wehub-resource-sync
104 lines
3.1 KiB
C++
104 lines
3.1 KiB
C++
//
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// miscellaneous.cpp
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// MNN
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//
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// Created by MNN on 2021/08/20.
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// Copyright © 2018, Alibaba Group Holding Limited
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//
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#include "cv/imgproc/miscellaneous.hpp"
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#include "cv/imgproc/filter.hpp"
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#include <MNN/ImageProcess.hpp>
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#include <MNN/expr/NeuralNetWorkOp.hpp>
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#include <MNN/expr/MathOp.hpp>
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namespace MNN {
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namespace CV {
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VARP adaptiveThreshold(VARP src, double maxValue, int adaptiveMethod, int thresholdType, int blockSize, double C) {
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auto origin_type = src->getInfo()->type;
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src = _Cast<float>(src);
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// get threshold
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VARP threshold;
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if (adaptiveMethod == ADAPTIVE_THRESH_MEAN_C) {
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threshold = boxFilter(src, -1, {blockSize, blockSize}, true, REFLECT);
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} else {
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threshold = GaussianBlur(src, {blockSize, blockSize}, 0, 0, REFLECT);
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}
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threshold = _Unsqueeze(threshold, {-1}) - _Scalar<float>(C);
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VARP dst;
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maxValue = maxValue > 255 ? 255 : maxValue;
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maxValue = maxValue < 0 ? 0 : maxValue;
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auto maxval = _Scalar<float>(maxValue);
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if (thresholdType == THRESH_BINARY) {
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dst = _Cast<float>(_Greater(src, threshold)) * maxval;
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} else {
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dst = _Cast<float>(_LessEqual(src, threshold)) * maxval;
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}
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return _Cast(dst, origin_type);
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}
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VARP blendLinear(VARP src1, VARP src2, VARP weight1, VARP weight2) {
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auto inputInfo = src1->getInfo();
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auto origin_type = inputInfo->type;
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if (origin_type.code != halide_type_float) {
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src1 = _Cast<float>(src1);
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src2 = _Cast<float>(src2);
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weight1 = _Cast<float>(weight1);
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weight2 = _Cast<float>(weight2);
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return _Cast((src1 * weight1 + src2 * weight2) / (weight1 + weight2 + _Scalar<float>(1e-5)), origin_type);
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}
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return _Cast((src1 * weight1 + src2 * weight2) / (weight1 + weight2 + _Scalar<float>(1e-5)), origin_type);
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}
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void distanceTransform(VARP src, VARP& dst, VARP& labels, int distanceType, int maskSize, int labelType) {
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// TODO
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}
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int floodFill(VARP image, std::pair<int, int> seedPoint, float newVal) {
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// TODO
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return 0;
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}
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VARP integral(VARP src, VARP& sum, int sdepth) {
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// TODO
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return nullptr;
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}
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VARP threshold(VARP src, double thresh, double maxval, int type) {
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auto origin_type = src->getInfo()->type;
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src = _Cast(src, halide_type_of<float>());
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auto mask = _Threshold(src, thresh);
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VARP dst;
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switch (type) {
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case THRESH_BINARY:
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dst = mask * _Scalar<float>(maxval);
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break;
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case THRESH_BINARY_INV:
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dst = (_Scalar<float>(1.f) - mask) * _Scalar<float>(maxval);
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break;
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case THRESH_TRUNC:
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dst = mask * _Scalar<float>(thresh) + (_Scalar<float>(1.f) - mask) * src;
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break;
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case THRESH_TOZERO:
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dst = mask * src;
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break;
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case THRESH_TOZERO_INV:
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dst = (_Scalar<float>(1.f) - mask) * src;
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break;
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case THRESH_MASK:
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case THRESH_OTSU:
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case THRESH_TRIANGLE:
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MNN_ERROR("Don't support THRESH_MASK/THRESH_OTSU/THRESH_TRIANGLE.");
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break;
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default:
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break;
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}
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return _Cast(dst, origin_type);
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}
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} // CV
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} // MNN
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