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/*!
Copyright 2013 Lovell Fuller and others.
SPDX-License-Identifier: Apache-2.0
*/
#include <iostream>
#include <numeric>
#include <string>
#include <vector>
#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() {
// Decrement queued task counter
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);
}
// Image is not opaque when alpha layer is present and contains a non-mamixa value
if (image.has_alpha()) {
double const minAlpha = static_cast<double>(stats.getpoint(STAT_MIN_INDEX, bands).front());
if (minAlpha != vips_interpretation_max_alpha(image.interpretation())) {
baton->isOpaque = false;
}
}
// Convert to greyscale
vips::VImage greyscale = image.colourspace(VIPS_INTERPRETATION_B_W)[0];
// Estimate entropy via histogram of greyscale value frequency
baton->entropy = std::abs(greyscale.hist_find().hist_entropy());
// Estimate sharpness via standard deviation of greyscale laplacian
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();
}
// Most dominant sRGB colour via 4096-bin 3D histogram
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());
}
}
// Clean up
vips_error_clear();
vips_thread_shutdown();
}
void OnOK() {
Napi::Env env = Env();
Napi::HandleScope scope(env);
// Handle warnings
std::string warning = sharp::VipsWarningPop();
while (!warning.empty()) {
debuglog.Call(Receiver().Value(), { Napi::String::New(env, warning) });
warning = sharp::VipsWarningPop();
}
if (baton->err.empty()) {
// Stats Object
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;
};
/*
stats(options, callback)
*/
Napi::Value stats(const Napi::CallbackInfo& info) {
// V8 objects are converted to non-V8 types held in the baton struct
StatsBaton *baton = new StatsBaton;
Napi::Object options = info[size_t(0)].As<Napi::Object>();
// Input
baton->input = sharp::CreateInputDescriptor(options.Get("input").As<Napi::Object>());
baton->input->access = VIPS_ACCESS_RANDOM;
// Function to notify of libvips warnings
Napi::Function debuglog = options.Get("debuglog").As<Napi::Function>();
// Join queue for worker thread
Napi::Function callback = info[size_t(1)].As<Napi::Function>();
StatsWorker *worker = new StatsWorker(callback, baton, debuglog);
worker->Receiver().Set("options", options);
worker->Queue();
// Increment queued task counter
sharp::counterQueue++;
return info.Env().Undefined();
}