mirror of
https://github.com/open-mmlab/mmdeploy.git
synced 2025-01-14 08:09:43 +08:00
3be1779e66
* fix sdk model's pipeline.json * resize INT64 mask * refactor unit tests * fix api in model.h * remove 'customs' from meta info * fix zip model * fix clang-format issue * put tc on each backend into a SECTION * change SECTION title * add DYNAMIC_SECTION for capi unit test * change 'devices' to 'device_names' * change trt to tensorrt * remove uncessary check * add color_type 'color_ignore_orientation' which is used in ocr * 'min_width', 'max_width' and 'backend' might be null in pipeline config * fix clang-format issue * remove useless code
46 lines
1.2 KiB
C++
46 lines
1.2 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#include "test_utils.h"
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using namespace std;
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namespace mmdeploy::test {
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unique_ptr<Transform> CreateTransform(const Value& cfg, Device device, Stream stream) {
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auto op_type = cfg.value<string>("type", "");
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auto op_version = cfg.value<int>("version", 1);
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try {
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auto creator = Registry<Transform>::Get().GetCreator(op_type, op_version);
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if (creator == nullptr) {
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return nullptr;
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}
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auto _cfg = cfg;
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_cfg["context"]["device"] = device;
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_cfg["context"]["stream"] = stream;
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return creator->Create(_cfg);
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} catch (std::exception& e) {
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cout << "exception: " << e.what() << endl;
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return nullptr;
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} catch (...) {
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cout << "unexpected exception" << endl;
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return nullptr;
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}
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}
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vector<int64_t> Shape(const Value& value, const string& shape_key) {
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vector<int64_t> shape;
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for (auto& v : value[shape_key]) {
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shape.push_back(v.get<int>());
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}
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return shape;
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}
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vector<float> ImageNormCfg(const Value& value, const std::string& key) {
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vector<float> res;
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for (auto& v : value["img_norm_cfg"][key]) {
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res.push_back(v.get<float>());
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}
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return res;
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}
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} // namespace mmdeploy::test
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