From 7ba2b4ee5c48539543cb8e53925d1921f0fa8447 Mon Sep 17 00:00:00 2001 From: Jan Gutsche Date: Mon, 21 Apr 2025 17:46:21 +0200 Subject: [PATCH 1/8] Start analyze raw data --- ddlitlab2024/dataset/analyze_raw_data.ipynb | 68 +++++++++++++++++++++ 1 file changed, 68 insertions(+) create mode 100644 ddlitlab2024/dataset/analyze_raw_data.ipynb diff --git a/ddlitlab2024/dataset/analyze_raw_data.ipynb b/ddlitlab2024/dataset/analyze_raw_data.ipynb new file mode 100644 index 0000000..e0ae8f7 --- /dev/null +++ b/ddlitlab2024/dataset/analyze_raw_data.ipynb @@ -0,0 +1,68 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Analyze raw data\n", + "This notebook is used to analyze the ROS 2 Bags that were used to create the given database." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import sqlite3\n", + "\n", + "import pandas as pd\n", + "\n", + "from ddlitlab2024 import DB_PATH" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "con = sqlite3.connect(DB_PATH)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Get mcaps used by the database\n", + "query = \"\"\"\n", + "SELECT original_file FROM Recording;\n", + "\"\"\"\n", + "df = pd.read_sql_query(query, con)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.1" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From b58b1359e1b4755508a7bb437bb795a7c5e6aca5 Mon Sep 17 00:00:00 2001 From: Jan Gutsche Date: Mon, 21 Apr 2025 20:49:46 +0200 Subject: [PATCH 2/8] Add dev dependency ipykernel --- poetry.lock | 700 ++++++++++++++++++++++++++++++++++++++----------- pyproject.toml | 1 + 2 files changed, 552 insertions(+), 149 deletions(-) diff --git a/poetry.lock b/poetry.lock index cf282b6..236da53 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand. 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description = "MCAP libraries for Python" optional = false python-versions = ">=3.7" -groups = ["main"] files = [ {file = "mcap-1.2.2-py3-none-any.whl", hash = "sha256:046a334912e43895075c115c23ef05ec62971748abfb0f8b05d4cc9b353afdce"}, {file = "mcap-1.2.2.tar.gz", hash = "sha256:64091bb55b288142e602ff1403f7522ccd83a15dc1b05df0c648533d86e59438"}, @@ -1137,7 +1349,6 @@ version = "0.5.5" description = "ROS2 support for the Python MCAP library" optional = false python-versions = ">=3.7" -groups = ["main"] files = [ {file = "mcap_ros2_support-0.5.5-py3-none-any.whl", hash = "sha256:79141d29d6b8e3b5494178333b260ef27ddcb3c61588bca388ee52993ab80443"}, {file = "mcap_ros2_support-0.5.5.tar.gz", hash = "sha256:cd0bf92fee3f5cbff1dcd129f8e890d5ea0d036e2257ceb1f0518bce68e64de4"}, @@ -1152,7 +1363,6 @@ version = "0.1.2" description = "Markdown URL utilities" optional = false python-versions = ">=3.7" -groups = ["main"] files = [ {file = "mdurl-0.1.2-py3-none-any.whl", hash = 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checked with the mypy type checker." optional = false python-versions = ">=3.5" -groups = ["main"] files = [ {file = "mypy_extensions-1.0.0-py3-none-any.whl", hash = "sha256:4392f6c0eb8a5668a69e23d168ffa70f0be9ccfd32b5cc2d26a34ae5b844552d"}, {file = "mypy_extensions-1.0.0.tar.gz", hash = "sha256:75dbf8955dc00442a438fc4d0666508a9a97b6bd41aa2f0ffe9d2f2725af0782"}, ] +[[package]] +name = "nest-asyncio" +version = "1.6.0" +description = "Patch asyncio to allow nested event loops" +optional = false +python-versions = ">=3.5" +files = [ + {file = "nest_asyncio-1.6.0-py3-none-any.whl", hash = "sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c"}, + {file = "nest_asyncio-1.6.0.tar.gz", hash = "sha256:6f172d5449aca15afd6c646851f4e31e02c598d553a667e38cafa997cfec55fe"}, +] + [[package]] name = "networkx" version = "3.4.2" description = "Python package for creating and manipulating graphs and networks" optional = false python-versions = ">=3.10" -groups = ["main"] files = [ 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-groups = ["main"] -markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\"" files = [ {file = "nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:0eedf14185e04b76aa05b1fea04133e59f465b6f960c0cbf4e37c3cb6b0ea198"}, {file = "nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:a178759ebb095827bd30ef56598ec182b85547f1508941a3d560eb7ea1fbf338"}, @@ -1302,8 +1513,6 @@ version = "12.4.127" description = "CUDA Runtime native Libraries" optional = false python-versions = ">=3" -groups = ["main"] -markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\"" files = [ {file = "nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:961fe0e2e716a2a1d967aab7caee97512f71767f852f67432d572e36cb3a11f3"}, {file = "nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:64403288fa2136ee8e467cdc9c9427e0434110899d07c779f25b5c068934faa5"}, @@ -1316,8 +1525,6 @@ version = "9.1.0.70" description = "cuDNN runtime libraries" optional = false python-versions = ">=3" -groups = ["main"] -markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\"" files = [ {file = "nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl", hash = "sha256:165764f44ef8c61fcdfdfdbe769d687e06374059fbb388b6c89ecb0e28793a6f"}, {file = "nvidia_cudnn_cu12-9.1.0.70-py3-none-win_amd64.whl", hash = "sha256:6278562929433d68365a07a4a1546c237ba2849852c0d4b2262a486e805b977a"}, @@ -1332,8 +1539,6 @@ version = "11.2.1.3" description = "CUFFT native runtime libraries" optional = false python-versions = ">=3" -groups = ["main"] -markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\"" files = [ {file = "nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_aarch64.whl", hash = "sha256:5dad8008fc7f92f5ddfa2101430917ce2ffacd86824914c82e28990ad7f00399"}, {file = "nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl", hash = "sha256:f083fc24912aa410be21fa16d157fed2055dab1cc4b6934a0e03cba69eb242b9"}, @@ -1349,8 +1554,6 @@ version = "10.3.5.147" description = "CURAND native runtime libraries" optional = false python-versions = ">=3" -groups = ["main"] -markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\"" files = [ {file = "nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_aarch64.whl", hash = "sha256:1f173f09e3e3c76ab084aba0de819c49e56614feae5c12f69883f4ae9bb5fad9"}, {file = "nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl", hash = "sha256:a88f583d4e0bb643c49743469964103aa59f7f708d862c3ddb0fc07f851e3b8b"}, @@ -1363,8 +1566,6 @@ version = "11.6.1.9" description = "CUDA solver native runtime libraries" optional = false python-versions = ">=3" -groups = ["main"] -markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\"" files = [ {file = "nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_aarch64.whl", hash = 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\"x86_64\"" files = [ {file = "nvidia_cusparselt_cu12-0.6.2-py3-none-manylinux2014_aarch64.whl", hash = "sha256:067a7f6d03ea0d4841c85f0c6f1991c5dda98211f6302cb83a4ab234ee95bef8"}, {file = "nvidia_cusparselt_cu12-0.6.2-py3-none-manylinux2014_x86_64.whl", hash = "sha256:df2c24502fd76ebafe7457dbc4716b2fec071aabaed4fb7691a201cde03704d9"}, @@ -1413,8 +1610,6 @@ version = "2.21.5" description = "NVIDIA Collective Communication Library (NCCL) Runtime" optional = false python-versions = ">=3" -groups = ["main"] -markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\"" files = [ {file = "nvidia_nccl_cu12-2.21.5-py3-none-manylinux2014_x86_64.whl", hash = "sha256:8579076d30a8c24988834445f8d633c697d42397e92ffc3f63fa26766d25e0a0"}, ] @@ -1425,8 +1620,6 @@ version = "12.4.127" description = "Nvidia JIT LTO Library" optional = false python-versions = ">=3" -groups = ["main"] -markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\"" files = [ {file = 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-groups = ["main"] files = [ {file = "opencv-python-4.11.0.86.tar.gz", hash = "sha256:03d60ccae62304860d232272e4a4fda93c39d595780cb40b161b310244b736a4"}, {file = "opencv_python-4.11.0.86-cp37-abi3-macosx_13_0_arm64.whl", hash = "sha256:432f67c223f1dc2824f5e73cdfcd9db0efc8710647d4e813012195dc9122a52a"}, @@ -1466,10 +1656,10 @@ files = [ [package.dependencies] numpy = [ - {version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\""}, - {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\""}, - {version = ">=1.23.5", markers = "python_version >= \"3.11\""}, {version = ">=1.26.0", markers = "python_version >= \"3.12\""}, + {version = ">=1.23.5", markers = "python_version >= \"3.11\" and python_version < \"3.12\""}, + {version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\" and python_version < \"3.11\""}, + {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\" and python_version < \"3.11\""}, ] [[package]] @@ -1478,7 +1668,6 @@ version = "24.2" description = "Core utilities for Python packages" optional = false python-versions = ">=3.8" -groups = ["main", "test"] files = [ {file = "packaging-24.2-py3-none-any.whl", hash = "sha256:09abb1bccd265c01f4a3aa3f7a7db064b36514d2cba19a2f694fe6150451a759"}, {file = "packaging-24.2.tar.gz", hash = "sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f"}, @@ -1490,7 +1679,6 @@ version = "2.2.3" description = "Powerful data structures for data analysis, time series, and statistics" optional = false python-versions = ">=3.9" -groups = ["main"] files = [ {file = "pandas-2.2.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:1948ddde24197a0f7add2bdc4ca83bf2b1ef84a1bc8ccffd95eda17fd836ecb5"}, {file = "pandas-2.2.