Commit: a0d6ca39dd29c69344792cd4a33eb92bcc76235c
Author: Lukas Stockner
Date: Sat Jan 14 18:57:03 2017 +0100
Branches: soc-2016-cycles_denoising
https://developer.blender.org/rBa0d6ca39dd29c69344792cd4a33eb92bcc76235c
Cycles Denoising: Redesign debug EXR writing code for a cleaner integration
Also, remove the denoising passes from CUDA - just adds to much clutter and the
results are the same as on the CPU anyways.
===================================================================
M intern/cycles/device/device_cpu.cpp
M intern/cycles/device/device_cuda.cpp
M intern/cycles/util/util_debug.cpp
M intern/cycles/util/util_debug.h
M intern/cycles/util/util_guarded_allocator.h
===================================================================
diff --git a/intern/cycles/device/device_cpu.cpp
b/intern/cycles/device/device_cpu.cpp
index 2e7844ca99..26ec530cf1 100644
--- a/intern/cycles/device/device_cpu.cpp
+++ b/intern/cycles/device/device_cpu.cpp
@@ -329,10 +329,7 @@ public:
for(int i = 0; i < 9; i++) {
buffer[i] = buffers[i] + frame_strides[i]*frame;
}
-#ifdef WITH_CYCLES_DEBUG_FILTER
- DenoiseDebug debug((rect.z - rect.x), h, 34);
-#endif
-
+ DebugPasses debug((rect.z - rect.x), h, 34, 1, w);
#define PASSPTR(i) (filter_buffer + (i)*pass_stride)
@@ -349,28 +346,21 @@ public:
filter_divide_shadow_kernel()(kg, sample, buffer, x, y, tile_x, tile_y,
offsets, strides, unfilteredA, sampleV, sampleVV, bufferV, &rect.x);
}
}
-#ifdef WITH_CYCLES_DEBUG_FILTER
-#define WRITE_DEBUG(name, var) debug.add_pass(string_printf("shadow_%s",
name), var, 1, w);
- WRITE_DEBUG("unfilteredA", unfilteredA);
- WRITE_DEBUG("unfilteredB", unfilteredB);
- WRITE_DEBUG("bufferV", bufferV);
- WRITE_DEBUG("sampleV", sampleV);
- WRITE_DEBUG("sampleVV", sampleVV);
-#endif
+ debug.add_pass("shadowUnfilteredA",
unfilteredA);
+ debug.add_pass("shadowUnfilteredB",
unfilteredB);
+ debug.add_pass("shadowBufferV", bufferV);
+ debug.add_pass("shadowSampleV", sampleV);
+ debug.add_pass("shadowSampleVV", sampleVV);
/* Smooth the (generally pretty noisy) buffer
variance using the spatial information from the sample variance. */
non_local_means(rect, bufferV, sampleV, cleanV,
sampleVV, nlm_temp1, nlm_temp2, nlm_temp3, 6, 3, 4.0f, 1.0f);
-#ifdef WITH_CYCLES_DEBUG_FILTER
- WRITE_DEBUG("cleanV", cleanV);
-#endif
+ debug.add_pass("shadowCleanV", cleanV);
/* Use the smoothed variance to filter the two
shadow half images using each other for weight calculation. */
non_local_means(rect, unfilteredA, unfilteredB,
sampleV, cleanV, nlm_temp1, nlm_temp2, nlm_temp3, 5, 3, 1.0f, 0.25f);
non_local_means(rect, unfilteredB, unfilteredA,
bufferV, cleanV, nlm_temp1, nlm_temp2, nlm_temp3, 5, 3, 1.0f, 0.25f);
-#ifdef WITH_CYCLES_DEBUG_FILTER
- WRITE_DEBUG("filteredA", sampleV);
- WRITE_DEBUG("filteredB", bufferV);
-#endif
+ debug.add_pass("shadowFilteredA", sampleV);
+ debug.add_pass("shadowFilteredB", bufferV);
/* Estimate the residual variance between the
two filtered halves. */
for(int y = rect.y; y < rect.w; y++) {
@@ -378,17 +368,13 @@ public:
filter_combine_halves_kernel()(x, y, NULL, sampleVV, sampleV, bufferV, &rect.x,
2);
}
}
-#ifdef WITH_CYCLES_DEBUG_FILTER
- WRITE_DEBUG("residualV", sampleVV);
-#endif
+ debug.add_pass("shadowResidualV", sampleVV);
/* Use the residual variance for a second
filter pass. */
non_local_means(rect, sampleV, bufferV,
unfilteredA, sampleVV, nlm_temp1, nlm_temp2, nlm_temp3, 4, 2, 1.0f, 0.5f);
non_local_means(rect, bufferV, sampleV,
