text: /*
   * 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 "render/denoising.h"
  
  #include "kernel/filter/filter_defines.h"
  
  #include "util/util_foreach.h"
  #include "util/util_map.h"
  #include "util/util_system.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,
                           Denoiser *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(RenderTile *tiles, Device *tile_device)
  {
    /* Fill tile information. */
    for (int i = 0; i < 9; i++) {
      if (i == 4) {
        continue;
      }
  
      int dx = (i % 3) - 1;
      int dy = (i / 3) - 1;
      tiles[i].x = clamp(tiles[4].x + dx * denoiser->tile_size.x, 0, image.width);
      tiles[i].w = clamp(tiles[4].x + (dx + 1) * denoiser->tile_size.x, 0, image.width) - tiles[i].x;
      tiles[i].y = clamp(tiles[4].y + dy * denoiser->tile_size.y, 0, image.height);
      tiles[i].h = clamp(tiles[4].y + (dy + 1) * denoiser->tile_size.y, 0, image.height) -
                   tiles[i].y;
  
      tiles[i].buffer = tiles[4].buffer;
      tiles[i].offset = tiles[4].offset;
      tiles[i].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 * tiles[4].w * tiles[4].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 * (tiles[4].y * image.width + tiles[4].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 < tiles[4].h; y++) {
      for (int x = 0; x < tiles[4].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. */
    tiles[9] = tiles[4];
    tiles[9].buffer = output_mem->device_pointer;
    tiles[9].stride = tiles[9].w;
    tiles[9].offset -= tiles[9].x + tiles[9].y * tiles[9].stride;
  
    thread_scoped_lock output_lock(output_mutex);
    assert(output_pixels.count(tiles[4].tile_index) == 0);
    output_pixels[tiles[9].tile_index] = output_mem;
  }
  
  void DenoiseTask::unmap_neighboring_tiles(RenderTile *tiles)
  {
    thread_scoped_lock output_lock(output_mutex);
    assert(output_pixels.count(tiles[4].tile_index) == 1);
    device_vector<float> *output_mem = output_pixels[tiles[9].tile_index];
    output_pixels.erase(tiles[4].tile_index);
    output_lock.unlock();
  
    /* Copy denoised pixels from device. */
    output_mem->copy_from_device(0, OUTPUT_NUM_CHANNELS * tiles[9].w, tiles[9].h);
  
    float *result = output_mem->data();
    float *out = &image.pixels[image.num_channels * (tiles[9].y * image.width + tiles[9].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 < tiles[9].h; y++) {
      for (int x = 0; x < tiles[9].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_do_filter = true;
    task.denoising_write_passes = false;
    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;
        }
      }
  
      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 outputput 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 */
  
  Denoiser::Denoiser(DeviceInfo &device_info)
  {
    samples_override = 0;
    tile_size = make_int2(64, 64);
  
    num_frames = 0;
  
    /* Initialize task scheduler. */
    TaskScheduler::init();
  
    /* Initialize device. */
    DeviceRequestedFeatures req;
    device = Device::create(device_info, stats, profiler, true);
    device->load_kernels(req);
  }
  
  Denoiser::~Denoiser()
  {
    delete device;
    TaskScheduler::exit();
  }
  
  bool Denoiser::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
  