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:381175499d3802cde0eabbaf6324cce0c4f5d52ca6f8c377c29ad442f50f6348"}, @@ -1538,9 +1726,9 @@ files = [ [package.dependencies] numpy = [ - {version = ">=1.22.4", markers = "python_version < \"3.11\""}, - {version = ">=1.23.2", markers = "python_version == \"3.11\""}, {version = ">=1.26.0", markers = "python_version >= \"3.12\""}, + {version = ">=1.23.2", markers = "python_version == \"3.11\""}, + {version = ">=1.22.4", markers = "python_version < \"3.11\""}, ] python-dateutil = ">=2.8.2" pytz = ">=2020.1" @@ -1571,13 +1759,41 @@ sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-d test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"] xml = ["lxml (>=4.9.2)"] +[[package]] +name = "parso" +version = "0.8.4" +description = "A Python Parser" +optional = false +python-versions = ">=3.6" +files = [ + {file = "parso-0.8.4-py2.py3-none-any.whl", hash = "sha256:a418670a20291dacd2dddc80c377c5c3791378ee1e8d12bffc35420643d43f18"}, + {file = "parso-0.8.4.tar.gz", hash = "sha256:eb3a7b58240fb99099a345571deecc0f9540ea5f4dd2fe14c2a99d6b281ab92d"}, +] 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"sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9"}, @@ -2969,14 +3364,13 @@ version = "2.4.0" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false python-versions = ">=3.9" -groups = ["main"] files = [ {file = "urllib3-2.4.0-py3-none-any.whl", hash = "sha256:4e16665048960a0900c702d4a66415956a584919c03361cac9f1df5c5dd7e813"}, {file = "urllib3-2.4.0.tar.gz", hash = "sha256:414bc6535b787febd7567804cc015fee39daab8ad86268f1310a9250697de466"}, ] [package.extras] -brotli = ["brotli (>=1.0.9) ; platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; platform_python_implementation != \"CPython\""] +brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"] h2 = ["h2 (>=4,<5)"] socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"] zstd = ["zstandard (>=0.18.0)"] @@ -2987,7 +3381,6 @@ version = "0.19.9" description = "A CLI and library for interacting with the Weights & Biases API." optional = false python-versions = ">=3.8" -groups = ["main"] files = [ {file = "wandb-0.19.9-py3-none-any.whl", hash = "sha256:191b2c794b401bd04cc7c48b16339ca2832510af8499348744e7461a1609b6a9"}, {file = "wandb-0.19.9-py3-none-macosx_10_14_x86_64.whl", hash = "sha256:de5702416f29d1d61f9e85f4090346f23db1ee7f23cab37a4dd5d394fcf5f7da"}, @@ -3030,24 +3423,34 @@ perf = ["orjson"] sweeps = ["sweeps (>=0.2.0)"] workspaces = ["wandb-workspaces"] +[[package]] +name = "wcwidth" +version = "0.2.13" +description = "Measures the displayed width of unicode strings in a terminal" +optional = false +python-versions = "*" +files = [ + {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"}, + {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"}, +] + [[package]] name = "zipp" version = "3.21.0" description = "Backport of pathlib-compatible object wrapper for zip files" optional = false python-versions = ">=3.9" -groups = ["main"] files = [ {file = "zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931"}, {file = "zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4"}, ] [package.extras] -check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""] +check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"] cover = ["pytest-cov"] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] enabler = ["pytest-enabler (>=2.2)"] -test = ["big-O", "importlib-resources ; python_version < \"3.9\"", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] +test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"] type = ["pytest-mypy"] [[package]] @@ -3056,7 +3459,6 @@ version = "0.23.0" description = "Zstandard bindings for Python" optional = false python-versions = ">=3.8" -groups = ["main"] files = [ {file = "zstandard-0.23.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:bf0a05b6059c0528477fba9054d09179beb63744355cab9f38059548fedd46a9"}, {file = "zstandard-0.23.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:fc9ca1c9718cb3b06634c7c8dec57d24e9438b2aa9a0f02b8bb36bf478538880"}, @@ -3164,6 +3566,6 @@ cffi = {version = ">=1.11", markers = "platform_python_implementation == \"PyPy\ cffi = ["cffi (>=1.11)"] [metadata] -lock-version = "2.1" +lock-version = "2.0" python-versions = "^3.10" -content-hash = "683fdebe52227977bb876e41aec9443743e4033ad7ef404db1e5ed2c544ad4fb" +content-hash = "4e4c26cf7c2c0d89bd3e741f04690d005220f600a129cdc6c5898865ae06054c" diff --git a/pyproject.toml b/pyproject.toml index 8accdb2..8e56276 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -36,6 +36,7 @@ torchvision = "^0.21.0" [tool.poetry.group.dev.dependencies] ruff = "^0.8.0" +ipykernel = "^6.29.5" [tool.poetry.group.test.dependencies] pytest = "^8.3.3" From a2fe30db4560b329ef3e44a0de1db1b7a1a0bc26 Mon Sep 17 00:00:00 2001 From: Jan Gutsche Date: Mon, 21 Apr 2025 20:49:55 +0200 Subject: [PATCH 3/8] Analyze database --- ddlitlab2024/dataset/analyze_db.ipynb | 426 ++++++++++++++++++++++++++ 1 file changed, 426 insertions(+) create mode 100644 ddlitlab2024/dataset/analyze_db.ipynb diff --git a/ddlitlab2024/dataset/analyze_db.ipynb b/ddlitlab2024/dataset/analyze_db.ipynb new file mode 100644 index 0000000..2930e52 --- /dev/null +++ b/ddlitlab2024/dataset/analyze_db.ipynb @@ -0,0 +1,426 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Analyze database\n", + "This notebook is used to analyze the database ant its recordings." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import sqlite3\n", + "from pathlib import Path\n", + "from typing import TypedDict\n", + "\n", + "from datetime import datetime\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "\n", + "from ddlitlab2024 import DB_PATH" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "DB_PATH = Path(\"/srv/ssd_nvm/dataset/ddlitlab2024/db/robocup_2024_german_open_2025.sqlite3\") # TODO Remove me" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Analyzing /srv/ssd_nvm/dataset/ddlitlab2024/db/robocup_2024_german_open_2025.sqlite3\n" + ] + } + ], + "source": [ + "print(f\"Analyzing {DB_PATH}\")\n", + "\n", + "# Connect read-only to the SQLite database\n", + "conn = sqlite3.connect(f\"file:{DB_PATH}?mode=ro\", uri=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Gather metrics:\n", + "- Duration [s]\n", + "- Image samples\n", + "- Rotation samples\n", + "- Joint state samples\n", + "- Joint command samples\n", + "- Game state samples\n", + "- Total number of (previous) samples" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "class Metric(TypedDict):\n", + " name: str\n", + " duration_s: float\n", + " num_images: int\n", + " num_rotations: int\n", + " num_joint_states: int\n", + " num_joint_commands: int\n", + " num_game_states: int\n", + " num_messages: int" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Iterate over all recordings in the database and gather metrics\n", + "def gather_metrics() -> pd.DataFrame:\n", + " # Get all recordings\n", + " recordings = conn.execute(\"SELECT _id, original_file, start_time, end_time FROM Recording\").fetchall()\n", + " metrics = []\n", + "\n", + " for recording in recordings:\n", + " recording_id = recording[0]\n", + "\n", + " duration_s = (datetime.fromisoformat(recording[3]) - datetime.fromisoformat(recording[2])).total_seconds()\n", + "\n", + " # Get the number of images\n", + " num_images = conn.execute(\n", + " \"SELECT COUNT(*) FROM Image WHERE recording_id = ?\", (recording_id,)\n", + " ).fetchone()[0]\n", + "\n", + " # Get the number of IMU messages\n", + " num_rotations = conn.execute(\n", + " \"SELECT COUNT(*) FROM Rotation WHERE recording_id = ?\", (recording_id,)\n", + " ).fetchone()[0]\n", + "\n", + " # Get the number of joint states\n", + " num_joint_states = conn.execute(\n", + " \"SELECT COUNT(*) FROM JointStates WHERE recording_id = ?\", (recording_id,)\n", + " ).fetchone()[0]\n", + "\n", + " # Get the number of joint commands\n", + " num_joint_commands = conn.execute(\n", + " \"SELECT COUNT(*) FROM JointCommands WHERE recording_id = ?\", (recording_id,)\n", + " ).fetchone()[0]\n", + "\n", + " # Get the number of game states\n", + " num_game_states = conn.execute(\n", + " \"SELECT COUNT(*) FROM GameState WHERE recording_id = ?\", (recording_id,)\n", + " ).fetchone()[0]\n", + "\n", + " # Get the number of messages\n", + " num_messages = num_images + num_rotations + num_joint_states + num_joint_commands + num_game_states\n", + " metrics.append(\n", + " Metric(\n", + " name=recording[1],\n", + " duration_s=duration_s,\n", + " num_images=num_images,\n", + " num_rotations=num_rotations,\n", + " num_joint_states=num_joint_states,\n", + " num_joint_commands=num_joint_commands,\n", + " num_game_states=num_game_states,\n", + " num_messages=num_messages,\n", + " )\n", + " )\n", + "\n", + " return pd.DataFrame(metrics)\n", + "\n", + "df = gather_metrics()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "df.to_csv(\"metrics_db.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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0ID_donna_2024-07-19T16:30:37_0.mcap689.85832067523376333763337639108050
1ID_jack_2024-07-19T11:31:28_0.mcap752.84041173453672836728367281120118649
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...........................
