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[CVCUDA] PP-OCR Cls & Rec preprocessor support CV-CUDA (#1470)

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* ppocr cls preprocessor use manager

* hwc2chw cvcuda

* ppocr rec preproc use manager

* ocr rec preproc cvcuda

* fix rec preproc bug

* ppocr cls&rec preproc set normalize

* fix pybind

* address comment
This commit is contained in:
Wang Xinyu
2023-03-02 10:50:44 +08:00
committed by GitHub
parent fe2882a1ef
commit 044ab993d2
19 changed files with 424 additions and 306 deletions
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40
fastdeploy/vision/common/processors/mat_batch.cc
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@@ -29,10 +29,12 @@ FDTensor* FDMatBatch::Tensor() {
if (has_batched_tensor) {
return fd_tensor.get();
}
FDASSERT(CheckShapeConsistency(mats), "Mats shapes are not consistent.")
FDASSERT(mats != nullptr, "Failed to get batched tensor, Mats are empty.");
FDASSERT(CheckShapeConsistency(mats), "Mats shapes are not consistent.");
// Each mat has its own tensor,
// to get a batched tensor, we need copy these tensors to a batched tensor
FDTensor* src = (*mats)[0].Tensor();
device = src->device;
auto new_shape = src->Shape();
new_shape.insert(new_shape.begin(), mats->size());
input_cache->Resize(new_shape, src->Dtype(), "batch_input_cache", device);
@@ -51,26 +53,34 @@ FDTensor* FDMatBatch::Tensor() {
void FDMatBatch::SetTensor(FDTensor* tensor) {
fd_tensor->SetExternalData(tensor->Shape(), tensor->Dtype(), tensor->Data(),
tensor->device, tensor->device_id);
device = tensor->device;
has_batched_tensor = true;
}
FDTensor* CreateCachedGpuInputTensor(FDMatBatch* mat_batch) {
#ifdef WITH_GPU
auto mats = mat_batch->mats;
FDASSERT(CheckShapeConsistency(mats), "Mats shapes are not consistent.")
FDTensor* src = (*mats)[0].Tensor();
if (mat_batch->device == Device::GPU) {
return mat_batch->Tensor();
} else if (mat_batch->device == Device::CPU) {
// Mats on CPU, we need copy them to GPU and then get a batched GPU tensor
for (size_t i = 0; i < mats->size(); ++i) {
FDTensor* tensor = CreateCachedGpuInputTensor(&(*mats)[i]);
(*mats)[i].SetTensor(tensor);
}
mat_batch->device = Device::GPU;
return mat_batch->Tensor();
// Get the batched tensor
FDTensor* src = mat_batch->Tensor();
// Need to make sure the returned tensor is pointed to the input_cache.
if (src->Data() == mat_batch->output_cache->Data()) {
std::swap(mat_batch->input_cache, mat_batch->output_cache);
std::swap(mat_batch->input_cache->name, mat_batch->output_cache->name);
}
if (src->device == Device::GPU) {
return src;
} else if (src->device == Device::CPU) {
// Batched tensor on CPU, we need copy it to GPU
mat_batch->output_cache->Resize(src->Shape(), src->Dtype(), "output_cache",
Device::GPU);
FDASSERT(cudaMemcpyAsync(mat_batch->output_cache->Data(), src->Data(),
src->Nbytes(), cudaMemcpyHostToDevice,
mat_batch->Stream()) == 0,
"[ERROR] Error occurs while copy memory from CPU to GPU.");
std::swap(mat_batch->input_cache, mat_batch->output_cache);
std::swap(mat_batch->input_cache->name, mat_batch->output_cache->name);
return mat_batch->input_cache;
} else {
FDASSERT(false, "FDMat is on unsupported device: %d", src->device);
FDASSERT(false, "FDMatBatch is on unsupported device: %d", src->device);
}
#else
FDASSERT(false, "FastDeploy didn't compile with WITH_GPU.");