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https://github.com/Relintai/pmlpp.git
synced 2024-12-21 14:56:47 +01:00
Added more getters and setters to MLPPTensor3.
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c707095f2d
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40751bf79a
@ -531,6 +531,78 @@ void MLPPTensor3::set_z_slice_mlpp_matrix(int p_index_z, const Ref<MLPPMatrix> &
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}
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}
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void MLPPTensor3::get_x_slice_into(int p_index_x, Ref<MLPPMatrix> target) const {
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ERR_FAIL_INDEX(p_index_x, _size.x);
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ERR_FAIL_COND(!target.is_valid());
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if (unlikely(target->size() != Size2i(_size.y, _size.z))) {
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target->resize(Size2i(_size.y, _size.z));
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}
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for (int z = 0; z < _size.z; ++z) {
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for (int y = 0; y < _size.y; ++y) {
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target->set_element(z, y, get_element(p_index_x, y, z));
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}
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}
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}
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Ref<MLPPMatrix> MLPPTensor3::get_x_slice(int p_index_x) const {
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ERR_FAIL_INDEX_V(p_index_x, _size.x, Ref<MLPPMatrix>());
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Ref<MLPPMatrix> m;
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m.instance();
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get_x_slice_into(p_index_x, m);
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return m;
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}
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void MLPPTensor3::set_x_slice(int p_index_x, const Ref<MLPPMatrix> &p_mat) {
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ERR_FAIL_INDEX(p_index_x, _size.x);
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ERR_FAIL_COND(!p_mat.is_valid());
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ERR_FAIL_COND(p_mat->size() != Size2i(_size.y, _size.z));
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for (int z = 0; z < _size.z; ++z) {
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for (int y = 0; y < _size.y; ++y) {
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set_element(p_index_x, y, z, p_mat->get_element(z, y));
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}
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}
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}
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void MLPPTensor3::get_y_slice_into(int p_index_y, Ref<MLPPMatrix> target) const {
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ERR_FAIL_INDEX(p_index_y, _size.y);
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ERR_FAIL_COND(!target.is_valid());
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if (unlikely(target->size() != Size2i(_size.y, _size.z))) {
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target->resize(Size2i(_size.x, _size.z));
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}
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for (int z = 0; z < _size.z; ++z) {
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for (int x = 0; x < _size.x; ++x) {
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target->set_element(z, x, get_element(x, p_index_y, z));
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}
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}
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}
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Ref<MLPPMatrix> MLPPTensor3::get_y_slice(int p_index_y) const {
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ERR_FAIL_INDEX_V(p_index_y, _size.y, Ref<MLPPMatrix>());
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Ref<MLPPMatrix> m;
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m.instance();
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get_y_slice_into(p_index_y, m);
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return m;
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}
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void MLPPTensor3::set_y_slice(int p_index_y, const Ref<MLPPMatrix> &p_mat) {
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ERR_FAIL_INDEX(p_index_y, _size.y);
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ERR_FAIL_COND(!p_mat.is_valid());
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ERR_FAIL_COND(p_mat->size() != Size2i(_size.y, _size.z));
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for (int z = 0; z < _size.z; ++z) {
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for (int x = 0; x < _size.x; ++x) {
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set_element(x, p_index_y, z, p_mat->get_element(z, x));
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}
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}
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}
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void MLPPTensor3::add_z_slices_image(const Ref<Image> &p_img, const int p_channels) {
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ERR_FAIL_COND(!p_img.is_valid());
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@ -952,6 +1024,268 @@ void MLPPTensor3::set_from_image(const Ref<Image> &p_img, const int p_channels)
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img->unlock();
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}
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Ref<Image> MLPPTensor3::get_x_slice_image(const int p_index_x) const {
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ERR_FAIL_INDEX_V(p_index_x, _size.x, Ref<Image>());
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Ref<Image> image;
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image.instance();
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if (data_size() == 0) {
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return image;
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}
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PoolByteArray arr;
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arr.resize(_size.y * _size.z);
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PoolByteArray::Write w = arr.write();
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uint8_t *wptr = w.ptr();
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int i = 0;
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for (int z = 0; z < _size.z; ++z) {
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for (int y = 0; y < _size.y; ++y) {
