| |
| |
|
|
| #include <numeric> |
| #include <vector> |
| #include <iostream> |
|
|
| #include <napi.h> |
| #include <vips/vips8> |
|
|
| #include "common.h" |
| #include "stats.h" |
|
|
| class StatsWorker : public Napi::AsyncWorker { |
| public: |
| StatsWorker(Napi::Function callback, StatsBaton *baton, Napi::Function debuglog) : |
| Napi::AsyncWorker(callback), baton(baton), debuglog(Napi::Persistent(debuglog)) {} |
| ~StatsWorker() {} |
|
|
| const int STAT_MIN_INDEX = 0; |
| const int STAT_MAX_INDEX = 1; |
| const int STAT_SUM_INDEX = 2; |
| const int STAT_SQ_SUM_INDEX = 3; |
| const int STAT_MEAN_INDEX = 4; |
| const int STAT_STDEV_INDEX = 5; |
| const int STAT_MINX_INDEX = 6; |
| const int STAT_MINY_INDEX = 7; |
| const int STAT_MAXX_INDEX = 8; |
| const int STAT_MAXY_INDEX = 9; |
|
|
| void Execute() { |
| |
| sharp::counterQueue--; |
|
|
| vips::VImage image; |
| sharp::ImageType imageType = sharp::ImageType::UNKNOWN; |
| try { |
| std::tie(image, imageType) = OpenInput(baton->input); |
| } catch (vips::VError const &err) { |
| (baton->err).append(err.what()); |
| } |
| if (imageType != sharp::ImageType::UNKNOWN) { |
| try { |
| vips::VImage stats = image.stats(); |
| int const bands = image.bands(); |
| for (int b = 1; b <= bands; b++) { |
| ChannelStats cStats( |
| static_cast<int>(stats.getpoint(STAT_MIN_INDEX, b).front()), |
| static_cast<int>(stats.getpoint(STAT_MAX_INDEX, b).front()), |
| stats.getpoint(STAT_SUM_INDEX, b).front(), |
| stats.getpoint(STAT_SQ_SUM_INDEX, b).front(), |
| stats.getpoint(STAT_MEAN_INDEX, b).front(), |
| stats.getpoint(STAT_STDEV_INDEX, b).front(), |
| static_cast<int>(stats.getpoint(STAT_MINX_INDEX, b).front()), |
| static_cast<int>(stats.getpoint(STAT_MINY_INDEX, b).front()), |
| static_cast<int>(stats.getpoint(STAT_MAXX_INDEX, b).front()), |
| static_cast<int>(stats.getpoint(STAT_MAXY_INDEX, b).front())); |
| baton->channelStats.push_back(cStats); |
| } |
| |
| if (sharp::HasAlpha(image)) { |
| double const minAlpha = static_cast<double>(stats.getpoint(STAT_MIN_INDEX, bands).front()); |
| if (minAlpha != sharp::MaximumImageAlpha(image.interpretation())) { |
| baton->isOpaque = false; |
| } |
| } |
| |
| vips::VImage greyscale = image.colourspace(VIPS_INTERPRETATION_B_W)[0]; |
| |
| baton->entropy = std::abs(greyscale.hist_find().hist_entropy()); |
| |
| if (image.width() > 1 || image.height() > 1) { |
| VImage laplacian = VImage::new_matrixv(3, 3, |
| 0.0, 1.0, 0.0, |
| 1.0, -4.0, 1.0, |
| 0.0, 1.0, 0.0); |
| laplacian.set("scale", 9.0); |
| baton->sharpness = greyscale.conv(laplacian).deviate(); |
| } |
| |
| vips::VImage hist = sharp::RemoveAlpha(image) |
| .colourspace(VIPS_INTERPRETATION_sRGB) |
| .hist_find_ndim(VImage::option()->set("bins", 16)); |
| std::complex<double> maxpos = hist.maxpos(); |
| int const dx = static_cast<int>(std::real(maxpos)); |
| int const dy = static_cast<int>(std::imag(maxpos)); |
| std::vector<double> pel = hist(dx, dy); |
| int const dz = std::distance(pel.begin(), std::find(pel.begin(), pel.end(), hist.max())); |
| baton->dominantRed = dx * 16 + 8; |
| baton->dominantGreen = dy * 16 + 8; |
| baton->dominantBlue = dz * 16 + 8; |
| } catch (vips::VError const &err) { |
| (baton->err).append(err.what()); |
| } |
| } |
|
|
| |
| vips_error_clear(); |
| vips_thread_shutdown(); |
| } |
|
|
| void OnOK() { |
| Napi::Env env = Env(); |
| Napi::HandleScope scope(env); |
|
|
| |
| std::string warning = sharp::VipsWarningPop(); |
| while (!warning.empty()) { |
| debuglog.Call(Receiver().Value(), { Napi::String::New(env, warning) }); |
| warning = sharp::VipsWarningPop(); |
| } |
|
|
| if (baton->err.empty()) { |
| |
| Napi::Object info = Napi::Object::New(env); |
| Napi::Array channels = Napi::Array::New(env); |
|
|
| std::vector<ChannelStats>::iterator it; |
| int i = 0; |
| for (it = baton->channelStats.begin(); it < baton->channelStats.end(); it++, i++) { |
| Napi::Object channelStat = Napi::Object::New(env); |
| channelStat.Set("min", it->min); |
| channelStat.Set("max", it->max); |
| channelStat.Set("sum", it->sum); |
| channelStat.Set("squaresSum", it->squaresSum); |
| channelStat.Set("mean", it->mean); |
| channelStat.Set("stdev", it->stdev); |
| channelStat.Set("minX", it->minX); |
| channelStat.Set("minY", it->minY); |
| channelStat.Set("maxX", it->maxX); |
| channelStat.Set("maxY", it->maxY); |
| channels.Set(i, channelStat); |
| } |
|
|
| info.Set("channels", channels); |
| info.Set("isOpaque", baton->isOpaque); |
| info.Set("entropy", baton->entropy); |
| info.Set("sharpness", baton->sharpness); |
| Napi::Object dominant = Napi::Object::New(env); |
| dominant.Set("r", baton->dominantRed); |
| dominant.Set("g", baton->dominantGreen); |
| dominant.Set("b", baton->dominantBlue); |
| info.Set("dominant", dominant); |
| Callback().Call(Receiver().Value(), { env.Null(), info }); |
| } else { |
| Callback().Call(Receiver().Value(), { Napi::Error::New(env, sharp::TrimEnd(baton->err)).Value() }); |
| } |
|
|
| delete baton->input; |
| delete baton; |
| } |
|
|
| private: |
| StatsBaton* baton; |
| Napi::FunctionReference debuglog; |
| }; |
|
|
| |
| |
| |
| Napi::Value stats(const Napi::CallbackInfo& info) { |
| |
| StatsBaton *baton = new StatsBaton; |
| Napi::Object options = info[size_t(0)].As<Napi::Object>(); |
|
|
| |
| baton->input = sharp::CreateInputDescriptor(options.Get("input").As<Napi::Object>()); |
| baton->input->access = VIPS_ACCESS_RANDOM; |
|
|
| |
| Napi::Function debuglog = options.Get("debuglog").As<Napi::Function>(); |
|
|
| |
| Napi::Function callback = info[size_t(1)].As<Napi::Function>(); |
| StatsWorker *worker = new StatsWorker(callback, baton, debuglog); |
| worker->Receiver().Set("options", options); |
| worker->Queue(); |
|
|
| |
| sharp::counterQueue++; |
|
|
| return info.Env().Undefined(); |
| } |
|
|