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@@ -63,8 +63,6 @@ void DepthModelImpl::preprocess(const tensor::Image &image, affine::LetterBoxMat
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void DepthModelImpl::postprocess(int width, int height, void *stream)
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void DepthModelImpl::postprocess(int width, int height, void *stream)
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{
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{
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adjust_memory(width, height);
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adjust_memory(width, height);
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-
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- size_t size_matrix = sizeof(affine.d2i);
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cudaStream_t stream_ = (cudaStream_t)stream;
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cudaStream_t stream_ = (cudaStream_t)stream;
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float *affine_matrix_device = affine_matrix_.gpu();
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float *affine_matrix_device = affine_matrix_.gpu();
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@@ -78,6 +76,10 @@ void DepthModelImpl::postprocess(int width, int height, void *stream)
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stream_);
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stream_);
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}
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}
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+Result DepthModelImpl::forward(const tensor::Image &image, int slice_width, int slice_height, float overlap_width_ratio, float overlap_height_ratio, void *stream)
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+{
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+ return cv::Mat();
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+}
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Result DepthModelImpl::forward(const tensor::Image &image, void *stream)
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Result DepthModelImpl::forward(const tensor::Image &image, void *stream)
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{
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{
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@@ -118,7 +120,7 @@ Result DepthModelImpl::forward(const tensor::Image &image, void *stream)
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#ifdef TRT10
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#ifdef TRT10
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if (!trt_->forward(std::unordered_map<std::string, const void *>{
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if (!trt_->forward(std::unordered_map<std::string, const void *>{
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{ "input", input_buffer_.gpu() },
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{ "input", input_buffer_.gpu() },
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- { "output", bbox_predict_.gpu() }
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+ { "output", depth_map_buffer_.gpu() }
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}, stream_))
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}, stream_))
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{
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{
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printf("Failed to tensorRT forward.");
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printf("Failed to tensorRT forward.");
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