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wptr[i] = static_cast<uint8_t>(get_element(p_index_x, y, z) * 255.0);
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++i;
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}
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}
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image->create(_size.y, _size.z, false, Image::FORMAT_L8, arr);
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return image;
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}
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void MLPPTensor3::get_x_slice_into_image(Ref<Image> p_target, const int p_index_x, const int p_target_channels) const {
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ERR_FAIL_INDEX(p_index_x, _size.x);
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ERR_FAIL_COND(!p_target.is_valid());
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int channel_count = 0;
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int channels[4];
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if (p_target_channels & IMAGE_CHANNEL_FLAG_R) {
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channels[channel_count] = 0;
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++channel_count;
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}
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if (p_target_channels & IMAGE_CHANNEL_FLAG_G) {
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channels[channel_count] = 1;
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++channel_count;
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}
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if (p_target_channels & IMAGE_CHANNEL_FLAG_B) {
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channels[channel_count] = 2;
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++channel_count;
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}
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if (p_target_channels & IMAGE_CHANNEL_FLAG_A) {
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channels[channel_count] = 3;
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++channel_count;
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}
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ERR_FAIL_COND(channel_count == 0);
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if (data_size() == 0) {
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p_target->clear();
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return;
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}
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Size2i img_size = Size2i(p_target->get_width(), p_target->get_height());
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Size2i fms = Size2i(_size.y, _size.z);
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if (img_size != fms) {
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bool mip_maps = p_target->has_mipmaps();
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p_target->resize(fms.x, fms.y, Image::INTERPOLATE_NEAREST);
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if (p_target->has_mipmaps() != mip_maps) {
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if (mip_maps) {
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p_target->generate_mipmaps();
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} else {
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p_target->clear_mipmaps();
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}
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}
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}
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p_target->lock();
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for (int y = 0; y < fms.y; ++y) {
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for (int z = 0; z < fms.x; ++z) {
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Color c;
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float e = get_element(y, p_index_x, z);
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for (int i = 0; i < channel_count; ++i) {
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c[channels[i]] = e;
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}
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p_target->set_pixel(z, y, c);
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}
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}
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p_target->unlock();
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}
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void MLPPTensor3::set_x_slice_image(const Ref<Image> &p_img, const int p_index_x, const int p_image_channel_flag) {
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ERR_FAIL_COND(!p_img.is_valid());
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ERR_FAIL_INDEX(p_index_x, _size.x);
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int channel_index = -1;
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for (int i = 0; i < 4; ++i) {
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if (((p_image_channel_flag & (1 << i)) != 0)) {
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channel_index = i;
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break;
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}
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}
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ERR_FAIL_INDEX(channel_index, 4);
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Size2i img_size = Size2i(p_img->get_width(), p_img->get_height());
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Size2i fms = Size2i(_size.y, _size.z);
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ERR_FAIL_COND(img_size != fms);
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Ref<Image> img = p_img;
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img->lock();
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for (int y = 0; y < fms.y; ++y) {
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for (int z = 0; z < fms.x; ++z) {
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Color c = img->get_pixel(z, y);
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set_element(y, p_index_x, z, c[channel_index]);
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}
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}
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img->unlock();
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}
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Ref<Image> MLPPTensor3::get_y_slice_image(const int p_index_y) const {
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ERR_FAIL_INDEX_V(p_index_y, _size.y, Ref<Image>());
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Ref<Image> image;
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image.instance();
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if (data_size() == 0) {
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return image;
