提交 947470a3 编写于 作者: L LDOUBLEV

fix error

上级 2ab0ba91
...@@ -89,97 +89,98 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes, ...@@ -89,97 +89,98 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes,
} }
std::cout << "\tscore: " << score << std::endl; std::cout << "\tscore: " << score << std::endl;
} }
}
void CRNNRecognizer::LoadModel(const std::string &model_dir) {
// AnalysisConfig config; void CRNNRecognizer::LoadModel(const std::string &model_dir) {
paddle_infer::Config config; // AnalysisConfig config;
config.SetModel(model_dir + "/inference.pdmodel", paddle_infer::Config config;
model_dir + "/inference.pdiparams"); config.SetModel(model_dir + "/inference.pdmodel",
model_dir + "/inference.pdiparams");
if (this->use_gpu_) {
config.EnableUseGpu(this->gpu_mem_, this->gpu_id_); if (this->use_gpu_) {
if (this->use_tensorrt_) { config.EnableUseGpu(this->gpu_mem_, this->gpu_id_);
config.EnableTensorRtEngine( if (this->use_tensorrt_) {
1 << 20, 10, 3, config.EnableTensorRtEngine(
this->use_fp16_ ? paddle_infer::Config::Precision::kHalf 1 << 20, 10, 3,
: paddle_infer::Config::Precision::kFloat32, this->use_fp16_ ? paddle_infer::Config::Precision::kHalf
false, false); : paddle_infer::Config::Precision::kFloat32,
} false, false);
} else {
config.DisableGpu();
if (this->use_mkldnn_) {
config.EnableMKLDNN();
// cache 10 different shapes for mkldnn to avoid memory leak
config.SetMkldnnCacheCapacity(10);
}
config.SetCpuMathLibraryNumThreads(this->cpu_math_library_num_threads_);
} }
} else {
config.DisableGpu();
if (this->use_mkldnn_) {
config.EnableMKLDNN();
// cache 10 different shapes for mkldnn to avoid memory leak
config.SetMkldnnCacheCapacity(10);
}
config.SetCpuMathLibraryNumThreads(this->cpu_math_library_num_threads_);
}
config.SwitchUseFeedFetchOps(false); config.SwitchUseFeedFetchOps(false);
// true for multiple input // true for multiple input
config.SwitchSpecifyInputNames(true); config.SwitchSpecifyInputNames(true);
config.SwitchIrOptim(true); config.SwitchIrOptim(true);
config.EnableMemoryOptim(); config.EnableMemoryOptim();
config.DisableGlogInfo(); config.DisableGlogInfo();
this->predictor_ = CreatePredictor(config); this->predictor_ = CreatePredictor(config);
} }
cv::Mat CRNNRecognizer::GetRotateCropImage( cv::Mat CRNNRecognizer::GetRotateCropImage(const cv::Mat &srcimage,
const cv::Mat &srcimage, std::vector<std::vector<int>> box) { std::vector<std::vector<int>> box) {
cv::Mat image; cv::Mat image;
srcimage.copyTo(image); srcimage.copyTo(image);
std::vector<std::vector<int>> points = box; std::vector<std::vector<int>> points = box;
int x_collect[4] = {box[0][0], box[1][0], box[2][0], box[3][0]};
int y_collect[4] = {box[0][1], box[1][1], box[2][1], box[3][1]};
int left = int(*std::min_element(x_collect, x_collect + 4));
int right = int(*std::max_element(x_collect, x_collect + 4));
int top = int(*std::min_element(y_collect, y_collect + 4));
int bottom = int(*std::max_element(y_collect, y_collect + 4));
cv::Mat img_crop;
image(cv::Rect(left, top, right - left, bottom - top)).copyTo(img_crop);
for (int i = 0; i < points.size(); i++) {
points[i][0] -= left;
points[i][1] -= top;
}
int img_crop_width = int(sqrt(pow(points[0][0] - points[1][0], 2) + int x_collect[4] = {box[0][0], box[1][0], box[2][0], box[3][0]};
pow(points[0][1] - points[1][1], 2))); int y_collect[4] = {box[0][1], box[1][1], box[2][1], box[3][1]};
int img_crop_height = int(sqrt(pow(points[0][0] - points[3][0], 2) + int left = int(*std::min_element(x_collect, x_collect + 4));
pow(points[0][1] - points[3][1], 2))); int right = int(*std::max_element(x_collect, x_collect + 4));
int top = int(*std::min_element(y_collect, y_collect + 4));
cv::Point2f pts_std[4]; int bottom = int(*std::max_element(y_collect, y_collect + 4));
pts_std[0] = cv::Point2f(0., 0.);
pts_std[1] = cv::Point2f(img_crop_width, 0.); cv::Mat img_crop;
pts_std[2] = cv::Point2f(img_crop_width, img_crop_height); image(cv::Rect(left, top, right - left, bottom - top)).copyTo(img_crop);
pts_std[3] = cv::Point2f(0.f, img_crop_height);
for (int i = 0; i < points.size(); i++) {
cv::Point2f pointsf[4]; points[i][0] -= left;
pointsf[0] = cv::Point2f(points[0][0], points[0][1]); points[i][1] -= top;
pointsf[1] = cv::Point2f(points[1][0], points[1][1]); }
pointsf[2] = cv::Point2f(points[2][0], points[2][1]);
pointsf[3] = cv::Point2f(points[3][0], points[3][1]); int img_crop_width = int(sqrt(pow(points[0][0] - points[1][0], 2) +
pow(points[0][1] - points[1][1], 2)));
cv::Mat M = cv::getPerspectiveTransform(pointsf, pts_std); int img_crop_height = int(sqrt(pow(points[0][0] - points[3][0], 2) +
pow(points[0][1] - points[3][1], 2)));
cv::Mat dst_img;
cv::warpPerspective(img_crop, dst_img, M, cv::Point2f pts_std[4];
cv::Size(img_crop_width, img_crop_height), pts_std[0] = cv::Point2f(0., 0.);
cv::BORDER_REPLICATE); pts_std[1] = cv::Point2f(img_crop_width, 0.);
pts_std[2] = cv::Point2f(img_crop_width, img_crop_height);
if (float(dst_img.rows) >= float(dst_img.cols) * 1.5) { pts_std[3] = cv::Point2f(0.f, img_crop_height);
cv::Mat srcCopy = cv::Mat(dst_img.rows, dst_img.cols, dst_img.depth());
cv::transpose(dst_img, srcCopy); cv::Point2f pointsf[4];
cv::flip(srcCopy, srcCopy, 0); pointsf[0] = cv::Point2f(points[0][0], points[0][1]);
return srcCopy; pointsf[1] = cv::Point2f(points[1][0], points[1][1]);
} else { pointsf[2] = cv::Point2f(points[2][0], points[2][1]);
return dst_img; pointsf[3] = cv::Point2f(points[3][0], points[3][1]);
}
cv::Mat M = cv::getPerspectiveTransform(pointsf, pts_std);
cv::Mat dst_img;
cv::warpPerspective(img_crop, dst_img, M,
cv::Size(img_crop_width, img_crop_height),
cv::BORDER_REPLICATE);
if (float(dst_img.rows) >= float(dst_img.cols) * 1.5) {
cv::Mat srcCopy = cv::Mat(dst_img.rows, dst_img.cols, dst_img.depth());
cv::transpose(dst_img, srcCopy);
cv::flip(srcCopy, srcCopy, 0);
return srcCopy;
} else {
return dst_img;
} }
}
} // namespace PaddleOCR } // namespace PaddleOCR
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