mirror of
https://github.com/open-mmlab/mmdeploy.git
synced 2025-01-14 08:09:43 +08:00
* 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
112 lines
3.0 KiB
C++
112 lines
3.0 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#include "apis/python/common.h"
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#include "core/value.h"
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namespace mmdeploy {
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std::map<std::string, void (*)(py::module&)>& gPythonBindings() {
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static std::map<std::string, void (*)(py::module&)> v;
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return v;
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}
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mm_mat_t GetMat(const PyImage& img) {
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auto info = img.request();
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if (info.ndim != 3) {
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fprintf(stderr, "info.ndim = %d\n", (int)info.ndim);
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throw std::runtime_error("continuous uint8 HWC array expected");
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}
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auto channels = (int)info.shape[2];
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mm_mat_t mat{};
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if (channels == 1) {
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mat.format = MM_GRAYSCALE;
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} else if (channels == 3) {
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mat.format = MM_BGR;
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} else {
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throw std::runtime_error("images of 1 or 3 channels are supported");
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}
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mat.height = (int)info.shape[0];
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mat.width = (int)info.shape[1];
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mat.channel = channels;
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mat.type = MM_INT8;
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mat.data = (uint8_t*)info.ptr;
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return mat;
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}
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py::object ConvertToPyObject(const Value& value) {
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switch (value.type()) {
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case ValueType::kNull:
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return py::none();
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case ValueType::kBool:
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return py::bool_(value.get<bool>());
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case ValueType::kInt:
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return py::int_(value.get<int64_t>());
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case ValueType::kUInt:
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return py::int_(value.get<uint64_t>());
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case ValueType::kFloat:
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return py::float_(value.get<double>());
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case ValueType::kString:
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return py::str(value.get<std::string>());
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case ValueType::kArray: {
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py::list list;
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for (const auto& x : value) {
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list.append(ConvertToPyObject(x));
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}
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return list;
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}
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case ValueType::kObject: {
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py::dict dict;
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for (auto it = value.begin(); it != value.end(); ++it) {
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dict[it.key().c_str()] = ConvertToPyObject(*it);
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}
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return dict;
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}
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case ValueType::kAny:
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return py::str("<any>");
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default:
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return py::str("<unknown>");
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}
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}
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Value ConvertToValue(const py::object& obj) {
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if (py::isinstance<py::none>(obj)) {
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return nullptr;
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} else if (py::isinstance<py::bool_>(obj)) {
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return obj.cast<bool>();
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} else if (py::isinstance<py::int_>(obj)) {
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return obj.cast<int>();
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} else if (py::isinstance<py::float_>(obj)) {
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return obj.cast<double>();
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} else if (py::isinstance<py::str>(obj)) {
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return obj.cast<std::string>();
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} else if (py::isinstance<py::list>(obj)) {
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py::list src(obj);
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Value::Array dst;
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dst.reserve(src.size());
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for (const auto& item : src) {
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dst.push_back(ConvertToValue(py::reinterpret_borrow<py::object>(item)));
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}
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return dst;
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} else if (py::isinstance<py::dict>(obj)) {
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py::dict src(obj);
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Value::Object dst;
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for (const auto& item : src) {
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dst.insert({item.first.cast<std::string>(),
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ConvertToValue(py::reinterpret_borrow<py::object>(item.second))});
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}
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return dst;
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} else {
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MMDEPLOY_ERROR("unsupported Python object type: {}", obj.get_type().cast<std::string>());
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return nullptr;
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}
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}
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} // namespace mmdeploy
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PYBIND11_MODULE(mmdeploy_python, m) {
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for (const auto& [_, f] : mmdeploy::gPythonBindings()) {
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f(m);
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}
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}
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