File size: 3,537 Bytes
ea55f45 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 | /*
* This copyright notice applies to this header file only:
*
* Copyright (c) 2010-2024 NVIDIA Corporation
*
* Permission is hereby granted, free of charge, to any person
* obtaining a copy of this software and associated documentation
* files (the "Software"), to deal in the Software without
* restriction, including without limitation the rights to use,
* copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the software, and to permit persons to whom the
* software is furnished to do so, subject to the following
* conditions:
*
* The above copyright notice and this permission notice shall be
* included in all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
* OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
* NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
* HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
* WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
* OTHER DEALINGS IN THE SOFTWARE.
*/
#include "Metrics.h"
__global__ void squaredErrorKernel(const uint8_t* image1, const uint8_t* image2, uint32_t width, uint32_t height, uint32_t pitch, float* sse) {
extern __shared__ float sdata[];
unsigned int tid = threadIdx.x;
unsigned int idx = blockIdx.x * blockDim.x + threadIdx.x;
unsigned int stride = gridDim.x * blockDim.x;
float sum = 0.0f;
// Accumulate squared error for this thread's part of the image
while (idx < width * height) {
int row = idx / width;
int col = idx % width;
int idx1 = row * pitch + col;
int idx2 = row * pitch + col;
float diff = static_cast<float>(image1[idx1]) - static_cast<float>(image2[idx2]);
sum += diff * diff;
idx += stride;
}
// Store the result in shared memory
sdata[tid] = sum;
__syncthreads();
// Reduce within the block
for (unsigned int s = blockDim.x / 2; s > 0; s >>= 1) {
if (tid < s) {
sdata[tid] += sdata[tid + s];
}
__syncthreads();
}
// Write the result of this block to the output array
if (tid == 0) {
atomicAdd(sse, sdata[0]);
}
}
void squaredError(uint8_t* image1, uint8_t* image2, uint32_t width, uint32_t height, uint32_t pitch, float &sse) {
int threadsPerBlock = 256;
int blocksPerGrid = (width * height + threadsPerBlock - 1) / threadsPerBlock;
int sharedMemSize = threadsPerBlock * sizeof(float);
float *sseDevice;
ck(cudaMalloc(&sseDevice, sizeof(float)));
ck(cudaMemset(sseDevice, 0, sizeof(float)));
squaredErrorKernel<<<blocksPerGrid, threadsPerBlock, sharedMemSize>>>(image1, image2, width, height, pitch, sseDevice);
CudaCheckError();
ck(cudaDeviceSynchronize());
ck(cudaMemcpy(&sse, sseDevice, sizeof(float), cudaMemcpyDeviceToHost));
ck(cudaFree(sseDevice));
}
void calcPSNRY(uint8_t* ref, uint8_t* dis, uint32_t width, uint32_t height, uint32_t pitch, float &psnr) {
float sse = 0.0f;
float mse = 0.0f;
uint32_t MAX = 255;
squaredError(ref, dis, width, height, pitch, sse);
mse = sse / (width * height);
if (mse)
psnr = 10.0f * log10f(MAX * MAX / mse);
else
psnr = 100.0;
} |