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[Hackthon_4th 177] Support PP-YOLOE-R with BM1684 (#1809)

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* first draft

* add robx iou

* add benchmark for ppyoloe_r

* remove trash code

* fix bugs

* add pybind nms rotated option

* add missing head file

* fix bug

* fix bug2

* fix shape bug

---------

Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
This commit is contained in:
thunder95
2023-04-21 10:48:05 +08:00
committed by GitHub
parent f3d44785c4
commit 51be3fea78
31 changed files with 1389 additions and 6 deletions
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55
fastdeploy/vision/detection/ppdet/postprocessor.cc
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@@ -264,6 +264,57 @@ bool PaddleDetPostprocessor::ProcessSolov2(
return true;
}
bool PaddleDetPostprocessor::ProcessPPYOLOER(
const std::vector<FDTensor>& tensors,
std::vector<DetectionResult>* results) {
if (tensors.size() != 2) {
FDERROR << "The size of tensors for PPYOLOER must be 2." << std::endl;
return false;
}
int boxes_index = 0;
int scores_index = 1;
multi_class_nms_rotated_.Compute(
static_cast<const float*>(tensors[boxes_index].Data()),
static_cast<const float*>(tensors[scores_index].Data()),
tensors[boxes_index].shape, tensors[scores_index].shape);
auto num_boxes = multi_class_nms_rotated_.out_num_rois_data;
auto box_data =
static_cast<const float*>(multi_class_nms_rotated_.out_box_data.data());
// Get boxes for each input image
results->resize(num_boxes.size());
int offset = 0;
for (size_t i = 0; i < num_boxes.size(); ++i) {
const float* ptr = box_data + offset;
(*results)[i].Reserve(num_boxes[i]);
for (size_t j = 0; j < num_boxes[i]; ++j) {
(*results)[i].label_ids.push_back(
static_cast<int32_t>(round(ptr[j * 10])));
(*results)[i].scores.push_back(ptr[j * 10 + 1]);
(*results)[i].rotated_boxes.push_back(std::array<float, 8>(
{ptr[j * 10 + 2], ptr[j * 10 + 3], ptr[j * 10 + 4], ptr[j * 10 + 5],
ptr[j * 10 + 6], ptr[j * 10 + 7], ptr[j * 10 + 8],
ptr[j * 10 + 9]}));
}
offset += (num_boxes[i] * 10);
}
// do scale
if (GetScaleFactor()[0] != 0) {
for (auto& result : *results) {
for (int i = 0; i < result.rotated_boxes.size(); i++) {
for (int j = 0; j < 8; j++) {
auto scale = i % 2 == 0 ? GetScaleFactor()[1] : GetScaleFactor()[0];
result.rotated_boxes[i][j] /= float(scale);
}
}
}
}
return true;
}
bool PaddleDetPostprocessor::Run(const std::vector<FDTensor>& tensors,
std::vector<DetectionResult>* results) {
if (arch_ == "SOLOv2") {
@@ -272,6 +323,10 @@ bool PaddleDetPostprocessor::Run(const std::vector<FDTensor>& tensors,
// The fourth output of solov2 is mask
return ProcessMask(tensors[3], results);
} else {
if (tensors[0].Shape().size() == 3 && tensors[0].Shape()[2] == 8) { // PPYOLOER
return ProcessPPYOLOER(tensors, results);
}
// Do process according to whether NMS exists.
if (with_nms_) {
if (!ProcessWithNMS(tensors, results)) {