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}
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PoolByteArray arr;
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arr.resize(_size.x * _size.z);
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PoolByteArray::Write w = arr.write();
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uint8_t *wptr = w.ptr();
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int i = 0;
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for (int z = 0; z < _size.z; ++z) {
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for (int x = 0; x < _size.x; ++x) {
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wptr[i] = static_cast<uint8_t>(get_element(x, p_index_y, z) * 255.0);
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++i;
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}
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}
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image->create(_size.x, _size.z, false, Image::FORMAT_L8, arr);
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return image;
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}
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void MLPPTensor3::get_y_slice_into_image(Ref<Image> p_target, const int p_index_y, const int p_target_channels) const {
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ERR_FAIL_INDEX(p_index_y, _size.y);
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ERR_FAIL_COND(!p_target.is_valid());
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int channel_count = 0;
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int channels[4];
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if (p_target_channels & IMAGE_CHANNEL_FLAG_R) {
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channels[channel_count] = 0;
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++channel_count;
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}
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if (p_target_channels & IMAGE_CHANNEL_FLAG_G) {
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channels[channel_count] = 1;
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++channel_count;
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}
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if (p_target_channels & IMAGE_CHANNEL_FLAG_B) {
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channels[channel_count] = 2;
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++channel_count;
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}
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if (p_target_channels & IMAGE_CHANNEL_FLAG_A) {
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channels[channel_count] = 3;
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++channel_count;
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}
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ERR_FAIL_COND(channel_count == 0);
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if (data_size() == 0) {
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p_target->clear();
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return;
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}
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Size2i img_size = Size2i(p_target->get_width(), p_target->get_height());
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Size2i fms = Size2i(_size.x, _size.z);
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if (img_size != fms) {
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bool mip_maps = p_target->has_mipmaps();
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p_target->resize(fms.x, fms.y, Image::INTERPOLATE_NEAREST);
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if (p_target->has_mipmaps() != mip_maps) {
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if (mip_maps) {
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p_target->generate_mipmaps();
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} else {
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p_target->clear_mipmaps();
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}
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}
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}
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p_target->lock();
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for (int x = 0; x < fms.y; ++x) {
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for (int z = 0; z < fms.x; ++z) {
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Color c;
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float e = get_element(p_index_y, x, z);
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for (int i = 0; i < channel_count; ++i) {
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c[channels[i]] = e;
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}
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p_target->set_pixel(z, x, c);
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}
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}
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p_target->unlock();
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}
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void MLPPTensor3::set_y_slice_image(const Ref<Image> &p_img, const int p_index_y, const int p_image_channel_flag) {
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ERR_FAIL_COND(!p_img.is_valid());
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ERR_FAIL_INDEX(p_index_y, _size.y);
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int channel_index = -1;
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for (int i = 0; i < 4; ++i) {
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if (((p_image_channel_flag & (1 << i)) != 0)) {
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channel_index = i;
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break;
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}
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}
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ERR_FAIL_INDEX(channel_index, 4);
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Size2i img_size = Size2i(p_img->get_width(), p_img->get_height());
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Size2i fms = Size2i(_size.x, _size.z);
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ERR_FAIL_COND(img_size != fms);
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Ref<Image> img = p_img;
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img->lock();
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for (int z = 0; z < fms.y; ++z) {
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for (int x = 0; x < fms.x; ++x) {
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Color c = img->get_pixel(x, z);
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set_element(p_index_y, x, z, c[channel_index]);
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}
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}
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img->unlock();
