示例#1
0
文件: filter.cpp 项目: scott89/cv_exe
void FiltMaxImg(const Img& in,  const int k_width, const int k_height, const int channel, Img& out) {
    const int width = in.width();
    const int height = in.height();
    const int num_channel = in.channel();
    assert(num_channel > channel);
    out.Reshape(width, height, 1);
    const double* in_data = in.data();
    double* out_data = out.mutable_data();

    for(int h = 0; h < height; h++) {
	for (int w = 0; w < width; w++) {
	    int w_start = w - ((k_width) / 2);
	    int h_start = h - ((k_height) / 2);
	    int kw_start = 0;
	    int kh_start = 0;
	    int kw_end = k_width;
	    int kh_end = k_height;
	    double max_value = -MAX_DOUBLE;
	    for (int i = kh_start; i < kh_end; i++ ) {
		for (int j = kw_start; j < kw_end; j++) {
		    int w_temp = w_start + j;
		    int h_temp = h_start + i;
		    if (w_temp >=0 && w_temp < width && h_temp >= 0 && h_temp < height) {
			max_value = std::max(max_value, in_data[h_temp * width + w_temp]);
		    }
		}
	    }
	    out_data[h * width + w] = max_value;
	}
    }

}
示例#2
0
文件: filter.cpp 项目: scott89/cv_exe
void FiltMedImg(const Img& in,  const int k_width, const int k_height, const int channel, Img& out) {
    const int width = in.width();
    const int height = in.height();
    const int num_channel = in.channel();
    assert(num_channel > channel);
    out.Reshape(width, height, 1);
    const double* in_data = in.data();
    double* out_data = out.mutable_data();

    for(int h = 0; h < height; h++) {
	for (int w = 0; w < width; w++) {
	    int w_start = w - ((k_width) / 2);
	    int h_start = h - ((k_height) / 2);
	    int kw_start = 0;
	    int kh_start = 0;
	    int kw_end = k_width;
	    int kh_end = k_height;
	    std::vector<double> temp_list;
	    for (int i = kh_start; i < kh_end; i++ ) {
		for (int j = kw_start; j < kw_end; j++) {
		    int w_temp = w_start + j;
		    int h_temp = h_start + i;
		    if (w_temp >=0 && w_temp < width && h_temp >= 0 && h_temp < height) {
			temp_list.push_back(in_data[h_temp * width + w_temp]);
		    }
		}
	    }
	    std::sort(temp_list.begin(), temp_list.end());
	    out_data[h * width + w] = temp_list[temp_list.size()/2];
	}
    }

}
示例#3
0
int main() {
    float scale     = 400.f;
    float offset_x  = 5.9f;
    float offset_y  = 5.1f;
    float offset_z  = 0.05f;
    float lacunarity    = 1.99f;
    float persistance   = 0.5f;

    Img img;

    while (!img.is_closed()) {
        Measure measure;
        measure.start();
        const SimplexNoise simplex(0.1f/scale, 0.5f, lacunarity, persistance); // Amplitude of 0.5 for the 1st octave : sum ~1.0f
        const int octaves = static_cast<int>(5 + std::log(scale)); // Estimate number of octaves needed for the current scale
        std::ostringstream title;
        title << "2D Simplex Perlin noise (" << octaves << " octaves)";
        img.set_title(title.str().c_str());
        for (int row = 0; row < img.height(); ++row) {
            const float y = static_cast<float>(row - img.height()/2 + offset_y*scale);
            for (int col = 0; col < img.width(); ++col) {
                const float x = static_cast<float>(col - img.width()/2 + offset_x*scale);
                
                // TODO(SRombauts): Add 'erosion' with simple smoothing like exponential, and other 'modifiers' like in libnoise
                // Generate "biomes", ie smooth geographic variation in frequency & amplitude, 
                // and add smaller details, summing the noise values for the coordinate
                const float noise = simplex.fractal(octaves, x, y) + offset_z;
                const color3f color = ramp(noise); // convert to color
                img.draw_point(col, row, (float*)&color);
            }
        }
        img.display();
        const double diff_ms = measure.get();
        std::cout << std::fixed << diff_ms << "ms\n";

        img.user(scale, offset_x, offset_y, offset_z, lacunarity, persistance);
    }

    return 0;
}
示例#4
0
文件: filter.cpp 项目: scott89/cv_exe
void FiltImg(const Img& in, const Img& filter, const int channel, Img& out) {
    const int width = in.width();
    const int height = in.height();
    const int num_channel = in.channel();
    assert(num_channel > channel);
    out.Reshape(width, height, 1);
    const double* in_data = in.data() + channel * out.dim();
    const double* filter_data = filter.data();
    double* out_data = out.mutable_data();
    const int k_width = filter.width();
    const int k_height = filter.height();
    for(int h = 0; h < height; h++) {
	for (int w = 0; w < width; w++) {
	    int w_start = w - ((k_width) / 2);
	    int h_start = h - ((k_height) / 2);
	    int kw_start = 0;
	    int kh_start = 0;
	    int kw_end = k_width;
	    int kh_end = k_height;
	    double sum = 0;
	    for (int i = kh_start; i < kh_end; i++ ) {
		for (int j = kw_start; j < kw_end; j++) {
		    int w_temp = w_start + j;
		    int h_temp = h_start + i;
		    if (w_temp >=0 && w_temp < width && h_temp >= 0 && h_temp < height) {
			sum += in_data[h_temp * width + w_temp] * filter_data[i * k_width + j];
                       //printf("%f x %f, ", in_data[h_temp * width + w_temp],  filter_data[i * k_width + j]);
                        //printf("%d %d, \n", h_temp, w_temp);
		    }
		}
	    }
	    out_data[h * width + w] = sum;
	}
    }

}