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" + ], + "text/plain": [ + " name duration_s num_images \\\n", + "0 ID_donna_2024-07-19T16:30:37_0.mcap 689.858320 6752 \n", + "1 ID_jack_2024-07-19T11:31:28_0.mcap 752.840411 7345 \n", + "2 ID_jack_2024-07-17T15:38:04_0.mcap 534.731386 5163 \n", + "3 ID_rory_2024-07-18T13:29:30_0.mcap 1177.131614 11588 \n", + "4 ID_donna_2024-07-19T11:48:16_0.mcap 1052.640304 10200 \n", + ".. ... ... ... \n", + "83 ID_rory_2025-03-13T14:48:56_0.mcap 220.334670 1919 \n", + "84 ID_jack_2025-03-13T14:49:56_0.mcap 768.941289 7438 \n", + "85 ID_donna_2025-03-15T10:27:37_0.mcap 1059.899044 10561 \n", + "86 ID_jack_2025-03-15T13:33:32_0.mcap 1036.381852 10144 \n", + "87 ID_donna_2025-03-14T14:40:42_0.mcap 383.138529 3801 \n", + "\n", + " num_rotations num_joint_states num_joint_commands num_game_states \\\n", + "0 33763 33763 33763 9 \n", + "1 36728 36728 36728 1120 \n", + "2 25819 25819 25819 634 \n", + "3 57941 57941 57941 2172 \n", + "4 51884 51884 51884 1453 \n", + ".. ... ... ... ... \n", + "83 9603 9603 9603 364 \n", + "84 37288 37288 37288 1456 \n", + "85 52932 52932 52932 1853 \n", + "86 50730 50730 50730 1375 \n", + "87 19009 19009 19009 668 \n", + "\n", + " num_messages \n", + "0 108050 \n", + "1 118649 \n", + "2 83254 \n", + "3 187583 \n", + "4 167305 \n", + ".. ... \n", + "83 31092 \n", + "84 120758 \n", + "85 171210 \n", + "86 163709 \n", + "87 61496 \n", + "\n", + "[88 rows x 8 columns]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "duration_s & 35.15 & 619.25±665.74 & 4598.73 & 54493.99\\\\\n", + "num_images & 200 & 5952±6638 & 45954 & 523819\\\\\n", + "num_rotations & 1014 & 30147±33378 & 229777 & 2652975\\\\\n", + "num_joint_states & 1014 & 30147±33378 & 229777 & 2652975\\\\\n", + "num_joint_commands & 1014 & 30147±33378 & 229777 & 2652975\\\\\n", + "num_game_states & 1 & 939±1001 & 6280 & 82638\\\\\n", + "num_messages & 3273 & 97334±107712 & 741565 & 8565382\\\\\n" + ] + } + ], + "source": [ + "# Print latex for each column\n", + "for column in df.columns:\n", + " if column == \"name\":\n", + " continue\n", + " if column == \"duration_s\":\n", + " print(f\"{column} & {df[column].min():.2f} & {df[column].mean():.2f}±{df[column].std():.2f} & {df[column].max():.2f} & {df[column].sum():.2f}\\\\\\\\\")\n", + " else:\n", + " print(f\"{column} & {df[column].min():.0f} & {df[column].mean():.0f}±{df[column].std():.0f} & {df[column].max():.0f} & {df[column].sum():.0f}\\\\\\\\\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "ddlitlab2024-bN9lk4bc-py3.10", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 4cffe34ecd3b5d60d8651a5aa83f87d2b3913a06 Mon Sep 17 00:00:00 2001 From: Jan Gutsche Date: Tue, 29 Apr 2025 13:02:55 +0200 Subject: [PATCH 4/8] Analyze db: Minutes --- ddlitlab2024/dataset/analyze_db.ipynb | 281 ++++++++++++++------------ 1 file changed, 152 insertions(+), 129 deletions(-) diff --git a/ddlitlab2024/dataset/analyze_db.ipynb b/ddlitlab2024/dataset/analyze_db.ipynb index 2930e52..273086e 100644 --- a/ddlitlab2024/dataset/analyze_db.ipynb +++ b/ddlitlab2024/dataset/analyze_db.ipynb @@ -158,7 +158,16 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "df[\"duration_m\"] = df[\"duration_s\"] / 60" + ] + }, + { + "cell_type": "code", + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -190,63 +199,69 @@ " num_joint_commands\n", " num_game_states\n", " num_messages\n", + " duration_m\n", " \n", " \n", " \n", " \n", - " 0\n", - " ID_donna_2024-07-19T16:30:37_0.mcap\n", - " 689.858320\n", - " 6752\n", - " 33763\n", - " 33763\n", - " 33763\n", - " 9\n", - " 108050\n", + " 80\n", + " ID_donna_2025-03-16T13:50:58_0.mcap\n", + " 4598.725709\n", + " 45954\n", + " 229777\n", + " 229777\n", + " 229777\n", + " 6280\n", + " 741565\n", + " 76.645428\n", " \n", " \n", - " 1\n", - " ID_jack_2024-07-19T11:31:28_0.mcap\n", - " 752.840411\n", - " 7345\n", - " 36728\n", - " 36728\n", - " 36728\n", - " 1120\n", - " 118649\n", + " 59\n", + " ID_rory_2025-03-16T14:02:56_0.mcap\n", + " 3791.524157\n", + " 37894\n", + " 189473\n", + " 189473\n", + " 189473\n", + " 5053\n", + " 611366\n", + " 63.192069\n", " \n", " \n", - " 2\n", - " ID_jack_2024-07-17T15:38:04_0.mcap\n", - " 534.731386\n", - " 5163\n", - " 25819\n", - " 25819\n", - " 25819\n", - " 634\n", - " 83254\n", + " 27\n", + " ID_rory_2024-07-19T17:45:15_0.mcap\n", + " 1903.966492\n", + " 18877\n", + " 94395\n", + " 94395\n", + " 94395\n", + " 3273\n", + " 305335\n", + " 31.732775\n", " \n", " \n", - " 3\n", - " ID_rory_2024-07-18T13:29:30_0.mcap\n", - " 1177.131614\n", - " 11588\n", - " 57941\n", - " 57941\n", - " 57941\n", - " 2172\n", - " 187583\n", + " 35\n", + " ID_donna_2024-07-20T15:26:55_0.mcap\n", + " 1328.308035\n", + " 8127\n", + " 65443\n", + " 65443\n", + " 65443\n", + " 2466\n", + " 206922\n", + " 22.138467\n", " \n", " \n", - " 4\n", - " ID_donna_2024-07-19T11:48:16_0.mcap\n", - " 1052.640304\n", - " 10200\n", - " 51884\n", - " 51884\n", - " 51884\n", - " 1453\n", - " 167305\n", + " 82\n", + " ID_rory_2025-03-13T10:53:00_0.mcap\n", + " 1290.537316\n", + " 12608\n", + " 63045\n", + " 63045\n", + " 63045\n", + " 2271\n", + " 204014\n", + " 21.508955\n", " \n", " \n", " ...\n", @@ -258,122 +273,129 @@ " ...\n", " ...\n", " ...\n", + " ...\n", " \n", " \n", - " 83\n", - " ID_rory_2025-03-13T14:48:56_0.mcap\n", - " 220.334670\n", - " 1919\n", - " 9603\n", - " 9603\n", - " 9603\n", - " 364\n", - " 31092\n", + " 10\n", + " ID_jack_2024-07-18T18:29:35_0.mcap\n", + " 54.169400\n", + " 369\n", + " 1852\n", + " 1852\n", + " 1852\n", + " 66\n", + " 5991\n", + " 0.902823\n", " \n", " \n", - " 84\n", - " ID_jack_2025-03-13T14:49:56_0.mcap\n", - " 768.941289\n", - " 7438\n", - " 37288\n", - " 37288\n", - " 37288\n", - " 1456\n", - " 120758\n", + " 57\n", + " ID_jack_2024-07-20T15:47:38_0.mcap\n", + " 47.663031\n", + " 332\n", + " 1676\n", + " 1676\n", + " 1676\n", + " 8\n", + " 5368\n", + " 0.794384\n", " \n", " \n", - " 85\n", - " ID_donna_2025-03-15T10:27:37_0.mcap\n", - " 1059.899044\n", - " 10561\n", - " 52932\n", - " 52932\n", - " 52932\n", - " 1853\n", - " 171210\n", + " 12\n", + " ID_jack_2024-07-18T18:42:01_0.mcap\n", + " 43.044205\n", + " 309\n", + " 1550\n", + " 1550\n", + " 1550\n", + " 53\n", + " 5012\n", + " 0.717403\n", " \n", " \n", - " 86\n", - " ID_jack_2025-03-15T13:33:32_0.mcap\n", - " 1036.381852\n", - " 10144\n", - " 50730\n", - " 50730\n", - " 50730\n", - " 1375\n", - " 163709\n", + " 20\n", + " ID_rory_2024-07-18T13:52:36_0.mcap\n", + " 39.836062\n", + " 237\n", + " 1191\n", + " 1191\n", + " 1191\n", + " 27\n", + " 3837\n", + " 0.663934\n", " \n", " \n", - " 87\n", - " ID_donna_2025-03-14T14:40:42_0.mcap\n", - " 383.138529\n", - " 3801\n", - " 19009\n", - " 19009\n", - " 19009\n", - " 668\n", - " 61496\n", + " 40\n", + " ID_jack_2024-07-19T18:01:33_0.mcap\n", + " 35.146186\n", + " 200\n", + " 1014\n", + " 1014\n", + " 1014\n", + " 31\n", + " 3273\n", + " 0.585770\n", " \n", " \n", "\n", - "

88 rows × 8 columns

\n", + "

88 rows × 9 columns

