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Fix AMD and OpenVINO

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This commit is contained in:
Tuan Nghia Nguyen
2026-04-08 13:45:52 +10:00
parent a4a8caaa86
commit 69787b0ff0
15 changed files with 1209 additions and 132 deletions
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14
modules/ANSODEngine/ANSYOLOOD.cpp
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@@ -218,6 +218,12 @@ namespace ANSCENTER
std::min(6, static_cast<int>(std::thread::hardware_concurrency())));
sessionOptions.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_ALL);
// DirectML REQUIRES these two settings per ORT documentation
if (ep.type == ANSCENTER::EngineType::AMD_GPU) {
sessionOptions.DisableMemPattern();
sessionOptions.SetExecutionMode(ExecutionMode::ORT_SEQUENTIAL);
}
// ── Log available providers ─────────────────────────────────────────
std::vector<std::string> availableProviders = Ort::GetAvailableProviders();
std::cout << "Available Execution Providers:" << std::endl;
@@ -519,7 +525,7 @@ namespace ANSCENTER
{
try {
// Get raw output pointer (NO COPY!)
const float* rawOutput = outputTensors[0].GetTensorData<float>();
const float* rawOutput = outputTensors[0].GetTensorMutableData<float>();
std::vector<int64_t> outputShape = outputTensors[0].GetTensorTypeAndShapeInfo().GetShape();
const int numClasses = static_cast<int>(outputShape[2]) - 5;
@@ -647,11 +653,11 @@ namespace ANSCENTER
}
return result;
}
std::vector<Object> YOLOOD::postprocessv11(const cv::Size& originalImageSize,const cv::Size& resizedImageShape,const std::vector<Ort::Value>& outputTensors,float confThreshold,float iouThreshold)
std::vector<Object> YOLOOD::postprocessv11(const cv::Size& originalImageSize,const cv::Size& resizedImageShape,std::vector<Ort::Value>& outputTensors,float confThreshold,float iouThreshold)
{
try {
// Get raw output
const float* rawOutput = outputTensors[0].GetTensorData<float>();
const float* rawOutput = outputTensors[0].GetTensorMutableData<float>();
const std::vector<int64_t> outputShape = outputTensors[0].GetTensorTypeAndShapeInfo().GetShape();
const size_t numFeatures = outputShape[1];
@@ -1448,7 +1454,7 @@ namespace ANSCENTER
);
// Parse output
const float* rawOutput = outputTensors[0].GetTensorData<float>();
const float* rawOutput = outputTensors[0].GetTensorMutableData<float>();
const std::vector<int64_t> outputShape = outputTensors[0].GetTensorTypeAndShapeInfo().GetShape();
const int dimensions = static_cast<int>(outputShape[1]); // 4 + num_classes