score-back/openwiki/architecture.md
Artur Mukhamadiev 162c210a7d feat(cloud_point): stereo rectification, point cloud pipeline, and CloudPointClient facade
- StereoRectifier wrapping cv::stereoRectify + cv::initUndistortRectifyMap (CV_16SC2 maps)
- PointCloudBuilder with cv::reprojectImageTo3D and depth/NaN filtering
- CloudPointClient high-level facade: connect(), compute_cloud() -> std::expected<PointCloud, Error>
- write_ply() ASCII PLY export helper
- CLI options 4 (compute-cloud) and 5 (compute-cloud + save PLY)
- Fix TcpServer to loop over multiple requests per connection
- Expose num_disparities parameter through CloudPointClient and StereoMatcherFactory
- Unity C# integration design spec
- Sync README, AGENTS, openwiki with stereo pipeline (C++23)
- E2E synthetic-scene test with constant-disparity stereo pair

TG-9 #ready-for-test
TG-4 #ready-for-test
TG-2 #in-progress
2026-07-12 22:28:21 +03:00

10 KiB

Architecture

Overview

The system follows a layered architecture for JSON-RPC 2.0 communication over TCP:

┌──────────────────────────────────────────────────────┐
│  Application / Unity                                  │
│  (registers callbacks via C API or server_main.cpp)   │
├──────────────────────────────────────────────────────┤
│  OpenCV Compute Layer (optional — requires opencv4)   │
│  CloudPointClient (facade: connect, compute_cloud,    │
│    write_ply)                                         │
│  StereoRectifier (cv::stereoRectify + remap, Q mat)   │
│  PointCloudBuilder (SGBM disparity, reproject, NaN    │
│    filter)                                            │
├──────────────────────────────────────────────────────┤
│  RPC Layer                                            │
│  RpcServer (method dispatch, JSON-RPC 2.0 handling)   │
│  RpcClient (typed method calls via jsonrpccxx)        │
├──────────────────────────────────────────────────────┤
│  Service Layer                                        │
│  Service (mock camera data: intrinsics, extrinsics,   │
│  stereo calibration, image pairs)                     │
├──────────────────────────────────────────────────────┤
│  Transport Layer                                      │
│  TcpServer (accept loop, per-client threads — loops)  │
│  TCPConnector (client-side connector for jsonrpccxx)  │
│  tcp_read (framed read with size prefix)              │
├──────────────────────────────────────────────────────┤
│  Serialization                                        │
│  serialize.hpp (size embedding, numeric (de)serialize)│
│  rpc_coder (Base64 encode/decode)                     │
├──────────────────────────────────────────────────────┤
│  Config                                               │
│  ConfigLoader (YAML → ServerConfig + TestData)        │
└──────────────────────────────────────────────────────┘

All C++ code lives in the score namespace. The rpc/ git submodule provides jsonrpcxx headers used by the client side.

Communication model

The PlantUML diagram at docs/communication_model.pu (rendered as docs/cm.png) describes the interaction flow:

  1. Unity side initializes a CloudPointServer via crpc_init(), which starts a TcpServer awaiting connections.
  2. Client side calls CloudPointClient::connect(), which opens a TCP connection and immediately fetches get-stereo-calibration once, initialising StereoRectifier with the returned intrinsics and geometry.
  3. On each compute_cloud() call, the client fetches a synchronised image pair via get-image-pair, passes the decoded images through StereoRectifier::rectify(), then PointCloudBuilder::build() (SGBM disparity at 1/16 scale → cv::reprojectImageTo3D → NaN filter), and returns std::expected<PointCloud, Error> to the caller.
  4. The server reads each request, dispatches it to RpcServer, which calls the registered handler (a C callback from Unity).
  5. The Unity integration uses a main-thread dispatcher: RPC callbacks arrive on a C++ per-client thread and enqueue a TaskCompletionSource onto a ConcurrentQueue; the Unity Update() loop drains the queue and completes the task. A bounded timeout (~5000 ms) prevents deadlocks when the editor is paused.
  6. The handler result is serialized back as a JSON-RPC response and sent over TCP; the per-client handler thread loops back to await the next request on the same connection.

See docs/unity-integration.md for the full Unity C# design spec.

Wire framing

Every TCP message (both directions) uses a simple length-prefixed framing protocol:

  • Header: 8 bytes — a uint64_t in native byte order containing the payload size.
  • Payload: exactly payload_size bytes of JSON-RPC text.