\n", "" ], "text/plain": [ " name duration_s num_images \\\n", - "0 ID_donna_2024-07-19T16:30:37_0.mcap 689.858320 6752 \n", - "1 ID_jack_2024-07-19T11:31:28_0.mcap 752.840411 7345 \n", - "2 ID_jack_2024-07-17T15:38:04_0.mcap 534.731386 5163 \n", - "3 ID_rory_2024-07-18T13:29:30_0.mcap 1177.131614 11588 \n", - "4 ID_donna_2024-07-19T11:48:16_0.mcap 1052.640304 10200 \n", + "80 ID_donna_2025-03-16T13:50:58_0.mcap 4598.725709 45954 \n", + "59 ID_rory_2025-03-16T14:02:56_0.mcap 3791.524157 37894 \n", + "27 ID_rory_2024-07-19T17:45:15_0.mcap 1903.966492 18877 \n", + "35 ID_donna_2024-07-20T15:26:55_0.mcap 1328.308035 8127 \n", + "82 ID_rory_2025-03-13T10:53:00_0.mcap 1290.537316 12608 \n", ".. ... ... ... \n", - "83 ID_rory_2025-03-13T14:48:56_0.mcap 220.334670 1919 \n", - "84 ID_jack_2025-03-13T14:49:56_0.mcap 768.941289 7438 \n", - "85 ID_donna_2025-03-15T10:27:37_0.mcap 1059.899044 10561 \n", - "86 ID_jack_2025-03-15T13:33:32_0.mcap 1036.381852 10144 \n", - "87 ID_donna_2025-03-14T14:40:42_0.mcap 383.138529 3801 \n", + "10 ID_jack_2024-07-18T18:29:35_0.mcap 54.169400 369 \n", + "57 ID_jack_2024-07-20T15:47:38_0.mcap 47.663031 332 \n", + "12 ID_jack_2024-07-18T18:42:01_0.mcap 43.044205 309 \n", + "20 ID_rory_2024-07-18T13:52:36_0.mcap 39.836062 237 \n", + "40 ID_jack_2024-07-19T18:01:33_0.mcap 35.146186 200 \n", "\n", " num_rotations num_joint_states num_joint_commands num_game_states \\\n", - "0 33763 33763 33763 9 \n", - "1 36728 36728 36728 1120 \n", - "2 25819 25819 25819 634 \n", - "3 57941 57941 57941 2172 \n", - "4 51884 51884 51884 1453 \n", + "80 229777 229777 229777 6280 \n", + "59 189473 189473 189473 5053 \n", + "27 94395 94395 94395 3273 \n", + "35 65443 65443 65443 2466 \n", + "82 63045 63045 63045 2271 \n", ".. ... ... ... ... \n", - "83 9603 9603 9603 364 \n", - "84 37288 37288 37288 1456 \n", - "85 52932 52932 52932 1853 \n", - "86 50730 50730 50730 1375 \n", - "87 19009 19009 19009 668 \n", + "10 1852 1852 1852 66 \n", + "57 1676 1676 1676 8 \n", + "12 1550 1550 1550 53 \n", + "20 1191 1191 1191 27 \n", + "40 1014 1014 1014 31 \n", "\n", - " num_messages \n", - "0 108050 \n", - "1 118649 \n", - "2 83254 \n", - "3 187583 \n", - "4 167305 \n", - ".. ... \n", - "83 31092 \n", - "84 120758 \n", - "85 171210 \n", - "86 163709 \n", - "87 61496 \n", + " num_messages duration_m \n", + "80 741565 76.645428 \n", + "59 611366 63.192069 \n", + "27 305335 31.732775 \n", + "35 206922 22.138467 \n", + "82 204014 21.508955 \n", + ".. ... ... \n", + "10 5991 0.902823 \n", + "57 5368 0.794384 \n", + "12 5012 0.717403 \n", + "20 3837 0.663934 \n", + "40 3273 0.585770 \n", "\n", - "[88 rows x 8 columns]" + "[88 rows x 9 columns]" ] }, - "execution_count": 7, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ + "df = df.sort_values(by=\"duration_s\", ascending=False)\n", "df" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -386,7 +408,8 @@ "num_joint_states & 1014 & 30147±33378 & 229777 & 2652975\\\\\n", "num_joint_commands & 1014 & 30147±33378 & 229777 & 2652975\\\\\n", "num_game_states & 1 & 939±1001 & 6280 & 82638\\\\\n", - "num_messages & 3273 & 97334±107712 & 741565 & 8565382\\\\\n" + "num_messages & 3273 & 97334±107712 & 741565 & 8565382\\\\\n", + "duration_m & 0.59 & 10.32±11.10 & 76.65 & 908.23\\\\\n" ] } ], @@ -395,7 +418,7 @@ "for column in df.columns:\n", " if column == \"name\":\n", " continue\n", - " if column == \"duration_s\":\n", + " if column in [\"duration_s\", \"duration_m\"]:\n", " print(f\"{column} & {df[column].min():.2f} & {df[column].mean():.2f}±{df[column].std():.2f} & {df[column].max():.2f} & {df[column].sum():.2f}\\\\\\\\\")\n", " else:\n", " print(f\"{column} & {df[column].min():.0f} & {df[column].mean():.0f}±{df[column].std():.0f} & {df[column].max():.0f} & {df[column].sum():.0f}\\\\\\\\\")" From b5f26936ed051c0e049fd3fe9edb86f41208a69a Mon Sep 17 00:00:00 2001 From: Jan Gutsche Date: Tue, 29 Apr 2025 13:03:25 +0200 Subject: [PATCH 5/8] WIP: Analyze raw data --- ddlitlab2024/dataset/analyze_raw_data.ipynb | 297 +++++++++++++++++++- 1 file changed, 290 insertions(+), 7 deletions(-) diff --git a/ddlitlab2024/dataset/analyze_raw_data.ipynb b/ddlitlab2024/dataset/analyze_raw_data.ipynb index e0ae8f7..87f9992 100644 --- a/ddlitlab2024/dataset/analyze_raw_data.ipynb +++ b/ddlitlab2024/dataset/analyze_raw_data.ipynb @@ -10,29 +10,56 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import sqlite3\n", + "from concurrent.futures import ThreadPoolExecutor\n", + "from contextlib import contextmanager\n", + "from datetime import datetime, timedelta\n", + "from pathlib import Path\n", + "from typing import TypedDict\n", "\n", "import pandas as pd\n", + "from mcap.reader import make_reader\n", + "from mcap.summary import Summary\n", + "from mcap_ros2.decoder import DecoderFactory\n", "\n", "from ddlitlab2024 import DB_PATH" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ - "con = sqlite3.connect(DB_PATH)" + "BASE_DIR = Path(\"/srv/rosbags\") # Same as https://data.bit-bots.de/ROSbags/" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "DB_PATH = Path(\"/srv/ssd_nvm/dataset/ddlitlab2024/db/robocup_2024_german_open_2025.sqlite3\") # TODO Remove me" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Connect read-only to the SQLite database\n", + "conn = sqlite3.connect(f\"file:{DB_PATH}?mode=ro\", uri=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -40,13 +67,269 @@ "query = \"\"\"\n", "SELECT original_file FROM Recording;\n", "\"\"\"\n", - "df = pd.read_sql_query(query, con)" + "files = pd.DataFrame()\n", + "files[\"mcap_file_name\"] = pd.read_sql_query(query, conn)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# Find the full file paths recursively contained in the following directory\n", + "def find_file(file_name):\n", + " candidates = []\n", + " for path in BASE_DIR.rglob(file_name):\n", + " candidates.append(path)\n", + " match len(candidates):\n", + " case 0:\n", + " print(f\"File {file_name} not found\")\n", + " return None\n", + " case 1:\n", + " return candidates[0]\n", + " case 2:\n", + " # Use the \"untrimmed\" version of the file if it exists\n", + " for candidate in candidates:\n", + " if \"untrimmed\" in str(candidate):\n", + " return candidate\n", + " print(f\"File {file_name} found multiple times: {candidates}\")\n", + " return None\n", + " case _:\n", + " print(f\"File {file_name} found multiple times: {candidates}\")\n", + " return None\n", + "\n", + "\n", + "# Find the full file paths for each mcap file\n", + "files[\"mcap_file_path\"] = files[\"mcap_file_name\"].apply(find_file)\n", + "assert files[\"mcap_file_path\"].notnull().all(), \"Some mcap files were not found\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Gather metrics:\n", + "- Amount [B]\n", + "- Duration [s]\n", + "- Image messages\n", + "- IMU messages\n", + "- Joint state messages\n", + "- Joint command messages\n", + "- Game state messages\n", + "- Total number of (previous) messages" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# Preparations\n", + "\n", + "\n", + "class Metric(TypedDict):\n", + " mcap_file_name: str\n", + " mcap_file_path: Path\n", + " mcap_file_size_B: int\n", + " duration_s: float\n", + " num_images: int\n", + " num_imu: int\n", + " num_joint_states: int\n", + " num_joint_commands: int\n", + " num_game_states: int\n", + " num_messages: int\n", + "\n", + "\n", + "@contextmanager\n", + "def _mcap_reader(mcap_file_path: Path):\n", + " with open(mcap_file_path, \"rb\") as f:\n", + " yield make_reader(f, decoder_factories=[DecoderFactory()])\n", + "\n", + "\n", + "def duration(summary: Summary) -> timedelta:\n", + " first_msg_start_time = None\n", + " last_msg_end_time = None\n", + "\n", + " for chunk_index in summary.chunk_indexes:\n", + " if first_msg_start_time is None or chunk_index.message_start_time < first_msg_start_time:\n", + " first_msg_start_time = chunk_index.message_start_time\n", + " if last_msg_end_time is None or chunk_index.message_end_time > last_msg_end_time:\n", + " last_msg_end_time = chunk_index.message_end_time\n", + "\n", + " assert first_msg_start_time is not None, \"No start time found in the MCAP file\"\n", + " assert last_msg_end_time is not None, \"No end time found in the MCAP file\"\n", + "\n", + " return datetime.fromtimestamp(last_msg_end_time / 1e9) - datetime.fromtimestamp(first_msg_start_time / 1e9)\n", + "\n", + "\n", + "USED_TOPICS = [\n", + " \"/DynamixelController/command\",\n", + " \"/camera/image_proc\",\n", + " \"/camera/image_to_record\",\n", + " \"/gamestate\",\n", + " \"/imu/data\",\n", + " \"/joint_states\",\n", + " \"/tf\",\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T16:30:37/ID_donna_2024-07-19T16:30:37_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T11:31:28/ID_jack_2024-07-19T11:31:28_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-17T15:38:04/ID_jack_2024-07-17T15:38:04_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-18T13:29:30/ID_rory_2024-07-18T13:29:30_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T11:48:16/ID_donna_2024-07-19T11:48:16_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-18T13:54:46/ID_rory_2024-07-18T13:54:46_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-20T11:08:32/ID_jack_2024-07-20T11:08:32_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T09:50:25/ID_jack_2024-07-19T09:50:25_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T17:27:57/ID_jack_2024-07-19T17:27:57_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T18:29:22/ID_donna_2024-07-18T18:29:22_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T18:29:35/ID_jack_2024-07-18T18:29:35_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T18:31:02/ID_donna_2024-07-18T18:31:02_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T18:42:01/ID_jack_2024-07-18T18:42:01_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T16:17:13/ID_donna_2024-07-19T16:17:13_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T11:30:19/ID_donna_2024-07-19T11:30:19_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T17:58:04/ID_jack_2024-07-19T17:58:04_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T19:28:32/ID_donna_2024-07-18T19:28:32_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T18:47:57/ID_jack_2024-07-18T18:47:57_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-20T15:56:08/ID_jack_2024-07-20T15:56:08_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-20T15:27:30/ID_rory_2024-07-20T15:27:30_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-18T13:52:36/ID_rory_2024-07-18T13:52:36_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T18:38:45/ID_jack_2024-07-18T18:38:45_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T18:47:16/ID_donna_2024-07-18T18_47_16_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-20T15:45:49/ID_rory_2024-07-20T15:45:49_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-20T15:34:27/ID_rory_2024-07-20T15:34:27_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_amy_2024-07-18T10:26:27/ID_amy_2024-07-18T10:26:27_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T11:47:41/ID_jack_2024-07-19T11:47:41_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-19T17:45:15/ID_rory_2024-07-19T17:45:15_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T19:48:52/ID_donna_2024-07-18T19:48:52_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T17:11:35/ID_donna_2024-07-19T17:11:35_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-19T17:27:54/ID_rory_2024-07-19T17:27:54_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T11:29:50/ID_jack_2024-07-19T11:29:50_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T15:29:51/ID_donna_2024-07-18T15:29:51_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T17:05:54/ID_donna_2024-07-19T17:05:54_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-20T15:27:14/ID_jack_2024-07-20T15:27:14_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-20T15:26:55/ID_donna_2024-07-20T15:26:55_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T19:56:19/ID_jack_2024-07-18T19:56:19_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-18T10:50:54/ID_rory_2024-07-18T10:50:54_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-20T15:49:20/ID_donna_2024-07-20T15:49:20_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T17:45:13/ID_donna_2024-07-19T17:45:13_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T18:01:33/ID_jack_2024-07-19T18:01:33_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T15:21:13/ID_donna_2024-07-18T15:21:13_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-20T11:19:40/ID_jack_2024-07-20T11:19:40_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-17T18:34:41/ID_jack_2024-07-17T18:34:41_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T19:51:25/ID_jack_2024-07-18T19:51:25_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_amy_2024-07-18T10:32:52/ID_amy_2024-07-18T10:32:52_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-17T15:35:46/ID_jack_2024-07-17T15:35:46_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-20T15:48:43/ID_jack_2024-07-20T15:48:43_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T17:35:46/ID_donna_2024-07-19T17:35:46_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T18:00:20/ID_donna_2024-07-19T18:00:20_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T19:28:29/ID_jack_2024-07-18T19:28:29_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T19:46:13/ID_jack_2024-07-18T19:46:13_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T19:38:20/ID_jack_2024-07-18T19:38:20_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-17T19:16:57/ID_rory_2024-07-17T19:16:57_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T15:00:02/ID_donna_2024-07-18T15:00:02_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T18:31:03/ID_jack_2024-07-18T18:31:03_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-20T15:40:46/ID_rory_2024-07-20T15:40:46_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-20T15:47:38/ID_jack_2024-07-20T15:47:38_0.mcap\n", + "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T17:46:07/ID_jack_2024-07-19T17:46:07_0.mcap\n", + "Processing /srv/rosbags/german_open_2025/original_untrimmed/ID_rory_2025-03-16T14:02:56/ID_rory_2025-03-16T14:02:56_0.mcap\n" + ] + } + ], + "source": [ + "def get_metrics(file_path: Path) -> Metric:\n", + " with _mcap_reader(file_path) as reader:\n", + " summary = reader.get_summary()\n", + " assert summary is not None, \"Summary is None\"\n", + "\n", + " has_imu_data = any(channel.topic == \"/imu/data\" for channel in summary.channels.values())\n", + "\n", + " metric: Metric = {\n", + " \"mcap_file_name\": file_path.name,\n", + " \"mcap_file_path\": file_path,\n", + " \"mcap_file_size_B\": file_path.stat().st_size,\n", + " \"duration_s\": duration(summary).total_seconds(),\n", + " \"num_images\": 0,\n", + " \"num_imu\": 0,\n", + " \"num_joint_states\": 0,\n", + " \"num_joint_commands\": 0,\n", + " \"num_game_states\": 0,\n", + " \"num_messages\": 