lvhan028 36124f6205
Merge sdk (#251)
* check in cmake

* move backend_ops to csrc/backend_ops

* check in preprocess, model, some codebase and their c-apis

* check in CMakeLists.txt

* check in parts of test_csrc

* commit everything else

* add readme

* update core's BUILD_INTERFACE directory

* skip codespell on third_party

* update trt_net and ort_net's CMakeLists

* ignore clion's build directory

* check in pybind11

* add onnx.proto. Remove MMDeploy's dependency on ncnn's source code

* export MMDeployTargets only when MMDEPLOY_BUILD_SDK is ON

* remove useless message

* target include directory is wrong

* change target name from mmdeploy_ppl_net to mmdeploy_pplnn_net

* skip install directory

* update project's cmake

* remove useless code

* set CMAKE_BUILD_TYPE to Release by force if it isn't set by user

* update custom ops CMakeLists

* pass object target's source lists

* fix lint end-of-file

* fix lint: trailing whitespace

* fix codespell hook

* remove bicubic_interpolate to csrc/backend_ops/

* set MMDEPLOY_BUILD_SDK OFF

* change custom ops build command

* add spdlog installation command

* update docs on how to checkout pybind11

* move bicubic_interpolate to backend_ops/tensorrt directory

* remove useless code

* correct cmake

* fix typo

* fix typo

* fix install directory

* correct sdk's readme

* set cub dir when cuda version < 11.0

* change directory where clang-format will apply to

* fix build command

* add .clang-format

* change clang-format style from google to file

* reformat csrc/backend_ops

* format sdk's code

* turn off clang-format for some files

* add -Xcompiler=-fno-gnu-unique

* fix trt topk initialize

* check in config for sdk demo

* update cmake script and csrc's readme

* correct config's path

* add cuda include directory, otherwise compile failed in case of tensorrt8.2

* clang-format onnx2ncnn.cpp

Co-authored-by: zhangli <lzhang329@gmail.com>
Co-authored-by: grimoire <yaoqian@sensetime.com>
2021-12-07 10:57:55 +08:00

104 lines
3.0 KiB
C++

// Copyright (c) OpenMMLab. All rights reserved.
#include "catch.hpp"
#include "core/tensor.h"
#include "preprocess/transform/transform.h"
using namespace mmdeploy;
using namespace std;
TEST_CASE("test collect constructor", "[collect]") {
std::string transform_type{"Collect"};
auto creator = Registry<Transform>::Get().GetCreator(transform_type, 1);
REQUIRE(creator != nullptr);
SECTION("empty args") {
try {
auto module = creator->Create({});
} catch (std::exception& e) {
REQUIRE(true);
INFO("expected exception: {}", e.what());
}
}
SECTION("args with 'keys' which is not an array") {
try {
auto module = creator->Create({{"keys", "img"}});
} catch (std::exception& e) {
REQUIRE(true);
INFO("expected exception: {}", e.what());
}
}
SECTION("args with keys in array") {
auto module = creator->Create({{"keys", {"img"}}});
REQUIRE(module != nullptr);
}
SECTION("args with meta_keys that is not an array") {
try {
auto module = creator->Create({{"keys", {"img"}}, {"meta_keys", "ori_img"}});
} catch (std::exception& e) {
REQUIRE(true);
INFO("expected exception: {}", e.what());
}
}
SECTION("args with meta_keys in array") {
auto module = creator->Create({{"keys", {"img"}}, {"meta_keys", {"ori_img"}}});
REQUIRE(module != nullptr);
}
}
TEST_CASE("test collect", "[collect]") {
std::string transform_type{"Collect"};
vector<std::string> keys{"img"};
vector<std::string> meta_keys{"filename", "ori_filename", "ori_shape", "img_shape",
"flip", "flip_direction", "img_norm_cfg"};
Value args;
for (auto& key : keys) {
args["keys"].push_back(key);
}
for (auto& meta_key : meta_keys) {
args["meta_keys"].push_back(meta_key);
}
auto creator = Registry<Transform>::Get().GetCreator(transform_type, 1);
REQUIRE(creator != nullptr);
auto module = creator->Create(args);
REQUIRE(module != nullptr);
Value input;
SECTION("input is empty") {
auto ret = module->Process(input);
REQUIRE(ret.has_error());
REQUIRE(ret.error() == eInvalidArgument);
}
SECTION("input has 'ori_img' and 'attribute'") {
input["ori_img"] = Tensor{};
input["attribute"] = "this is a faked image";
auto ret = module->Process(input);
REQUIRE(ret.has_error());
REQUIRE(ret.error() == eInvalidArgument);
}
SECTION("array input with correct keys and meta keys") {
Tensor tensor;
Value input{{"img", tensor},
{"filename", "test.jpg"},
{"ori_filename", "../tests/preprocess/data/test.jpg"},
{"ori_shape", {1000, 1000, 3}},
{"img_shape", {1, 3, 224, 224}},
{"flip", "false"},
{"flip_direction", "horizontal"},
{"img_norm_cfg",
{{"mean", {123.675, 116.28, 103.53}},
{"std", {58.395, 57.12, 57.375}},
{"to_rgb", true}}}};
auto ret = module->Process(input);
REQUIRE(ret.has_value());
}
}