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}
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void MLPPTensor3::add(const Ref<MLPPTensor3> &B) {
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ERR_FAIL_COND(!B.is_valid());
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ERR_FAIL_COND(_size != B->size());
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@ -1943,6 +2277,14 @@ void MLPPTensor3::_bind_methods() {
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ClassDB::bind_method(D_METHOD("set_z_slice_mlpp_vector", "index_z", "row"), &MLPPTensor3::set_z_slice_mlpp_vector);
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ClassDB::bind_method(D_METHOD("set_z_slice_mlpp_matrix", "index_z", "mat"), &MLPPTensor3::set_z_slice_mlpp_matrix);
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ClassDB::bind_method(D_METHOD("get_x_slice_into", "index_x", "target"), &MLPPTensor3::get_x_slice_into);
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ClassDB::bind_method(D_METHOD("get_x_slice", "index_x"), &MLPPTensor3::get_x_slice);
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ClassDB::bind_method(D_METHOD("set_x_slice", "index_x", "mat"), &MLPPTensor3::set_x_slice);
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ClassDB::bind_method(D_METHOD("get_y_slice_into", "index_y", "target"), &MLPPTensor3::get_y_slice_into);
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ClassDB::bind_method(D_METHOD("get_y_slice", "index_y"), &MLPPTensor3::get_y_slice);
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ClassDB::bind_method(D_METHOD("set_y_slice", "index_y", "mat"), &MLPPTensor3::set_y_slice);
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ClassDB::bind_method(D_METHOD("add_z_slices_image", "img", "channels"), &MLPPTensor3::add_z_slices_image, IMAGE_CHANNEL_FLAG_RGBA);
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ClassDB::bind_method(D_METHOD("get_z_slice_image", "index_z"), &MLPPTensor3::get_z_slice_image);
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@ -1956,6 +2298,14 @@ void MLPPTensor3::_bind_methods() {
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ClassDB::bind_method(D_METHOD("set_from_image", "img", "channels"), &MLPPTensor3::set_from_image, IMAGE_CHANNEL_FLAG_RGBA);
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ClassDB::bind_method(D_METHOD("get_x_slice_image", "index_x"), &MLPPTensor3::get_x_slice_image);
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ClassDB::bind_method(D_METHOD("get_x_slice_into_image", "target", "index_x", "target_channels"), &MLPPTensor3::get_x_slice_into_image, IMAGE_CHANNEL_FLAG_RGB);
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ClassDB::bind_method(D_METHOD("set_x_slice_image", "img", "index_x", "image_channel_flag"), &MLPPTensor3::set_x_slice_image, IMAGE_CHANNEL_FLAG_R);
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ClassDB::bind_method(D_METHOD("get_y_slice_image", "index_x"), &MLPPTensor3::get_y_slice_image);
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ClassDB::bind_method(D_METHOD("get_y_slice_into_image", "target", "index_x", "target_channels"), &MLPPTensor3::get_y_slice_into_image, IMAGE_CHANNEL_FLAG_RGB);
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ClassDB::bind_method(D_METHOD("set_y_slice_image", "img", "index_x", "image_channel_flag"), &MLPPTensor3::set_y_slice_image, IMAGE_CHANNEL_FLAG_R);
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ClassDB::bind_method(D_METHOD("fill", "val"), &MLPPTensor3::fill);
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ClassDB::bind_method(D_METHOD("to_flat_pool_vector"), &MLPPTensor3::to_flat_pool_vector);
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@ -125,6 +125,19 @@ public:
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void set_z_slice_mlpp_vector(int p_index_z, const Ref<MLPPVector> &p_row);
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void set_z_slice_mlpp_matrix(int p_index_z, const Ref<MLPPMatrix> &p_mat);
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//TODO resize() need to be reworked for add and remove to work, in any other direction than z
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//void add_x_slice(const Ref<MLPPMatrix> &p_matrix);
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//void remove_x_slice(int p_index);
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void get_x_slice_into(int p_index_x, Ref<MLPPMatrix> target) const;
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Ref<MLPPMatrix> get_x_slice(int p_index_x) const;
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void set_x_slice(int p_index_x, const Ref<MLPPMatrix> &p_mat);
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//void add_y_slice(const Ref<MLPPMatrix> &p_matrix);
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//void remove_y_slice(int p_index);
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void get_y_slice_into(int p_index_y, Ref<MLPPMatrix> target) const;
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Ref<MLPPMatrix> get_y_slice(int p_index_y) const;
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void set_y_slice(int p_index_y, const Ref<MLPPMatrix> &p_mat);
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public:
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//Image api
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@ -156,6 +169,16 @@ public:
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void set_from_image(const Ref<Image> &p_img, const int p_channels = IMAGE_CHANNEL_FLAG_RGBA);
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//void add_x_slices_image(const Ref<Image> &p_img, const int p_channels = IMAGE_CHANNEL_FLAG_RGBA);
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Ref<Image> get_x_slice_image(const int p_index_x) const;
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void get_x_slice_into_image(Ref<Image> p_target, const int p_index_x, const int p_target_channels = IMAGE_CHANNEL_FLAG_RGB) const;
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void set_x_slice_image(const Ref<Image> &p_img, const int p_index_x, const int p_image_channel_flag = IMAGE_CHANNEL_FLAG_R);
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//void add_y_slices_image(const Ref<Image> &p_img, const int p_channels = IMAGE_CHANNEL_FLAG_RGBA);
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Ref<Image> get_y_slice_image(const int p_index_y) const;
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void get_y_slice_into_image(Ref<Image> p_target, const int p_index_y, const int p_target_channels = IMAGE_CHANNEL_FLAG_RGB) const;
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void set_y_slice_image(const Ref<Image> &p_img, const int p_index_y, const int p_image_channel_flag = IMAGE_CHANNEL_FLAG_R);
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public:
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//math api
|
||||
|
||||
|
||||
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Reference in New Issue
Block a user