0,\n", + " }\n", + "\n", + " for _, channel, _, ros_msg in reader.iter_decoded_messages(topics=USED_TOPICS):\n", + " match channel.topic:\n", + " case \"/camera/image_proc\":\n", + " metric[\"num_images\"] += 1\n", + " case \"/imu/data\" if has_imu_data:\n", + " metric[\"num_imu\"] += 1\n", + " case \"/joint_states\":\n", + " metric[\"num_joint_states\"] += 1\n", + " case \"/DynamixelController/command\":\n", + " metric[\"num_joint_commands\"] += 1\n", + " case \"/gamestate\":\n", + " metric[\"num_game_states\"] += 1\n", + " case \"/tf\" if not has_imu_data:\n", + " for tf_msg in ros_msg.transforms:\n", + " if tf_msg.child_frame_id == \"base_footprint\" and tf_msg.header.frame_id == \"base_link\":\n", + " metric[\"num_imu\"] += 1\n", + " case _:\n", + " pass\n", + "\n", + " metric[\"num_messages\"] = (\n", + " metric[\"num_images\"]\n", + " + metric[\"num_imu\"]\n", + " + metric[\"num_joint_states\"]\n", + " + metric[\"num_joint_commands\"]\n", + " + metric[\"num_game_states\"]\n", + " )\n", + "\n", + " return metric\n", + "\n", + "\n", + "# Get the metrics for each mcap file in parallel\n", + "def get_metrics_for_all_files():\n", + " metrics = []\n", + "\n", + " def process_file(row):\n", + " file_path = row[\"mcap_file_path\"]\n", + " print(f\"Processing {file_path}\")\n", + " metric = get_metrics(file_path)\n", + " return metric\n", + "\n", + " with ThreadPoolExecutor() as executor:\n", + " metrics = list(executor.map(process_file, [row for _, row in files.iterrows()]))\n", + "\n", + " return pd.DataFrame(metrics)\n", + "\n", + "\n", + "df = get_metrics_for_all_files()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df" ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "ddlitlab2024-bN9lk4bc-py3.10", "language": "python", "name": "python3" }, @@ -60,7 +343,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.1" + "version": "3.10.12" } }, "nbformat": 4, From 89800b224d5d4c0c71715dc9674650cc75332096 Mon Sep 17 00:00:00 2001 From: Jan Gutsche Date: Thu, 25 Sep 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b/soccer_diffusion/dataset/analyze_raw_data.ipynb index d51a6fd..5f12d03 100644 --- a/soccer_diffusion/dataset/analyze_raw_data.ipynb +++ b/soccer_diffusion/dataset/analyze_raw_data.ipynb @@ -10,31 +10,31 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "import sqlite3\n", - "from concurrent.futures import ThreadPoolExecutor\n", + "#import sqlite3\n", "from contextlib import contextmanager\n", "from datetime import datetime, timedelta\n", "from pathlib import Path\n", "from typing import TypedDict\n", "\n", "import pandas as pd\n", - "from ddlitlab2024 import DB_PATH\n", "from mcap.reader import make_reader\n", "from mcap.summary import Summary\n", - "from mcap_ros2.decoder import DecoderFactory" + "from mcap_ros2.decoder import DecoderFactory\n", + "\n", + "#from soccer_diffusion import DB_PATH" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "BASE_DIR = Path(\"/srv/rosbags\") # Same as https://data.bit-bots.de/ROSbags/" + "BASE_DIR = Path(\"/srv/data/data.bit-bots.de/ROSbags/\") # Same as https://data.bit-bots.de/ROSbags/" ] }, { @@ -43,65 +43,74 @@ "metadata": {}, "outputs": [], "source": [ - "# DB_PATH = Path(\"/srv/ssd_nvm/dataset/ddlitlab2024/db/robocup_2024_german_open_2025.sqlite3\") # TODO Remove me" + "#DB_PATH = Path(\"/srv/ssd_nvm/dataset/ddlitlab2024/db/robocup_2024_german_open_2025.sqlite3\") # TODO Remove me" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Connect read-only to the SQLite database\n", - "conn = sqlite3.connect(f\"file:{DB_PATH}?mode=ro\", uri=True)" + "#conn = sqlite3.connect(f\"file:{DB_PATH}?mode=ro\", uri=True)" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Get mcaps used by the database\n", - "query = \"\"\"\n", - "SELECT original_file FROM Recording;\n", - "\"\"\"\n", - "files = pd.DataFrame()\n", - "files[\"mcap_file_name\"] = pd.read_sql_query(query, conn)" + "# query = \"\"\"\n", + "# SELECT original_file FROM Recording;\n", + "# \"\"\"\n", + "# files = pd.DataFrame()\n", + "# files[\"mcap_file_name\"] = pd.read_sql_query(query, conn)" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Find the full file paths recursively contained in the following directory\n", - "def find_file(file_name):\n", - " candidates = []\n", - " for path in BASE_DIR.rglob(file_name):\n", - " candidates.append(path)\n", - " match len(candidates):\n", - " case 0:\n", - " print(f\"File {file_name} not found\")\n", - " return None\n", - " case 1:\n", - " return candidates[0]\n", - " case 2:\n", - " # Use the \"untrimmed\" version of the file if it exists\n", - " for candidate in candidates:\n", - " if \"untrimmed\" in str(candidate):\n", - " return candidate\n", - " print(f\"File {file_name} found multiple times: {candidates}\")\n", - " return None\n", - " case _:\n", - " print(f\"File {file_name} found multiple times: {candidates}\")\n", - " return None\n", - "\n", - "\n", - "# Find the full file paths for each mcap file\n", - "files[\"mcap_file_path\"] = files[\"mcap_file_name\"].apply(find_file)\n", - "assert files[\"mcap_file_path\"].notnull().all(), \"Some mcap files were not found\"" + "#def find_file(file_name):\n", + "# candidates = []\n", + "# for path in BASE_DIR.rglob(file_name):\n", + "# candidates.append(path)\n", + "# if len(candidates) == 0:\n", + "# print(f\"File {file_name} not found\")\n", + "# return None\n", + "# elif len(candidates) == 1:\n", + "# return candidates[0]\n", + "# elif len(candidates) == 2:\n", + "# # Use the \"untrimmed\" version of the file if it exists\n", + "# for candidate in candidates:\n", + "# if \"untrimmed\" in str(candidate):\n", + "# return candidate\n", + "# print(f\"File {file_name} found multiple times: {candidates}\")\n", + "# return None\n", + "# else:\n", + "# print(f\"File {file_name} found multiple times: {candidates}\")\n", + "# return None\n", + "#\n", + "#\n", + "## Find the full file paths for each mcap file\n", + "#files[\"mcap_file_path\"] = files[\"mcap_file_name\"].apply(find_file)\n", + "#assert files[\"mcap_file_path\"].notnull().all(), \"Some mcap files were not found\"\n", + "#files.to_csv(\"mcap_files.csv\", index=False)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "files = pd.read_csv(\"mcap_files.csv\")" ] }, { @@ -121,7 +130,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -178,74 +187,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T16:30:37/ID_donna_2024-07-19T16:30:37_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T11:31:28/ID_jack_2024-07-19T11:31:28_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-17T15:38:04/ID_jack_2024-07-17T15:38:04_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-18T13:29:30/ID_rory_2024-07-18T13:29:30_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T11:48:16/ID_donna_2024-07-19T11:48:16_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-18T13:54:46/ID_rory_2024-07-18T13:54:46_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-20T11:08:32/ID_jack_2024-07-20T11:08:32_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T09:50:25/ID_jack_2024-07-19T09:50:25_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T17:27:57/ID_jack_2024-07-19T17:27:57_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T18:29:22/ID_donna_2024-07-18T18:29:22_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T18:29:35/ID_jack_2024-07-18T18:29:35_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T18:31:02/ID_donna_2024-07-18T18:31:02_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T18:42:01/ID_jack_2024-07-18T18:42:01_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T16:17:13/ID_donna_2024-07-19T16:17:13_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T11:30:19/ID_donna_2024-07-19T11:30:19_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T17:58:04/ID_jack_2024-07-19T17:58:04_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T19:28:32/ID_donna_2024-07-18T19:28:32_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T18:47:57/ID_jack_2024-07-18T18:47:57_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-20T15:56:08/ID_jack_2024-07-20T15:56:08_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-20T15:27:30/ID_rory_2024-07-20T15:27:30_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-18T13:52:36/ID_rory_2024-07-18T13:52:36_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T18:38:45/ID_jack_2024-07-18T18:38:45_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T18:47:16/ID_donna_2024-07-18T18_47_16_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-20T15:45:49/ID_rory_2024-07-20T15:45:49_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-20T15:34:27/ID_rory_2024-07-20T15:34:27_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_amy_2024-07-18T10:26:27/ID_amy_2024-07-18T10:26:27_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T11:47:41/ID_jack_2024-07-19T11:47:41_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-19T17:45:15/ID_rory_2024-07-19T17:45:15_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T19:48:52/ID_donna_2024-07-18T19:48:52_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T17:11:35/ID_donna_2024-07-19T17:11:35_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-19T17:27:54/ID_rory_2024-07-19T17:27:54_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T11:29:50/ID_jack_2024-07-19T11:29:50_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T15:29:51/ID_donna_2024-07-18T15:29:51_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T17:05:54/ID_donna_2024-07-19T17:05:54_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-20T15:27:14/ID_jack_2024-07-20T15:27:14_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-20T15:26:55/ID_donna_2024-07-20T15:26:55_0.mcap\n", - "Processing 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/srv/rosbags/robocup_2024/ID_amy_2024-07-18T10:32:52/ID_amy_2024-07-18T10:32:52_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-17T15:35:46/ID_jack_2024-07-17T15:35:46_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-20T15:48:43/ID_jack_2024-07-20T15:48:43_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T17:35:46/ID_donna_2024-07-19T17:35:46_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-19T18:00:20/ID_donna_2024-07-19T18:00:20_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T19:28:29/ID_jack_2024-07-18T19:28:29_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T19:46:13/ID_jack_2024-07-18T19:46:13_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T19:38:20/ID_jack_2024-07-18T19:38:20_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-17T19:16:57/ID_rory_2024-07-17T19:16:57_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_donna_2024-07-18T15:00:02/ID_donna_2024-07-18T15:00:02_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-18T18:31:03/ID_jack_2024-07-18T18:31:03_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_rory_2024-07-20T15:40:46/ID_rory_2024-07-20T15:40:46_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-20T15:47:38/ID_jack_2024-07-20T15:47:38_0.mcap\n", - "Processing /srv/rosbags/robocup_2024/ID_jack_2024-07-19T17:46:07/ID_jack_2024-07-19T17:46:07_0.mcap\n", - "Processing /srv/rosbags/german_open_2025/original_untrimmed/ID_rory_2025-03-16T14:02:56/ID_rory_2025-03-16T14:02:56_0.mcap\n" - ] - } - ], + "outputs": [], "source": [ "def get_metrics(file_path: Path) -> Metric:\n", " with _mcap_reader(file_path) as reader:\n", @@ -268,23 +210,22 @@ " }\n", "\n", " for _, channel, _, ros_msg in reader.iter_decoded_messages(topics=USED_TOPICS):\n", - " match channel.topic:\n", - " case \"/camera/image_proc\":\n", - " metric[\"num_images\"] += 1\n", - " case \"/imu/data\" if has_imu_data:\n", - " metric[\"num_imu\"] += 1\n", - " case \"/joint_states\":\n", - " metric[\"num_joint_states\"] += 1\n", - " case \"/DynamixelController/command\":\n", - " metric[\"num_joint_commands\"] += 1\n", - " case \"/gamestate\":\n", - " metric[\"num_game_states\"] += 1\n", - " case \"/tf\" if not has_imu_data:\n", - " for tf_msg in ros_msg.transforms:\n", - " if tf_msg.child_frame_id == \"base_footprint\" and tf_msg.header.frame_id == \"base_link\":\n", - " metric[\"num_imu\"] += 1\n", - " case _:\n", - " pass\n", + " if channel.topic == \"/camera/image_proc\":\n", + " metric[\"num_images\"] += 1\n", + " elif channel.topic == \"/imu/data\" and has_imu_data:\n", + " metric[\"num_imu\"] += 1\n", + " elif channel.topic == \"/joint_states\":\n", + " metric[\"num_joint_states\"] += 1\n", + " elif channel.topic == \"/DynamixelController/command\":\n", + " metric[\"num_joint_commands\"] += 1\n", + " elif channel.topic == \"/gamestate\":\n", + " metric[\"num_game_states\"] += 1\n", + " elif channel.topic == \"/tf\" and not has_imu_data:\n", + " for tf_msg in ros_msg.transforms:\n", + " if tf_msg.child_frame_id == \"base_footprint\" and tf_msg.header.frame_id == \"base_link\":\n", + " metric[\"num_imu\"] += 1\n", + " else:\n", + " pass\n", "\n", " metric[\"num_messages\"] = (\n", " metric[\"num_images\"]\n", @@ -294,26 +235,7 @@ " + metric[\"num_game_states\"]\n", " )\n", "\n", - " return metric\n", - "\n", - "\n", - "# Get the metrics for each mcap file in parallel\n", - "def get_metrics_for_all_files():\n", - " metrics = []\n", - "\n", - " def process_file(row):\n", - " file_path = row[\"mcap_file_path\"]\n", - " print(f\"Processing {file_path}\")\n", - " metric = get_metrics(file_path)\n", - " return metric\n", - "\n", - " with ThreadPoolExecutor() as executor:\n", - " metrics = list(executor.map(process_file, [row for _, row in files.iterrows()]))\n", - "\n", - " return pd.DataFrame(metrics)\n", - "\n", - "\n", - "df = get_metrics_for_all_files()" + " return metric" ] }, { @@ -322,13 +244,30 @@ "metadata": {}, "outputs": [], "source": [ - "df" + "# For every file, get the metrics\n", + "# metrics = pd.DataFrame()\n", + "metrics = pd.read_csv(\"mcap_file_metrics.csv\")\n", + "for _, row in files.iterrows():\n", + " if row[\"mcap_file_name\"] in metrics[\"mcap_file_name\"].values:\n", + " print(f\"Skipping {row['mcap_file_name']} because it is already processed\")\n", + " continue\n", + " print(f\"Processing {row['mcap_file_name']}...