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https://github.com/open-mmlab/mmdeploy.git
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* executor prototype * add split/when_all * fix GCC build * WIP let_value * fix let_value * WIP ensure_started * ensure_started & start_detached * fix let_value + when_all combo on MSVC 142 * fix static thread pool * generic just, then, let_value, sync_wait * minor * generic split and when_all * fully generic sender adapters * when_all: workaround for GCC7 * support legacy spdlog * fix memleak * bulk * static detector * fix bulk & first pipeline * bulk for static thread pools * fix on MSVC * WIP async batch submission * WIP collation * async batch * fix detector * fix async detector * fix * fix * debug * fix cuda allocator * WIP type erased executor * better type erasure * simplify C API impl * Expand & type erase TC * deduction guide for type erased senders * fix GCC build * when_all for arrays of Value senders * WIP pipeline v2 * WIP pipeline parser * WIP timed batch operation * add registry * experiment * fix pipeline * naming * fix mem-leak * fix deferred batch operation * WIP * WIP configurable scheduler * WIP configurable scheduler * add comment * parse scheduler config * force link schedulers * WIP pipeable sender * WIP CPO * ADL isolation and dismantle headers * type erase single thread context * fix MSVC build * CPO * replace decay_t with remove_cvref_t * structure adjustment * structure adjustment * apply CPOs & C API rework * refine C API * detector async C API * adjust detector async C API * # Conflicts: # csrc/apis/c/detector.cpp * fix when_all for type erased senders * support void return for Then * async detector * fix some CPOs * minor * WIP rework capture mechanism for type erased types * minor fix * fix MSVC build * move expand.h to execution * make `Expand` pipeable * fix type erased * un-templatize `_TypeErasedOperation` * re-work C API * remove async_detector C API * fix pipeline * add flatten & unflatten * fix flatten & unflatten * add aync OCR demo * config executor for nodes & better executor API * working async OCR example * minor * dynamic batch via scheduler * dynamic batch on `Value` * fix MSVC build * type erase dynamic batch scheduler * sender as Python Awaitable * naming * naming * add docs * minor * merge tmp branch * unify C APIs * fix ocr * unify APIs * fix typo * update async OCR demo * add v3 API text recognizer * fix v3 API * fix lint * add license info & reformat * add demo async_ocr_v2 * revert files * revert files * resolve link issues * fix scheduler linkage for shared libs * fix license header * add docs for `mmdeploy_executor_split` * add missing `mmdeploy_executor_transfer_just` and `mmdeploy_executor_execute` * make `TimedSingleThreadContext` header only * fix lint * simplify type-erased sender
150 lines
4.6 KiB
C++
150 lines
4.6 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#include "restorer.h"
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#include "apis/c/common_internal.h"
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#include "apis/c/executor_internal.h"
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#include "apis/c/handle.h"
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#include "apis/c/pipeline.h"
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#include "codebase/mmedit/mmedit.h"
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#include "core/device.h"
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#include "core/graph.h"
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#include "core/utils/formatter.h"
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using namespace mmdeploy;
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namespace {
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const Value& config_template() {
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// clang-format off
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static Value v {
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{
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"pipeline", {
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{
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"tasks", {
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{
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{"name", "det"},
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{"type", "Inference"},
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{"params", {{"model", "TBD"}}},
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{"input", {"img"}},
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{"output", {"out"}}
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}
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}
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},
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{"input", {"img"}},
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{"output", {"out"}}
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}
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}
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};
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// clang-format on
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return v;
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}
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int mmdeploy_restorer_create_impl(mm_model_t model, const char* device_name, int device_id,
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mmdeploy_exec_info_t exec_info, mm_handle_t* handle) {
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auto config = config_template();
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config["pipeline"]["tasks"][0]["params"]["model"] = *static_cast<Model*>(model);
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return mmdeploy_pipeline_create(Cast(&config), device_name, device_id, exec_info, handle);
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}
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} // namespace
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int mmdeploy_restorer_create(mm_model_t model, const char* device_name, int device_id,
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mm_handle_t* handle) {
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return mmdeploy_restorer_create_impl(model, device_name, device_id, nullptr, handle);
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}
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int mmdeploy_restorer_create_by_path(const char* model_path, const char* device_name, int device_id,
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mm_handle_t* handle) {
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mm_model_t model{};
