lzhangzz 640aa03538
Support Windows (#106)
* minor changes

* support windows

* fix GCC build

* fix lint

* reformat

* fix Windows build

* fix GCC build

* search backend ops for onnxruntime

* fix lint

* fix lint

* code clean-up

* code clean-up

* fix clang build

* fix trt support

* fix cmake for ncnn

* fix cmake for openvino

* fix SDK Python API

* handle ops for other backends (ncnn, trt)

* handle SDK Python API library location

* robustify linkage

* fix cuda

* minor fix for openvino & ncnn

* use CMAKE_CUDA_ARCHITECTURES if set

* fix cuda preprocessor

* fix misc

* fix pplnn & pplcv, drop support for pplcv<0.6.0

* robustify cmake

* update build.md (#2)

* build dynamic modules as module library & fix demo (partially)

* fix candidate path for mmdeploy_python

* move "enable CUDA" to cmake config for demo

* refine demo cmake

* add comment

* fix ubuntu build

* revert docs/en/build.md

* fix C API

* fix lint

* Windows build doc (#3)

* check in docs related to mmdeploy build on windows

* update build guide on windows platform

* update build guide on windows platform

* make path of thirdparty libraries consistent

* make path consistency

* correct build command for custom ops

* correct build command for sdk

* update sdk build instructions

* update doc

* correct build command

* fix lint

* correct build command and fix lint

Co-authored-by: lvhan <lvhan@pjlab.org>

* trailing whitespace (#4)

* minor fix

* fix sr sdk model

* fix type deduction

* fix cudaFree after driver shutting down

* update ppl.cv installation warning (#5)

* fix device allocator threshold & fix lint

* update doc (#6)

* update ppl.cv installation warning

* missing 'git clone'

Co-authored-by: chenxin <chenxin2@sensetime.com>
Co-authored-by: zhangli <zhangli@sensetime.com>
Co-authored-by: lvhan028 <lvhan_028@163.com>
Co-authored-by: lvhan <lvhan@pjlab.org>
2022-02-24 20:08:44 +08:00

92 lines
3.1 KiB
C++

// Copyright (c) OpenMMLab. All rights reserved.
#include "crop.h"
#include "archive/json_archive.h"
using namespace std;
namespace mmdeploy {
CenterCropImpl::CenterCropImpl(const Value& args) : TransformImpl(args) {
if (!args.contains(("crop_size"))) {
throw std::invalid_argument("'crop_size' is expected");
}
if (args["crop_size"].is_number_integer()) {
int crop_size = args["crop_size"].get<int>();
arg_.crop_size[0] = arg_.crop_size[1] = crop_size;
} else if (args["crop_size"].is_array() && args["crop_size"].size() == 2) {
arg_.crop_size[0] = args["crop_size"][0].get<int>();
arg_.crop_size[1] = args["crop_size"][1].get<int>();
} else {
throw std::invalid_argument("'crop_size' should be integer or an int array of size 2");
}
}
Result<Value> CenterCropImpl::Process(const Value& input) {
MMDEPLOY_DEBUG("input: {}", to_json(input).dump(2));
auto img_fields = GetImageFields(input);
// copy input data, and update its properties
Value output = input;
for (auto& key : img_fields) {
auto tensor = input[key].get<Tensor>();
auto desc = tensor.desc();
int h = desc.shape[1];
int w = desc.shape[2];
int crop_height = arg_.crop_size[0];
int crop_width = arg_.crop_size[1];
int y1 = std::max(0, int(std::round((h - crop_height) / 2.0)));
int x1 = std::max(0, int(std::round((w - crop_width) / 2.0)));
int y2 = std::min(h, y1 + crop_height) - 1;
int x2 = std::min(w, x1 + crop_width) - 1;
OUTCOME_TRY(auto dst_tensor, CropImage(tensor, y1, x1, y2, x2));
auto& shape = dst_tensor.desc().shape;
output[key] = dst_tensor;
output["img_shape"] = {shape[0], shape[1], shape[2], shape[3]};
if (input.contains("scale_factor")) {
// image has been processed by `Resize` transform before.
// Compute cropped image's offset against the original image
assert(input["scale_factor"].is_array() && input["scale_factor"].size() >= 2);
float w_scale = input["scale_factor"][0].get<float>();
float h_scale = input["scale_factor"][1].get<float>();
output["offset"].push_back(x1 / w_scale);
output["offset"].push_back(y1 / h_scale);
} else {
output["offset"].push_back(x1);
output["offset"].push_back(y1);
}
}
MMDEPLOY_DEBUG("output: {}", to_json(output).dump(2));
return output;
}
CenterCrop::CenterCrop(const Value& args, int version) : Transform(args) {
auto impl_creator = Registry<CenterCropImpl>::Get().GetCreator(specified_platform_, version);
if (nullptr == impl_creator) {
MMDEPLOY_ERROR("'CenterCrop' is not supported on '{}' platform", specified_platform_);
throw std::domain_error("'Resize' is not supported on specified platform");
}
impl_ = impl_creator->Create(args);
}
class CenterCropCreator : public Creator<Transform> {
public:
const char* GetName(void) const override { return "CenterCrop"; }
int GetVersion(void) const override { return version_; }
ReturnType Create(const Value& args) override { return make_unique<CenterCrop>(args, version_); }
private:
int version_{1};
};
REGISTER_MODULE(Transform, CenterCropCreator);
MMDEPLOY_DEFINE_REGISTRY(CenterCropImpl);
} // namespace mmdeploy