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Diffstat (limited to 'intern/cycles/session/denoising.cpp')
| -rw-r--r-- | intern/cycles/session/denoising.cpp | 934 |
1 files changed, 934 insertions, 0 deletions
diff --git a/intern/cycles/session/denoising.cpp b/intern/cycles/session/denoising.cpp new file mode 100644 index 00000000000..21df068092a --- /dev/null +++ b/intern/cycles/session/denoising.cpp @@ -0,0 +1,934 @@ +/* + * Copyright 2011-2018 Blender Foundation + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +#include "session/denoising.h" + +#if 0 + +# include "kernel/filter/filter_defines.h" + +# include "util/util_foreach.h" +# include "util/util_map.h" +# include "util/util_system.h" +# include "util/util_task.h" +# include "util/util_time.h" + +# include <OpenImageIO/filesystem.h> + +CCL_NAMESPACE_BEGIN + +/* Utility Functions */ + +static void print_progress(int num, int total, int frame, int num_frames) +{ + const char *label = "Denoise Frame "; + int cols = system_console_width(); + + cols -= strlen(label); + + int len = 1; + for (int x = total; x > 9; x /= 10) { + len++; + } + + int bars = cols - 2 * len - 6; + + printf("\r%s", label); + + if (num_frames > 1) { + int frame_len = 1; + for (int x = num_frames - 1; x > 9; x /= 10) { + frame_len++; + } + bars -= frame_len + 2; + printf("%*d ", frame_len, frame); + } + + int v = int(float(num) * bars / total); + printf("["); + for (int i = 0; i < v; i++) { + printf("="); + } + if (v < bars) { + printf(">"); + } + for (int i = v + 1; i < bars; i++) { + printf(" "); + } + printf(string_printf("] %%%dd / %d", len, total).c_str(), num); + fflush(stdout); +} + +/* Splits in at its last dot, setting suffix to the part after the dot and in to the part before + * it. Returns whether a dot was found. */ +static bool split_last_dot(string &in, string &suffix) +{ + size_t pos = in.rfind("."); + if (pos == string::npos) { + return false; + } + suffix = in.substr(pos + 1); + in = in.substr(0, pos); + return true; +} + +/* Separate channel names as generated by Blender. + * If views is true: + * Inputs are expected in the form RenderLayer.Pass.View.Channel, sets renderlayer to + * "RenderLayer.View" Otherwise: Inputs are expected in the form RenderLayer.Pass.Channel */ +static bool parse_channel_name( + string name, string &renderlayer, string &pass, string &channel, bool multiview_channels) +{ + if (!split_last_dot(name, channel)) { + return false; + } + string view; + if (multiview_channels && !split_last_dot(name, view)) { + return false; + } + if (!split_last_dot(name, pass)) { + return false; + } + renderlayer = name; + + if (multiview_channels) { + renderlayer += "." + view; + } + + return true; +} + +/* Channel Mapping */ + +struct ChannelMapping { + int channel; + string name; +}; + +static void fill_mapping(vector<ChannelMapping> &map, int pos, string name, string channels) +{ + for (const char *chan = channels.c_str(); *chan; chan++) { + map.push_back({pos++, name + "." + *chan}); + } +} + +static const int INPUT_NUM_CHANNELS = 15; +static const int INPUT_DENOISING_DEPTH = 0; +static const int INPUT_DENOISING_NORMAL = 1; +static const int INPUT_DENOISING_SHADOWING = 4; +static const int INPUT_DENOISING_ALBEDO = 5; +static const int INPUT_NOISY_IMAGE = 8; +static const int INPUT_DENOISING_VARIANCE = 11; +static const int INPUT_DENOISING_INTENSITY = 14; +static vector<ChannelMapping> input_channels() +{ + vector<ChannelMapping> map; + fill_mapping(map, INPUT_DENOISING_DEPTH, "Denoising Depth", "Z"); + fill_mapping(map, INPUT_DENOISING_NORMAL, "Denoising Normal", "XYZ"); + fill_mapping(map, INPUT_DENOISING_SHADOWING, "Denoising Shadowing", "X"); + fill_mapping(map, INPUT_DENOISING_ALBEDO, "Denoising