:14:52 +04:00
int w_offset = c % ksize;
int h_offset = (c / ksize) % ksize;
int c_im = c / ksize / ksize;
2014-07-14 09:07:51 +04:00
for (h = 0; h < height_col; ++h) {
for (w = 0; w < width_col; ++w) {
int im_row = h_offset + h * stride;
int im_col = w_offset + w * stride;
int col_index = (c * height_col + h) * width_col + w + (batch-1) * c * height_col*width_col;
data_col[col_index] = im2col_get_pixel(data_im, height, width, channels,
2014-07-14 09:07:51 +04:00
im_row, im_col, c_im, pad);
2014-05-10 02:14:52 +04:00
}
}
}
data_im += im_size;
data_col+= channels_col;
2014-05-10 02:14:52 +04:00
}
}
2014-07-17 21:14:59 +04:00
//From Berkeley Vision's Caffe!
//https://github.com/BVLC/caffe/blob/master/LICENSE
void im2col_cpu(float* data_im,
const int channels, const int height, const int width,
const int ksize, const int stride, int pad, float* data_col)
{
int c,h,w;
int height_col = (height - ksize) / stride + 1;
int width_col = (width - ksize) / stride + 1;
if (pad){
height_col = 1 + (height-1) / stride;
width_col = 1 + (width-1) / stride;
pad = ksize/2;
}
int channels_col = channels * ksize * ksize;
for (c = 0; c < channels_col; ++c) {
int w_offset = c % ksize;
int h_offset = (c / ksize) % ksize;
int c_im = c / ksize / ksize;
for (h = 0; h < height_col; ++h) {
for (w = 0; w < width_col; ++w) {
int im_row = h_offset + h * stride;
int im_col = w_offset + w * stride;
int col_index = (c * height_col + h) * width_col + w;
data_col[col_index] = im2col_get_pixel(data_im, height, width, channels,
im_row, im_col, c_im, pad);
}
}
}
}
2014-05-10 02:14:52 +04:00
#ifdef GPU
#include "opencl.h"
#include <math.h>
cl_kernel get_im2col_kernel()
{
static int init = 0;
static cl_kernel im2col_kernel;
if(!init){
im2col_kernel = get_kernel("src/im2col.cl", "im2col", 0);
init = 1;
}
return im2col_kernel;
}
void im2col_ongpu(cl_mem data_im, const int batch,
const int channels, const int height, const int width,
const int ksize, const int stride, cl_mem data_col)
{
cl_setup();
cl_kernel im2col_kernel = get_im2col_kernel();
cl_command_queue queue = cl.queue;
cl_uint i = 0;
cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(data_im), (void*) &data_im);
cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(batch), (void*) &batch);
cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(channels), (void*) &channels);
cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(height), (void*) &height);
cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(width), (void*) &width);
cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(ksize), (void*) &ksize);
cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(stride), (void*) &stride);
cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(data_col), (void*) &data_col);
check_error(cl);
int height_col = (height - ksize) / stride + 1;
int width_col = (width - ksize) / stride + 1;
int channels_col = channels * ksize * ksize;
size_t global_size[2];
size_t local_size[2];
global_size[0] = batch;
global_size[1] = channels_col;
local_size[0] = height_col;
local_size[1] = width_col;
clEnqueueNDRangeKernel(queue, im2col_kernel, 2, 0,
global_size, local_size, 0, 0, 0);
check_error(cl);
}
void im2col_gpu(float *data_im,
const int batch, const int channels, const int height, const int width,
const int ksize, const int stride,
float *data_col)
{
cl_setup();
cl_context context = cl.context;
cl_command_queue queue = cl.queue;
size_t size = sizeof(float)*(channels*height*width*batch);
cl_mem im_gpu = clCreateBuffer(context,
CL_MEM_READ_ONLY|CL_MEM_COPY_HOST_PTR,
size, data_im, &cl.error);
check_error(cl);
int height_col = (height - ksize) / stride + 1;
int width_col = (width - ksize) / stride + 1;
int channels_col = channels * ksize * ksize;
size = sizeof(float)*(height_col*width_col*channels_col*batch);
cl_mem col_gpu = clCreateBuffer(context,
CL_MEM_WRITE_ONLY|CL_MEM_COPY_HOST_PTR,
size, data_col, &cl.error);
check_error(cl);
im2col_ongpu(im_gpu, batch, channels, height, width,
ksize, stride, col_gpu);
clEnqueueReadBuffer(queue, col_gpu, CL_TRUE, 0, size, data_col, 0, 0, 0);
check_error(cl);
clReleaseMemObject(col_gpu);
clReleaseMemObject(im_gpu);
}
#endif