unfilteredB, sampleVV, nlm_temp1, nlm_temp2, nlm_temp3, 4, 2, 1.0f, 0.5f);
-#ifdef WITH_CYCLES_DEBUG_FILTER
- WRITE_DEBUG("finalA", unfilteredA);
- WRITE_DEBUG("finalB", unfilteredB);
-#endif
+ debug.add_pass("shadowFinalA", unfilteredA);
+ debug.add_pass("shadowFinalB", unfilteredB);
/* Combine the two double-filtered halves to a
final shadow feature image and associated variance. */
for(int y = rect.y; y < rect.w; y++) {
@@ -396,12 +382,8 @@ public:
filter_combine_halves_kernel()(x, y, PASSPTR(8), PASSPTR(9), unfilteredA,
unfilteredB, &rect.x, 0);
}
}
-#ifdef WITH_CYCLES_DEBUG_FILTER
- WRITE_DEBUG("final", PASSPTR(8));
- WRITE_DEBUG("finalV", PASSPTR(9));
- debug.write(string_printf("debugf_%dx%d.exr",
tile_x[1], tile_y[1]));
-#undef WRITE_DEBUG
-#endif
+ debug.add_pass("shadowFinal", PASSPTR(8));
+ debug.add_pass("shadowFinalV", PASSPTR(9));
}
/* ==== Step 2: Prefilter general features. ==== */
@@ -429,13 +411,9 @@ public:
}
}
non_local_means(rect, unfiltered,
unfiltered, PASSPTR(offset_to[i]), PASSPTR(offset_to[i]+1), nlm_temp1,
nlm_temp2, nlm_temp3, 2, 2, 1, 0.25f);
-#ifdef WITH_CYCLES_DEBUG_FILTER
-#define WRITE_DEBUG(name, var) debug.add_pass(string_printf("f%d_%s", i,
name), var, 1, w);
- WRITE_DEBUG("unfiltered", unfiltered);
- WRITE_DEBUG("sampleV",
PASSPTR(offset_to[i]+1));
- WRITE_DEBUG("filtered",
PASSPTR(offset_to[i]));
-#undef WRITE_DEBUG
-#endif
+
debug.add_pass(string_printf("feature%dUnfiltered", i), unfiltered);
+
debug.add_pass(string_printf("feature%dFiltered", i), PASSPTR(offset_to[i]));
+
debug.add_pass(string_printf("feature%dVariance", i), PASSPTR(offset_to[i]+1));
}
}
@@ -468,6 +446,8 @@ public:
}
}
}
+
+ debug.write(string_printf("debug_tile_%d_%d.exr",
rect.x, rect.y));
}
return filter_buffers;
diff --git a/intern/cycles/device/device_cuda.cpp
b/intern/cycles/device/device_cuda.cpp
index 8ec6ca6b91..4659b1dc01 100644
--- a/intern/cycles/device/device_cuda.cpp
+++ b/intern/cycles/device/device_cuda.cpp
@@ -993,33 +993,12 @@ public:
xthreads, ythreads,
1, /* threads */
0, 0, divide_args,
0));
-#ifdef WITH_CYCLES_DEBUG_FILTER
-#define WRITE_DEBUG(name, ptr)
debug_write_pfm(string_printf("debug_%dx%d_cuda_shadow_%s.pfm",
rtile.x+rtile.buffers->params.overscan, rtile.y+rtile.buffers->params.overscan,
name).c_str(), ptr, rtile.w, rtile.h, 1, w)
- float *temp = new float[pass_stride*6];
- cuda_assert(cuMemcpyDtoH(temp, d_sampleV,
6*pass_stride*sizeof(float)));
-
- WRITE_DEBUG("unfilteredA", temp +
4*pass_stride);
- WRITE_DEBUG("unfilteredB", temp +
5*pass_stride);
- WRITE_DEBUG("bufferV", temp + 2*pass_stride);
- WRITE_DEBUG("sampleV", temp + 0*pass_stride);
- WRITE_DEBUG("sampleVV", temp + 1*pass_stride);
-#endif
-
/* Smooth the (generally pretty noisy) buffer
variance using the spatial information from the sample variance. */
non_local_means(rect, d_bufferV, d_sampleV,
d_cleanV, d_sampleVV, d_temp1, d_temp2, d_temp3, 6, 3, 2.0f, 2.0f);
-#ifdef WITH_CYCLES_DEBUG_FILTER
- cuda_assert(cuMemcpyDtoH(temp, d_cleanV,
pass_stride*sizeof(float)));
- WRITE_DEBUG("cleanV", temp);
-#endif
/* Use the smoothed variance to filter the two
shadow half images using each other for weight calculation. */
non_local_means(rect, d_unfilteredA,
d_unfilteredB, d_sampleV, d_cleanV, d_temp1, d_temp2, d_temp3, 5, 3, 1.0f,
0.25f);
non_local_means(rect, d_unfilteredB,
d_unfilteredA, d_bufferV, d_cleanV, d_temp1, d_temp2, d_temp3, 5, 3, 1.0f,
0.25f);
-#ifdef WITH_CYCLES_DEBUG_FILTER