Albedo", "RGB"); + fill_mapping(map, INPUT_NOISY_IMAGE, "Noisy Image", "RGB"); + fill_mapping(map, INPUT_DENOISING_VARIANCE, "Denoising Variance", "RGB"); + fill_mapping(map, INPUT_DENOISING_INTENSITY, "Denoising Intensity", "X"); + return map; +} + +static const int OUTPUT_NUM_CHANNELS = 3; +static vector<ChannelMapping> output_channels() +{ + vector<ChannelMapping> map; + fill_mapping(map, 0, "Combined", "RGB"); + return map; +} + +/* Renderlayer Handling */ + +bool DenoiseImageLayer::detect_denoising_channels() +{ + /* Map device input to image channels. */ + input_to_image_channel.clear(); + input_to_image_channel.resize(INPUT_NUM_CHANNELS, -1); + + foreach (const ChannelMapping &mapping, input_channels()) { + vector<string>::iterator i = find(channels.begin(), channels.end(), mapping.name); + if (i == channels.end()) { + return false; + } + + size_t input_channel = mapping.channel; + size_t layer_channel = i - channels.begin(); + input_to_image_channel[input_channel] = layer_to_image_channel[layer_channel]; + } + + /* Map device output to image channels. */ + output_to_image_channel.clear(); + output_to_image_channel.resize(OUTPUT_NUM_CHANNELS, -1); + + foreach (const ChannelMapping &mapping, output_channels()) { + vector<string>::iterator i = find(channels.begin(), channels.end(), mapping.name); + if (i == channels.end()) { + return false; + } + + size_t output_channel = mapping.channel; + size_t layer_channel = i - channels.begin(); + output_to_image_channel[output_channel] = layer_to_image_channel[layer_channel]; + } + + /* Check that all buffer channels are correctly set. */ + for (int i = 0; i < INPUT_NUM_CHANNELS; i++) { + assert(input_to_image_channel[i] >= 0); + } + for (int i = 0; i < OUTPUT_NUM_CHANNELS; i++) { + assert(output_to_image_channel[i] >= 0); + } + + return true; +} + +bool DenoiseImageLayer::match_channels(int neighbor, + const std::vector<string> &channelnames, + const std::vector<string> &neighbor_channelnames) +{ + neighbor_input_to_image_channel.resize(neighbor + 1); + vector<int> &mapping = neighbor_input_to_image_channel[neighbor]; + + assert(mapping.size() == 0); + mapping.resize(input_to_image_channel.size(), -1); + + for (int i = 0; i < input_to_image_channel.size(); i++) { + const string &channel = channelnames[input_to_image_channel[i]]; + std::vector<string>::const_iterator frame_channel = find( + neighbor_channelnames.begin(), neighbor_channelnames.end(), channel); + + if (frame_channel == neighbor_channelnames.end()) { + return false; + } + + mapping[i] = frame_channel - neighbor_channelnames.begin(); + } + + return true; +} + +/* Denoise Task */ + +DenoiseTask::DenoiseTask(Device *device, + DenoiserPipeline *denoiser, + int frame, + const vector<int> &neighbor_frames) + : denoiser(denoiser), + device(device), + frame(frame), + neighbor_frames(neighbor_frames), + current_layer(0), + input_pixels(device, "filter input buffer", MEM_READ_ONLY), + num_tiles(0) +{ + image.samples = denoiser->samples_override; +} + +DenoiseTask::~DenoiseTask() +{ + free(); +} + +/* Device callbacks */ + +bool DenoiseTask::acquire_tile(Device *device, Device *tile_device, RenderTile &tile) +{ + thread_scoped_lock tile_lock(tiles_mutex); + + if (tiles.empty()) { + return false; + } + + tile = tiles.front(); + tiles.pop_front(); + + device->map_tile(tile_device, tile); + + print_progress(num_tiles - tiles.size(), num_tiles, frame, denoiser->num_frames); + + return true; +} + +/* Mapping tiles is required for regular rendering since each tile has its separate memory + * which may be allocated on a different device. + * For standalone denoising, there is a single memory that is present on all devices, so the only + * thing that needs to be done here is to specify the surrounding tile geometry. + * + * However, since