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Update api && comments

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This commit is contained in:
felixhjh
2023-02-14 03:18:54 +00:00
parent 0a6ce5a6ed
commit 619b561817
4 changed files with 37 additions and 21 deletions
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37
fastdeploy/vision/visualize/matting.cc
View File

@@ -19,8 +19,8 @@ namespace fastdeploy {
namespace vision {
cv::Mat VisMatting(const cv::Mat& im, const MattingResult& result,
bool remove_small_connected_area, bool is_transparent,
float transparent_threshold) {
bool transparent_background, float transparent_threshold,
bool remove_small_connected_area) {
FDASSERT((!im.empty()), "im can't be empty!");
auto vis_img = im.clone();
@@ -44,8 +44,8 @@ cv::Mat VisMatting(const cv::Mat& im, const MattingResult& result,
if ((vis_img).type() != CV_8UC3) {
(vis_img).convertTo((vis_img), CV_8UC3);
}
if(is_transparent) {
if (transparent_background) {
if (vis_img.channels() != 4) {
cv::cvtColor(vis_img, transparent_vis_mat, cv::COLOR_BGR2BGRA);
vis_img = transparent_vis_mat;
@@ -60,17 +60,24 @@ cv::Mat VisMatting(const cv::Mat& im, const MattingResult& result,
for (size_t i = 0; i < height; ++i) {
for (size_t j = 0; j < width; ++j) {
float alpha_val = alpha_data[i * width + j];
vis_data[i * width * channel + j * channel + 0] = cv::saturate_cast<uchar>(
static_cast<float>(im_data[i * width * 3 + j * 3 + 0]) * alpha_val +
(1.f - alpha_val) * 153.f);
vis_data[i * width * channel + j * channel + 1] = cv::saturate_cast<uchar>(
static_cast<float>(im_data[i * width * 3 + j * 3 + 1]) * alpha_val +
(1.f - alpha_val) * 255.f);
vis_data[i * width * channel + j * channel + 2] = cv::saturate_cast<uchar>(
static_cast<float>(im_data[i * width * 3 + j * 3 + 2]) * alpha_val +
(1.f - alpha_val) * 120.f);
if (is_transparent && alpha_val < transparent_threshold) {
vis_data[i * width * channel + j * channel + 3] = cv::saturate_cast<uchar>(0.f);
vis_data[i * width * channel + j * channel + 0] =
cv::saturate_cast<uchar>(
static_cast<float>(im_data[i * width * 3 + j * 3 + 0]) *
alpha_val +
(1.f - alpha_val) * 153.f);
vis_data[i * width * channel + j * channel + 1] =
cv::saturate_cast<uchar>(
static_cast<float>(im_data[i * width * 3 + j * 3 + 1]) *
alpha_val +
(1.f - alpha_val) * 255.f);
vis_data[i * width * channel + j * channel + 2] =
cv::saturate_cast<uchar>(
static_cast<float>(im_data[i * width * 3 + j * 3 + 2]) *
alpha_val +
(1.f - alpha_val) * 120.f);
if (transparent_background && alpha_val < transparent_threshold) {
vis_data[i * width * channel + j * channel + 3] =
cv::saturate_cast<uchar>(0.f);
}
}
}

6
fastdeploy/vision/visualize/visualize.h
View File

@@ -143,16 +143,16 @@ FASTDEPLOY_DECL cv::Mat VisSegmentation(const cv::Mat& im,
*
* \param[in] im the input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format
* \param[in] result the result produced by model
* \param[in] remove_small_connected_area if remove_small_connected_area==true, the visualized result will not include the small connected areas
* \param[in] is_transparent if is_transparent==true, the background will with transparent color
* \param[in] transparent_threshold since the alpha value in MattringResult is a float between [0, 1], transparent_threshold is used to filter background pixel
* \param[in] remove_small_connected_area if remove_small_connected_area==true, the visualized result will not include the small connected areas
* \return cv::Mat type stores the visualized results
*/
FASTDEPLOY_DECL cv::Mat VisMatting(const cv::Mat& im,
const MattingResult& result,
bool remove_small_connected_area = false,
bool is_transparent = false,
float transparent_threshold = 0.999);
float transparent_threshold = 0.999
bool remove_small_connected_area = false);
/** \brief Show the visualized results for Ocr models
*
* \param[in] im the input image data, comes from cv::imread(), is a 3-D array with layout HWC, BGR format

6
fastdeploy/vision/visualize/visualize_pybind.cc
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@@ -102,10 +102,12 @@ void BindVisualize(pybind11::module& m) {
})
.def("vis_matting",
[](pybind11::array& im_data, vision::MattingResult& result,
bool transparent_background, bool transparent_threshold,
bool remove_small_connected_area) {
cv::Mat im = PyArrayToCvMat(im_data);
auto vis_im =
vision::VisMatting(im, result, remove_small_connected_area);
auto vis_im = vision::VisMatting(
im, result, transparent_background, transparent_threshold,
remove_small_connected_area);
FDTensor out;
vision::Mat(vis_im).ShareWithTensor(&out);
return TensorToPyArray(out);

9
python/fastdeploy/vision/visualize/__init__.py
View File

@@ -95,15 +95,22 @@ def vis_matting_alpha(im_data,
remove_small_connected_area)
def vis_matting(im_data, matting_result, remove_small_connected_area=False):
def vis_matting(im_data,
matting_result,
transparent_background=False,
transparent_threshold=0.99,
remove_small_connected_area=False):
"""Show the visualized results for matting models
:param im_data: (numpy.ndarray)The input image data, 3-D array with layout HWC, BGR format
:param matting_result: the result produced by model
:param transparent_background: whether visulizing matting result with transparent background
:param transparent_threshold: since the alpha value in MattringResult is a float between [0, 1], transparent_threshold is used to filter background pixel
:param remove_small_connected_area: (bool) if remove_small_connected_area==True, the visualized result will not include the small connected areas
:return: (numpy.ndarray) image with visualized results
"""
return C.vision.vis_matting(im_data, matting_result,
transparent_background, transparent_threshold,
remove_small_connected_area)