This is implemented in:

  • inplace_size_embedding() (include/cloud_point_rpc/serialize.hpp): Prepends the serialized uint64_t size to a std::string. Used by TcpServer::handle_client and TCPConnector::Send.
  • tcp_read() (include/cloud_point_rpc/tcp_read.hpp): Reads the 8-byte header, deserializes the size, then reads the full payload — continuing to read if the payload arrives in multiple TCP segments.
// Sending: embed size before the JSON payload
std::string response = processor_(payload);
response += "\n";
inplace_size_embedding(response);
asio::write(*socket, asio::buffer(response));

// Receiving: read 8-byte header, then full payload
std::array<char, 8> header;
asio::read(socket, asio::buffer(header, header.size()));
uint64_t packet_size = deserialize<uint64_t>(v);
std::vector<char> payload(packet_size);
asio::read(socket, asio::buffer(payload));

TcpServer

include/cloud_point_rpc/tcp_server.hpp

  • Accepts connections on a configurable IP/port using asio.
  • Runs an accept thread (std::jthread) that blocks on acceptor_.accept().
  • Each client connection is handled in its own std::jthread; finished threads are cleaned up via a std::list<pair<jthread, future<bool>>> with periodic remove_if.
  • The RequestProcessor (a std::function<std::string(const std::string&)>) is called for each incoming request — typically RpcServer::process.
  • stop() unblocks the accept loop by first connecting a dummy socket to the listening endpoint (to avoid a race with close()), then closing the acceptor.
  • Thread safety: cliThrMtx_ guards the client thread list; acceptorMtx_ guards the acceptor.

Key source: include/cloud_point_rpc/tcp_server.hpp

RpcServer

include/cloud_point_rpc/rpc_server.hpp, src/rpc_server.cpp

  • Maintains a std::map<std::string, Handler> of registered methods.
  • Handler type: std::function<std::variant<nlohmann::json, std::string>(const nlohmann::json&)> — handlers can return either a JSON object or a raw string.
  • Supports two registration overloads:
    • register_method(name, Handler) — for C++ lambdas/functors.
    • register_method(name, callback_t) — for C function pointers (rpc_string* (*)(rpc_string*)). The C callback receives the JSON params as a string and returns a string that is parsed as JSON if possible, or kept as a raw string otherwise.
  • process(request_str) parses the JSON-RPC 2.0 request, validates required fields (jsonrpc, method, id), dispatches to the handler, and builds the response. Returns JSON-RPC error objects for parse errors (-32700), invalid requests (-32600), method not found (-32601), and server errors (-32000).

Known issue

Non-object JSON requests (arrays, strings, numbers, null) throw nlohmann::json::type_error instead of returning a -32600 Invalid Request error. This is documented in tests/test_rpc_edge_cases.cpp.

RpcClient

include/cloud_point_rpc/rpc_client.hpp

  • Extends jsonrpccxx::JsonRpcClient from the json-rpc-cxx submodule.
  • Wraps a TCPConnector as the transport connector.
  • Provides typed methods: get_intrinsic_params(), get_extrinsic_params(), get_cloud_point().
  • Template call<ReturnType>(name) wraps CallMethod with an auto-incrementing request ID.

TCPConnector

include/cloud_point_rpc/tcp_connector.hpp

  • Implements jsonrpccxx::IClientConnector.
  • On construction, opens a TCP connection to the server.
  • Send(request) embeds the size prefix, writes the full message, then calls tcp_read() to receive the response.

Service

include/cloud_point_rpc/service.hpp, src/service.cpp

  • Holds TestData (intrinsic params, extrinsic params, cloud point).
  • Returns configured data if available, otherwise returns identity-matrix fallbacks.
  • Used by server_main.cpp for the standalone mock server. The C API path does not use Service — Unity provides its own handlers via callbacks.

Config

include/cloud_point_rpc/config.hpp

  • ConfigLoader::load(path) parses a YAML file into a Config struct.
  • Config contains ServerConfig (ip, port) and TestData (camera parameters).
  • Falls back to 127.0.0.1:8080 if no server section is present.
  • Sample config: config.yml (server IP 127.0.0.1, port 9095).

Executables

Executable Source Description
cloud_point_rpc_server src/server_main.cpp Standalone server with mock Service data
cloud_point_rpc_cli src/main.cpp Interactive CLI client (menu-driven)
minimal_client src/minimal_client.cpp Minimal client that sends a hardcoded ping request

Shared libraries

Library Sources Description
libcloud_point_rpc rpc_coder.cpp, rpc_server.cpp, server_api.cpp, service.cpp Core RPC + server + config
libcloud_point_rpc_cli cli.cpp CLI client logic (links against core lib)
test_cloud_point test_api.cpp Test API library for method scheduling and auto-calling

Threading model

  • Server: Accept thread + per-client handler threads (all std::jthread). Each client handler loops: it reads one request, processes it, sends the response, and then loops back to read the next request on the same connection. The connection remains open until the client disconnects (EOF) or an error occurs.
  • C API server (server_api.cpp): The global RpcServer and TcpServer are guarded by server_mtx. The rpc_string garbage collector is guarded by gc_mtx.
  • Test API (test_api.cpp): A TestThread runs a std::jthread with a condition-variable-driven loop that can auto-call registered methods at a configurable interval or process queued one-shot calls.