there is only one large memory, the denoised result has to be written to + * a different buffer to avoid having to copy an entire horizontal slice of the image. */ +void DenoiseTask::map_neighboring_tiles(RenderTileNeighbors &neighbors, Device *tile_device) +{ + RenderTile ¢er_tile = neighbors.tiles[RenderTileNeighbors::CENTER]; + RenderTile &target_tile = neighbors.target; + + /* Fill tile information. */ + for (int i = 0; i < RenderTileNeighbors::SIZE; i++) { + if (i == RenderTileNeighbors::CENTER) { + continue; + } + + RenderTile &tile = neighbors.tiles[i]; + int dx = (i % 3) - 1; + int dy = (i / 3) - 1; + tile.x = clamp(center_tile.x + dx * denoiser->tile_size.x, 0, image.width); + tile.w = clamp(center_tile.x + (dx + 1) * denoiser->tile_size.x, 0, image.width) - tile.x; + tile.y = clamp(center_tile.y + dy * denoiser->tile_size.y, 0, image.height); + tile.h = clamp(center_tile.y + (dy + 1) * denoiser->tile_size.y, 0, image.height) - tile.y; + + tile.buffer = center_tile.buffer; + tile.offset = center_tile.offset; + tile.stride = image.width; + } + + /* Allocate output buffer. */ + device_vector<float> *output_mem = new device_vector<float>( + tile_device, "denoising_output", MEM_READ_WRITE); + output_mem->alloc(OUTPUT_NUM_CHANNELS * center_tile.w * center_tile.h); + + /* Fill output buffer with noisy image, assumed by kernel_filter_finalize + * when skipping denoising of some pixels. */ + float *result = output_mem->data(); + float *in = &image.pixels[image.num_channels * (center_tile.y * image.width + center_tile.x)]; + + const DenoiseImageLayer &layer = image.layers[current_layer]; + const int *input_to_image_channel = layer.input_to_image_channel.data(); + + for (int y = 0; y < center_tile.h; y++) { + for (int x = 0; x < center_tile.w; x++, result += OUTPUT_NUM_CHANNELS) { + for (int i = 0; i < OUTPUT_NUM_CHANNELS; i++) { + result[i] = in[image.num_channels * x + input_to_image_channel[INPUT_NOISY_IMAGE + i]]; + } + } + in += image.num_channels * image.width; + } + + output_mem->copy_to_device(); + + /* Fill output tile info. */ + target_tile = center_tile; + target_tile.buffer = output_mem->device_pointer; + target_tile.stride = target_tile.w; + target_tile.offset -= target_tile.x + target_tile.y * target_tile.stride; + + thread_scoped_lock output_lock(output_mutex); + assert(output_pixels.count(center_tile.tile_index) == 0); + output_pixels[target_tile.tile_index] = output_mem; +} + +void DenoiseTask::unmap_neighboring_tiles(RenderTileNeighbors &neighbors) +{ + RenderTile ¢er_tile = neighbors.tiles[RenderTileNeighbors::CENTER]; + RenderTile &target_tile = neighbors.target; + + thread_scoped_lock output_lock(output_mutex); + assert(output_pixels.count(center_tile.tile_index) == 1); + device_vector<float> *output_mem = output_pixels[target_tile.tile_index]; + output_pixels.erase(center_tile.tile_index); + output_lock.unlock(); + + /* Copy denoised pixels from device. */ + output_mem->copy_from_device(0, OUTPUT_NUM_CHANNELS * target_tile.w, target_tile.h); + + float *result = output_mem->data(); + float *out = &image.pixels[image.num_channels * (target_tile.y * image.width + target_tile.x)]; + + const DenoiseImageLayer &layer = image.layers[current_layer]; + const int *output_to_image_channel = layer.output_to_image_channel.data(); + + for (int y = 0; y < target_tile.h; y++) { + for (int x = 0; x < target_tile.w; x++, result += OUTPUT_NUM_CHANNELS) { + for (int i = 0; i < OUTPUT_NUM_CHANNELS; i++) { + out[image.num_channels * x + output_to_image_channel[i]] = result[i]; + } + } + out += image.num_channels * image.width; + } + + /* Free device buffer. */ + output_mem->free(); + delete output_mem; +} + +void DenoiseTask::release_tile() +{ +} + +bool DenoiseTask::get_cancel() +{ + return false; +} + +void DenoiseTask::create_task(DeviceTask &task) +{ + /* Callback functions. */ + task.acquire_tile = function_bind(&DenoiseTask::acquire_tile, this, device, _1, _2); + task.map_neighbor_tiles = function_bind(&DenoiseTask::map_neighboring_tiles, this, _1, _2); + task.unmap_neighbor_tiles = function_bind(&DenoiseTask::unmap_neighboring_tiles, this, _1); + task.release_tile = function_bind(&DenoiseTask::release_tile, this); + task.get_cancel = function_bind(&DenoiseTask::get_cancel, this); + + /* Denoising parameters. */ + task.denoising = denoiser->params; + task.denoising.type = DENOISER_NLM; + task.denoising.use = true; + task.denoising_from_render = false; + + task.denoising_frames.resize(neighbor_frames.size()); + for (int i = 0; i < neighbor_frames.size(); i++) { + task.denoising_frames[i] = neighbor_frames[i] - frame; + } + + /* Buffer parameters. */ + task.pass_stride = INPUT_NUM_CHANNELS; + task.target_pass_stride = OUTPUT_NUM_CHANNELS; + task.pass_denoising_data = 0; + task.pass_denoising_clean = -1; + task.frame_stride = image.width * image.height * INPUT_NUM_CHANNELS; + + /* Create tiles. */ + thread_scoped_lock tile_lock(tiles_mutex); + thread_scoped_lock output_lock(output_mutex); + + tiles.clear(); + assert(output_pixels.empty()); + output_pixels.clear(); + + int tiles_x = divide_up(image.width, denoiser->tile_size.x); + int tiles_y = divide_up(image.height, denoiser->tile_size.y); + + for (int ty = 0; ty < tiles_y; ty++) { + for (int tx = 0; tx < tiles_x; tx++) { + RenderTile tile; + tile.x = tx * denoiser->tile_size.x; + tile.y = ty * denoiser->tile_size.y; + tile.w = min(image.width - tile.x, denoiser->tile_size.x); + tile.h = min(image.height - tile.y, denoiser->tile_size.y); + tile.start_sample = 0; + tile.num_samples = image.layers[current_layer].samples; + tile.sample = 0; + tile.offset = 0; + tile.stride = image.width; + tile.tile_index = ty * tiles_x + tx; + tile.task = RenderTile::DENOISE; + tile.buffers = NULL; + tile.buffer = input_pixels.device_pointer; + tiles.push_back(tile); + } + } + + num_tiles = tiles.size(); +} + +/* Denoiser Operations */ + +bool DenoiseTask::load_input_pixels(int layer) +{ + int w = image.width; + int h = image.height; + int num_pixels = image.width * image.height; + int frame_stride = num_pixels * INPUT_NUM_CHANNELS; + + /* Load center image */ + DenoiseImageLayer &image_layer = image.layers[layer]; + + float *buffer_data = input_pixels.data(); + image.read_pixels(image_layer, buffer_data); + buffer_data += frame_stride; + + /* Load neighbor images */ + for (int i = 0; i < image.in_neighbors.size(); i++) { + if (!image.read_neighbor_pixels(i, image_layer, buffer_data)) { + error = "Failed to read neighbor frame pixels"; + return false; + } + buffer_data += frame_stride; + } + + /* Preprocess */ + buffer_data = input_pixels.data(); + for (int neighbor = 0; neighbor < image.in_neighbors.size() + 1; neighbor++) { + /* Clamp */ + if (denoiser->params.clamp_input) { + for (int i = 0; i < num_pixels * INPUT_NUM_CHANNELS; i++) { + buffer_data[i] = clamp(buffer_data[i], -1e8f, 1e8f); + } + } + + /* Box blur */ + int r = 5 * denoiser->params.radius; + float *data = buffer_data + 14; + array<float> temp(num_pixels); + + for (int y = 0; y < h; y++) { + for (int x = 0; x < w; x++) { + int n = 0; + float sum = 0.0f; + for (int dx = max(x - r, 0); dx < min(x + r + 1, w); dx++, n++) { + sum += data[INPUT_NUM_CHANNELS * (y * w + dx)]; + } + temp[y * w + x] = sum / n; + } + } + + for (int y = 0; y < h; y++) { + for (int x = 0; x < w; x++) { + int n = 0; + float sum = 0.0f; + + for (int dy = max(y - r, 0); dy < min(y + r + 1, h); dy++, n++) { + sum += temp[dy * w + x]; + } + + data[INPUT_NUM_CHANNELS * (y * w + x)] = sum / n; + } + } + + /* Highlight compression */ + data = buffer_data + 8; + for (int y = 0; y < h; y++) { + for (int x = 0; x < w; x++) { + int idx = INPUT_NUM_CHANNELS * (y * w + x); + float3 color = make_float3(data[idx], data[idx + 1], data[idx + 2]); + color = color_highlight_compress(color, NULL); + data[idx] = color.x; + data[idx + 1] = color.y; + data[idx + 2] = color.z; + } + } + + buffer_data += frame_stride; + } + + /* Copy to device */ + input_pixels.copy_to_device(); + + return true; +} + +/* Task stages */ + +bool DenoiseTask::load() +{ + string center_filepath = denoiser->input[frame]; + if (!image.load(center_filepath, error)) { + return false; + } + + if (!image.load_neighbors(denoiser->input, neighbor_frames, error)) { + return false; + } + + if (image.layers.empty()) { + error = "No image layers found to denoise in " + center_filepath; + return false; + } + + /* Allocate device buffer. */ + int num_frames = image.in_neighbors.size() + 1; + input_pixels.alloc(image.width * INPUT_NUM_CHANNELS, image.height * num_frames); + input_pixels.zero_to_device(); + + /* Read pixels for first layer. */ + current_layer = 0; + if (!load_input_pixels(current_layer)) { + return false; + } + + return true; +} + +bool DenoiseTask::exec() +{ + for (current_layer = 0; current_layer < image.layers.size(); current_layer++) { + /* Read pixels for secondary layers, first was already loaded. */ + if (current_layer > 0) { + if (!load_input_pixels(current_layer)) { + return false; + } + } + + /* Run task on device. */ + DeviceTask task(DeviceTask::RENDER); + create_task(task); + device->task_add(task); + device->task_wait(); + + printf("\n"); + } + + return true; +} + +bool DenoiseTask::save() +{ + bool ok = image.save_output(denoiser->output[frame], error); + free(); + return ok; +} + +void DenoiseTask::free() +{ + image.free(); + input_pixels.free(); + assert(output_pixels.empty()); +} + +/* Denoise Image Storage */ + +DenoiseImage::DenoiseImage() +{ + width = 0; + height = 0; + num_channels = 0; + samples = 0; +} + +DenoiseImage::~DenoiseImage() +{ + free(); +} + +void DenoiseImage::close_input() +{ + in_neighbors.clear(); +} + +void DenoiseImage::free() +{ + close_input(); + pixels.clear(); +} + +bool DenoiseImage::parse_channels(const ImageSpec &in_spec, string &error) +{ + const std::vector<string> &channels = in_spec.channelnames; + const ParamValue *multiview = in_spec.find_attribute("multiView"); + const bool multiview_channels = (multiview && multiview->type().basetype == TypeDesc::STRING && + multiview->type().arraylen >= 2); + + layers.clear(); + + /* Loop over all the channels in the file, parse their name and sort them + * by RenderLayer. + * Channels that can't be parsed are directly passed through to the output. */ + map<string, DenoiseImageLayer> file_layers; + for (int i = 0; i < channels.size(); i++) { + string layer, pass, channel; + if (parse_channel_name(channels[i], layer, pass, channel, multiview_channels)) { + file_layers[layer].channels.push_back(pass + "." + channel); + file_layers[layer].layer_to_image_channel.push_back(i); + } + } + + /* Loop over all detected RenderLayers, check whether they contain a full set of input channels. + * Any channels that won't be processed internally are also passed through. */ + for (map<string, DenoiseImageLayer>::iterator i = file_layers.begin(); i != file_layers.end(); + ++i) { + const string &name = i->first; + DenoiseImageLayer &layer = i->second; + + /* Check for full pass set. */ + if (!layer.detect_denoising_channels()) { + continue; + } + + layer.name = name; + layer.samples = samples; + + /* If the sample value isn't set yet, check if there is a layer-specific one in the input file. + */ + if (layer.samples < 1) { + string sample_string = in_spec.get_string_attribute("cycles." + name + ".samples", ""); + if (sample_string != "") { + if (!sscanf(sample_string.c_str(), "%d", &layer.samples)) { + error = "Failed to parse samples metadata: " + sample_string; + return false; + } + } + } + + if (layer.samples < 1) { + error = string_printf( + "No sample number specified in the file for layer %s or on the command line", + name.c_str()); + return false; + } + + layers.push_back(layer); + } + + return true; +} + +void DenoiseImage::read_pixels(const DenoiseImageLayer &layer, float *input_pixels) +{ + /* Pixels from center file have already been loaded into pixels. + * We copy a subset into the device input buffer with channels reshuffled. */ + const int *input_to_image_channel = layer.input_to_image_channel.data(); + + for (int i = 0; i < width * height; i++) { + for (int j = 0; j < INPUT_NUM_CHANNELS; j++) { + int image_channel = input_to_image_channel[j]; + input_pixels[i * INPUT_NUM_CHANNELS + j] = + pixels[((size_t)i) * num_channels + image_channel]; + } + } +} + +bool DenoiseImage::read_neighbor_pixels(int neighbor, + const DenoiseImageLayer &layer, + float *input_pixels) +{ + /* Load pixels from neighboring frames, and copy them into device buffer + * with channels reshuffled. */ + size_t num_pixels = (size_t)width * (size_t)height; + array<float> neighbor_pixels(num_pixels * num_channels); + if (!in_neighbors[neighbor]->read_image(TypeDesc::FLOAT, neighbor_pixels.data())) { + return false; + } + + const int *input_to_image_channel = layer.neighbor_input_to_image_channel[neighbor].data(); + + for (int i = 0; i < width * height; i++) { + for (int j = 0; j < INPUT_NUM_CHANNELS; j++) { + int image_channel = input_to_image_channel[j]; + input_pixels[i * INPUT_NUM_CHANNELS + j] = + neighbor_pixels[((size_t)i) * num_channels + image_channel]; + } + } + + return true; +} + +bool DenoiseImage::load(const string &in_filepath, string &error) +{ + if (!Filesystem::is_regular(in_filepath)) { + error = "Couldn't find file: " + in_filepath; + return false; + } + + unique_ptr<ImageInput> in(ImageInput::open(in_filepath)); + if (!in) { + error = "Couldn't open file: " + in_filepath; + return false; + } + + in_spec = in->spec(); + width = in_spec.width; + height = in_spec.height; + num_channels = in_spec.nchannels; + + if (!parse_channels(in_spec, error)) { + return false; + } + + if (layers.size() == 0) { + error = "Could not find a render layer containing denoising info"; + return false; + } + + size_t num_pixels = (size_t)width * (size_t)height; + pixels.resize(num_pixels * num_channels); + + /* Read all channels into buffer. Reading all channels at once is faster + * than individually due to interleaved EXR channel storage. */ + if (!in->read_image(TypeDesc::FLOAT, pixels.data())) { + error = "Failed to read image: " + in_filepath; + return false; + } + + return true; +} + +bool DenoiseImage::load_neighbors(const vector<string> &filepaths, + const vector<int> &frames, + string &error) +{ + if (frames.size() > DENOISE_MAX_FRAMES - 1) { + error = string_printf("Maximum number of neighbors (%d) exceeded\n", DENOISE_MAX_FRAMES - 1); + return false; + } + + for (int neighbor = 0; neighbor < frames.size(); neighbor++) { + int frame = frames[neighbor]; + const string &filepath = filepaths[frame]; + + if (!Filesystem::is_regular(filepath)) { + error = "Couldn't find neighbor frame: " + filepath; + return false; + } + + unique_ptr<ImageInput> in_neighbor(ImageInput::open(filepath)); + if (!in_neighbor) { + error = "Couldn't open neighbor frame: " + filepath; + return false; + } + + const ImageSpec &neighbor_spec = in_neighbor->spec(); + if (neighbor_spec.width != width || neighbor_spec.height != height) { + error = "Neighbor frame has different