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if (auto ec = mmdeploy_model_create_by_path(model_path, &model)) {
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return ec;
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}
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auto ec = mmdeploy_restorer_create_impl(model, device_name, device_id, nullptr, handle);
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mmdeploy_model_destroy(model);
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return ec;
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}
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int mmdeploy_restorer_apply(mm_handle_t handle, const mm_mat_t* images, int count,
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mm_mat_t** results) {
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wrapped<mmdeploy_value_t> input;
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if (auto ec = mmdeploy_restorer_create_input(images, count, input.ptr())) {
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return ec;
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}
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wrapped<mmdeploy_value_t> output;
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if (auto ec = mmdeploy_restorer_apply_v2(handle, input, output.ptr())) {
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return ec;
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}
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if (auto ec = mmdeploy_restorer_get_result(output, results)) {
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return ec;
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}
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return MM_SUCCESS;
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}
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void mmdeploy_restorer_release_result(mm_mat_t* results, int count) {
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for (int i = 0; i < count; ++i) {
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delete[] results[i].data;
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}
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delete[] results;
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}
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void mmdeploy_restorer_destroy(mm_handle_t handle) { delete static_cast<AsyncHandle*>(handle); }
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int mmdeploy_restorer_create_v2(mm_model_t model, const char* device_name, int device_id,
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mmdeploy_exec_info_t exec_info, mm_handle_t* handle) {
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return mmdeploy_restorer_create_impl(model, device_name, device_id, exec_info, handle);
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}
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int mmdeploy_restorer_create_input(const mm_mat_t* mats, int mat_count, mmdeploy_value_t* value) {
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return mmdeploy_common_create_input(mats, mat_count, value);
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}
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int mmdeploy_restorer_apply_v2(mm_handle_t handle, mmdeploy_value_t input,
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mmdeploy_value_t* output) {
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return mmdeploy_pipeline_apply(handle, input, output);
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}
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int mmdeploy_restorer_apply_async(mm_handle_t handle, mmdeploy_sender_t input,
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mmdeploy_sender_t* output) {
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return mmdeploy_pipeline_apply_async(handle, input, output);
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}
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int mmdeploy_restorer_get_result(mmdeploy_value_t output, mm_mat_t** results) {
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if (!output || !results) {
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return MM_E_INVALID_ARG;
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}
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try {
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const Value& value = Cast(output)->front();
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auto restorer_output = from_value<std::vector<mmedit::RestorerOutput>>(value);
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auto count = restorer_output.size();
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auto deleter = [&](mm_mat_t* p) {
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mmdeploy_restorer_release_result(p, static_cast<int>(count));
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};
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std::unique_ptr<mm_mat_t[], decltype(deleter)> _results(new mm_mat_t[count]{}, deleter);
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for (int i = 0; i < count; ++i) {
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auto upscale = restorer_output[i];
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auto& res = _results[i];
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res.data = new uint8_t[upscale.byte_size()];
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memcpy(res.data, upscale.data<uint8_t>(), upscale.byte_size());
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res.format = (mm_pixel_format_t)upscale.pixel_format();
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res.height = upscale.height();
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res.width = upscale.width();
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res.channel = upscale.channel();
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res.type = (mm_data_type_t)upscale.type();
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}
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*results = _results.release();
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return MM_SUCCESS;
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} catch (const std::exception& e) {
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MMDEPLOY_ERROR("unhandled exception: {}", e.what());
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} catch (...) {
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MMDEPLOY_ERROR("unknown exception caught");
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}
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return MM_E_FAIL;
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}
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