Ubuntu
60 lines
1.6 KiB
C++
60 lines
1.6 KiB
C++
/**
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* AWB Processor - OpenCV Gray World White Balance
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* Compiled to WASM via Emscripten (MAIN_MODULE, dynamic linking with .so)
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*
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* Reads: /data/input.png (MEMFS, injected by Node.js runner)
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* Writes: /data/output.png (MEMFS, read by Node.js runner)
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* Stdout: metadata string
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*/
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#include <stdio.h>
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#include <opencv2/core.hpp>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/imgcodecs.hpp>
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int main() {
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const char* input = "/data/input.png";
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const char* output = "/data/output.png";
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cv::Mat img = cv::imread(input);
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if (img.empty()) {
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fprintf(stderr, "ERR:Failed to read: %s\n", input);
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return 1;
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}
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int h = img.rows, w = img.cols;
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// Convert to float for accuracy
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cv::Mat imgf;
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img.convertTo(imgf, CV_32FC3);
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// Split channels (BGR order in OpenCV)
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std::vector<cv::Mat> ch;
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cv::split(imgf, ch);
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// Compute channel means
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cv::Scalar m = cv::mean(imgf);
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// Gray World: average of all channels
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float avg = (m[0] + m[1] + m[2]) / 3.0f;
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// Scale each channel so its mean equals the global average
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if (m[0] > 0.01f) ch[0] *= (avg / m[0]); // B
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if (m[1] > 0.01f) ch[1] *= (avg / m[1]); // G
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if (m[2] > 0.01f) ch[2] *= (avg / m[2]); // R
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// Merge and convert back
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cv::merge(ch, imgf);
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imgf.convertTo(img, CV_8UC3);
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// Write output
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cv::imwrite(output, img);
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// Metadata to stderr (runner reads pure base64 from stdout)
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fprintf(stderr, "OK:%dx%d:M=%.2f,%.2f,%.2f:S=%.4f,%.4f,%.4f\n",
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w, h,
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m[2], m[1], m[0], // RGB means
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avg / m[2], avg / m[1], avg / m[0]); // RGB scales
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return 0;
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}
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