- cuda_assert(cuMemcpyDtoH(temp, d_sampleV,
3*pass_stride*sizeof(float)));
- WRITE_DEBUG("filteredA", temp);
- WRITE_DEBUG("filteredB", temp + 2*pass_stride);
-#endif
/* Estimate the residual variance between the
two filtered halves. */
int var_r = 2;
@@ -1029,19 +1008,10 @@ public:
xblocks , yblocks,
1, /* blocks */
xthreads, ythreads,
1, /* threads */
0, 0,
residual_variance_args, 0));
-#ifdef WITH_CYCLES_DEBUG_FILTER
- cuda_assert(cuMemcpyDtoH(temp, d_cleanV,
pass_stride*sizeof(float)));
- WRITE_DEBUG("residualV", temp);
-#endif
/* Use the residual variance for a second
filter pass. */
non_local_means(rect, d_sampleV, d_bufferV,
d_unfilteredA, d_cleanV, d_temp1, d_temp2, d_temp3, 4, 2, 1.0f, 1.0f);
non_local_means(rect, d_bufferV, d_sampleV,
d_unfilteredB, d_cleanV, d_temp1, d_temp2, d_temp3, 4, 2, 1.0f, 1.0f);
-#ifdef WITH_CYCLES_DEBUG_FILTER
- cuda_assert(cuMemcpyDtoH(temp, d_unfilteredA,
2*pass_stride*sizeof(float)));
- WRITE_DEBUG("finalA", temp);
- WRITE_DEBUG("finalB", temp + 1*pass_stride);
-#endif
/* Combine the two double-filtered halves to a
final shadow feature image and associated variance. */
var_r = 0;
@@ -1053,13 +1023,6 @@ public:
xthreads, ythreads,
1, /* threads */
0, 0,
final_prefiltered_args, 0));
cuda_assert(cuCtxSynchronize());
-#ifdef WITH_CYCLES_DEBUG_FILTER
- cuda_assert(cuMemcpyDtoH(temp, d_mean,
2*pass_stride*sizeof(float)));
- WRITE_DEBUG("final", temp);
- WRITE_DEBUG("finalV", temp + 1*pass_stride);
- delete[] temp;
-#undef WRITE_DEBUG
-#endif
}
/* ==== Step 2: Prefilter general features. ==== */
@@ -1113,18 +1076,6 @@ public:
}
}
-#ifdef WITH_CYCLES_DEBUG_FILTER
-#define WRITE_DEBUG(name, pass)
debug_write_pfm(string_printf("debug_%dx%d_cuda_feature%d_%s.pfm",
rtile.x+rtile.buffers->params.overscan, rtile.y+rtile.buffers->params.overscan,
i, name).c_str(), host_denoise_buffer+pass*pass_stride, rtile.w, rtile.h, 1, w)
- float *host_denoise_buffer = new float[22*pass_stride];
- cuda_assert(cuMemcpyDtoH(host_denoise_buffer,
d_denoise_buffers, 22*pass_stride*sizeof(float)));
- for(int i = 0; i < 8; i++) {
- WRITE_DEBUG("filtered", 2*i);
- WRITE_DEBUG("variance", 2*i+1);
- }
- delete[] host_denoise_buffer;
-#undef WRITE_DEBUG
-#endif
-
/* Use the prefiltered feature to denoise the image. */
int storage_num = filter_area.z*filter_area.w;
CUdeviceptr d_storage, d_transforms;
@@ -1226,26 +1177,6 @@ public:
0, 0, finalize_args, 0));
cuda_assert(cuMemFree(d_XtWX));
cuda_assert(cuMemFree(d_XtWY));
-
-#ifdef WITH_CYCLES_DEBUG_FILTER
- CUDAFilterStorage *host_storage = new
CUDAFilterStorage[filter_area.z*filter_area.w];
- cuda_assert(cuMemcpyDtoH(host_storage, d_storage,
sizeof(CUDAFilterStorage)*filter_area.z*filter_area.w));
-#define WRITE_DEBUG(name, var)
debug_write_pfm(string_printf("debug_%dx%d_cuda_%s.pfm",
rtile.x+rtile.buffers->params.overscan, rtile.y+rtile.buffers->params.overscan,
name).c_str(), &host_storage[0].var, filter_area.z, filter_area.w,
sizeof(CUDAFilterStorage)/sizeof(float), filter_area.z);
- for(int i = 0; i < DENOISE_FEATURES; i++) {
- WRITE_DEBUG(string_printf("mean_%d", i).c_str(),
means[i]);
- WRITE_DEBUG(string_printf("scale_%d", i).c_str(),
scales[i]);
- WRITE_DEBUG(string_printf("singular_%d", i).c_str(),
singular[i]);
- WRITE_DEBUG(string_printf("bandwidth_%d", i).c_str(),
bandwidth[i]);
- }
- WRITE_DEBUG("singula
@@ Diff output truncated at 10240 characters. @@
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