dimensions: " + filepath; + return false; + } + + foreach (DenoiseImageLayer &layer, layers) { + if (!layer.match_channels(neighbor, in_spec.channelnames, neighbor_spec.channelnames)) { + error = "Neighbor frame misses denoising data passes: " + filepath; + return false; + } + } + + in_neighbors.push_back(std::move(in_neighbor)); + } + + return true; +} + +bool DenoiseImage::save_output(const string &out_filepath, string &error) +{ + /* Save image with identical dimensions, channels and metadata. */ + ImageSpec out_spec = in_spec; + + /* Ensure that the output frame contains sample information even if the input didn't. */ + for (int i = 0; i < layers.size(); i++) { + string name = "cycles." + layers[i].name + ".samples"; + if (!out_spec.find_attribute(name, TypeDesc::STRING)) { + out_spec.attribute(name, TypeDesc::STRING, string_printf("%d", layers[i].samples)); + } + } + + /* We don't need input anymore at this point, and will possibly + * overwrite the same file. */ + close_input(); + + /* Write to temporary file path, so we denoise images in place and don't + * risk destroying files when something goes wrong in file saving. */ + string extension = OIIO::Filesystem::extension(out_filepath); + string unique_name = ".denoise-tmp-" + OIIO::Filesystem::unique_path(); + string tmp_filepath = out_filepath + unique_name + extension; + unique_ptr<ImageOutput> out(ImageOutput::create(tmp_filepath)); + + if (!out) { + error = "Failed to open temporary file " + tmp_filepath + " for writing"; + return false; + } + + /* Open temporary file and write image buffers. */ + if (!out->open(tmp_filepath, out_spec)) { + error = "Failed to open file " + tmp_filepath + " for writing: " + out->geterror(); + return false; + } + + bool ok = true; + if (!out->write_image(TypeDesc::FLOAT, pixels.data())) { + error = "Failed to write to file " + tmp_filepath + ": " + out->geterror(); + ok = false; + } + + if (!out->close()) { + error = "Failed to save to file " + tmp_filepath + ": " + out->geterror(); + ok = false; + } + + out.reset(); + + /* Copy temporary file to output filepath. */ + string rename_error; + if (ok && !OIIO::Filesystem::rename(tmp_filepath, out_filepath, rename_error)) { + error = "Failed to move denoised image to " + out_filepath + ": " + rename_error; + ok = false; + } + + if (!ok) { + OIIO::Filesystem::remove(tmp_filepath); + } + + return ok; +} + +/* File pattern handling and outer loop over frames */ + +DenoiserPipeline::DenoiserPipeline(DeviceInfo &device_info) +{ + samples_override = 0; + tile_size = make_int2(64, 64); + + num_frames = 0; + + /* Initialize task scheduler. */ + TaskScheduler::init(); + + /* Initialize device. */ + device = Device::create(device_info, stats, profiler, true); + + device->load_kernels(KERNEL_FEATURE_DENOISING); +} + +DenoiserPipeline::~DenoiserPipeline() +{ + delete device; + TaskScheduler::exit(); +} + +bool DenoiserPipeline::run() +{ + assert(input.size() == output.size()); + + num_frames = output.size(); + + for (int frame = 0; frame < num_frames; frame++) { + /* Skip empty output paths. */ + if (output[frame].empty()) { + continue; + } + + /* Determine neighbor frame numbers that should be used for filtering. */ + vector<int> neighbor_frames; + for (int f = frame - params.neighbor_frames; f <= frame + params.neighbor_frames; f++) { + if (f >= 0 && f < num_frames && f != frame) { + neighbor_frames.push_back(f); + } + } + + /* Execute task. */ + DenoiseTask task(device, this, frame, neighbor_frames); + if (!task.load()) { + error = task.error; + return false; + } + + if (!task.exec()) { + error = task.error; + return false; + } + + if (!task.save()) { + error = task.error; + return false; + } + + task.free(); + } + + return true; +} + +CCL_NAMESPACE_END + +#endif |