Method run

test/cv/ImageProcessTest.cpp:191–225

public:
    virtual ~ImageProcessGrayToGrayNearestTransformTest() = default;
    virtual bool run(int precision) {
        ImageProcess::Config config;
        config.sourceFormat = GRAY;
        config.destFormat   = GRAY;
        config.filterType   = MNN::CV::Filter::NEAREST;
        config.wrap         = ZERO;
        std::shared_ptr<ImageProcess> process(ImageProcess::create(config));

        int sw = 1280;
        int sh = 720;
        int dw = 360;
        int dh = 640;
        Matrix tr;
        tr.setScale(1.0 / sw, 1.0 / sh);
        tr.postRotate(90, 0.5f, 0.5f);
        tr.postScale(dw, dh);
        tr.invert(&tr);
        process->setMatrix(tr);

        auto integers = genSourceData(sh, sw, 1);
        std::shared_ptr<Tensor> tensor(
            Tensor::create<float>(std::vector<int>{1, 1, dw, dh}, nullptr, Tensor::CAFFE_C4));
        for (int i = 0; i < 10; ++i) {
            process->convert(integers.data(), sw, sh, 0, tensor.get());
        }
        auto floats  = tensor->host<float>();
        int expect[] = {0, 4, 16, 36, 64, 21, 65, 38, 19, 8};
        for (int v = 0; v < 10; ++v) {
            if ((int)(floats[4 * v]) != expect[v]) {
                MNN_ERROR("Error for %d, %.f, correct=%d\n", v, floats[4 * v], expect[v]);
                return false;
            }
        }
        return true;
    }
};
MNNTestSuiteRegister(ImageProcessGrayToGrayNearestTransformTest, "cv/image_process/gray_to_gray_nearest_transorm");