\")\n", + " if pd.isna(row[\"mcap_file_path\"]):\n", + " print(f\"Skipping {row['mcap_file_name']} because file path is NaN\")\n", + " continue\n", + " file_path = Path(row[\"mcap_file_path\"])\n", + " if not file_path.exists():\n", + " print(f\"Skipping {row['mcap_file_name']} because file {file_path} does not exist\")\n", + " continue\n", + " metric = get_metrics(file_path)\n", + " metrics = pd.concat([metrics, pd.DataFrame([metric])], ignore_index=True)\n", + " metrics.to_csv(\"mcap_file_metrics.csv\", index=False)" ] } ], "metadata": { "kernelspec": { - "display_name": "ddlitlab2024-bN9lk4bc-py3.10", + "display_name": "Python 3", "language": "python", "name": "python3" }, @@ -342,7 +281,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.12" + "version": "3.9.2" } }, "nbformat": 4, diff --git a/soccer_diffusion/dataset/raw_data_metrics.csv b/soccer_diffusion/dataset/raw_data_metrics.csv new file mode 100644 index 0000000..0a32b19 --- /dev/null +++ b/soccer_diffusion/dataset/raw_data_metrics.csv @@ -0,0 +1,89 @@ +mcap_file_name,mcap_file_path,mcap_file_size_B,duration_s,num_images,num_imu,num_joint_states,num_joint_commands,num_game_states,num_messages +ID_donna_2024-07-19T16:30:37_0.mcap,/srv/data/data.bit-bots.de/ROSbags/robocup_2024/ID_donna_2024-07-19T16:30:37/ID_donna_2024-07-19T16:30:37_0.mcap,3827601913,689.85832,6894,14677,229438,50319,9,301337 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+ID_donna_2025-03-14T14:40:42_0.mcap,/srv/data/data.bit-bots.de/ROSbags/german_open_2025/original_untrimmed/ID_donna_2025-03-14T14:40:42/ID_donna_2025-03-14T14:40:42_0.mcap,2263696346,383.138529,3831,120613,136107,37225,673,298449 From 1f3cf53c81142468d88ad20bfcdfcc442bff0da5 Mon Sep 17 00:00:00 2001 From: Jan Gutsche Date: Sun, 28 Sep 2025 18:23:55 +0200 Subject: [PATCH 8/8] Raw data analysis --- .../dataset/analyze_raw_data.ipynb | 274 +++++++++++------- 1 file changed, 164 insertions(+), 110 deletions(-) diff --git a/soccer_diffusion/dataset/analyze_raw_data.ipynb b/soccer_diffusion/dataset/analyze_raw_data.ipynb index 5f12d03..52ce2d5 100644 --- a/soccer_diffusion/dataset/analyze_raw_data.ipynb +++ b/soccer_diffusion/dataset/analyze_raw_data.ipynb @@ -14,18 +14,16 @@ "metadata": {}, "outputs": [], "source": [ - "#import sqlite3\n", - "from contextlib import contextmanager\n", - "from datetime import datetime, timedelta\n", + "# import sqlite3\n", "from pathlib import Path\n", "from typing import TypedDict\n", "\n", "import pandas as pd\n", - "from mcap.reader import make_reader\n", - "from mcap.summary import Summary\n", - "from mcap_ros2.decoder import DecoderFactory\n", + "# from mcap.reader import make_reader\n", + "# from mcap.summary import Summary\n", + "# from mcap_ros2.decoder import DecoderFactory\n", "\n", - "#from soccer_diffusion import DB_PATH" + "# from soccer_diffusion import DB_PATH" ] }, { @@ -34,7 +32,7 @@ "metadata": {}, "outputs": [], "source": [ - "BASE_DIR = Path(\"/srv/data/data.bit-bots.de/ROSbags/\") # Same as https://data.bit-bots.de/ROSbags/" + "# BASE_DIR = Path(\"/srv/data/data.bit-bots.de/ROSbags/\") # Same as https://data.bit-bots.de/ROSbags/" ] }, { @@ -43,7 +41,7 @@ "metadata": {}, "outputs": [], "source": [ - "#DB_PATH = Path(\"/srv/ssd_nvm/dataset/ddlitlab2024/db/robocup_2024_german_open_2025.sqlite3\") # TODO Remove me" + "# DB_PATH = Path(\"/srv/ssd_nvm/dataset/ddlitlab2024/db/robocup_2024_german_open_2025.sqlite3\") # TODO Remove me" ] }, { @@ -53,7 +51,7 @@ "outputs": [], "source": [ "# Connect read-only to the SQLite database\n", - "#conn = sqlite3.connect(f\"file:{DB_PATH}?mode=ro\", uri=True)" + "# conn = sqlite3.connect(f\"file:{DB_PATH}?mode=ro\", uri=True)" ] }, { @@ -77,7 +75,7 @@ "outputs": [], "source": [ "# Find the full file paths recursively contained in the following directory\n", - "#def find_file(file_name):\n", + "# def find_file(file_name):\n", "# candidates = []\n", "# for path in BASE_DIR.rglob(file_name):\n", "# candidates.append(path)\n", @@ -99,9 +97,9 @@ "#\n", "#\n", "## Find the full file paths for each mcap file\n", - "#files[\"mcap_file_path\"] = files[\"mcap_file_name\"].apply(find_file)\n", - "#assert files[\"mcap_file_path\"].notnull().all(), \"Some mcap files were not found\"\n", - "#files.to_csv(\"mcap_files.csv\", index=False)" + "# files[\"mcap_file_path\"] = files[\"mcap_file_name\"].apply(find_file)\n", + "# assert files[\"mcap_file_path\"].notnull().all(), \"Some mcap files were not found\"\n", + "# files.to_csv(\"mcap_files.csv\", index=False)" ] }, { @@ -110,7 +108,7 @@ "metadata": {}, "outputs": [], "source": [ - "files = pd.read_csv(\"mcap_files.csv\")" + "# files = pd.read_csv(\"mcap_files.csv\")" ] }, { @@ -150,37 +148,37 @@ " num_messages: int\n", "\n", "\n", - "@contextmanager\n", - "def _mcap_reader(mcap_file_path: Path):\n", - " with open(mcap_file_path, \"rb\") as f:\n", - " yield make_reader(f, decoder_factories=[DecoderFactory()])\n", - "\n", - "\n", - "def duration(summary: Summary) -> timedelta:\n", - " first_msg_start_time = None\n", - " last_msg_end_time = None\n", - "\n", - " for chunk_index in summary.chunk_indexes:\n", - " if first_msg_start_time is None or chunk_index.message_start_time < first_msg_start_time:\n", - " first_msg_start_time = chunk_index.message_start_time\n", - " if last_msg_end_time is None or chunk_index.message_end_time > last_msg_end_time:\n", - " last_msg_end_time = chunk_index.message_end_time\n", - "\n", - " assert first_msg_start_time is not None, \"No start time found in the MCAP file\"\n", - " assert last_msg_end_time is not None, \"No end time found in the MCAP file\"\n", - "\n", - " return datetime.fromtimestamp(last_msg_end_time / 1e9) - datetime.fromtimestamp(first_msg_start_time / 1e9)\n", - "\n", - "\n", - "USED_TOPICS = [\n", - " \"/DynamixelController/command\",\n", - " \"/camera/image_proc\",\n", - " \"/camera/image_to_record\",\n", - " \"/gamestate\",\n", - " \"/imu/data\",\n", - " \"/joint_states\",\n", - " \"/tf\",\n", - "]" + "# @contextmanager\n", + "# def _mcap_reader(mcap_file_path: Path):\n", + "# with open(mcap_file_path, \"rb\") as f:\n", + "# yield make_reader(f, decoder_factories=[DecoderFactory()])\n", + "#\n", + "#\n", + "# def duration(summary: Summary) -> timedelta:\n", + "# first_msg_start_time = None\n", + "# last_msg_end_time = None\n", + "#\n", + "# for chunk_index in summary.chunk_indexes:\n", + "# if first_msg_start_time is None or chunk_index.message_start_time < first_msg_start_time:\n", + "# first_msg_start_time = chunk_index.message_start_time\n", + "# if last_msg_end_time is None or chunk_index.message_end_time > last_msg_end_time:\n", + "# last_msg_end_time = chunk_index.message_end_time\n", + "#\n", + "# assert first_msg_start_time is not None, \"No start time found in the MCAP file\"\n", + "# assert last_msg_end_time is not None, \"No end time found in the MCAP file\"\n", + "#\n", + "# return datetime.fromtimestamp(last_msg_end_time / 1e9) - datetime.fromtimestamp(first_msg_start_time / 1e9)\n", + "#\n", + "#\n", + "# USED_TOPICS = [\n", + "# \"/DynamixelController/command\",\n", + "# \"/camera/image_proc\",\n", + "# \"/camera/image_to_record\",\n", + "# \"/gamestate\",\n", + "# \"/imu/data\",\n", + "# \"/joint_states\",\n", + "# \"/tf\",\n", + "# ]" ] }, { @@ -189,53 +187,53 @@ "metadata": {}, "outputs": [], "source": [ - "def get_metrics(file_path: Path) -> Metric:\n", - " with _mcap_reader(file_path) as reader:\n", - " summary = reader.get_summary()\n", - " assert summary is not None, \"Summary is None\"\n", - "\n", - " has_imu_data = any(channel.topic == \"/imu/data\" for channel in summary.channels.values())\n", - "\n", - " metric: Metric = {\n", - " \"mcap_file_name\": file_path.name,\n", - " \"mcap_file_path\": file_path,\n", - " \"mcap_file_size_B\": file_path.stat().st_size,\n", - " \"duration_s\": duration(summary).total_seconds(),\n", - " \"num_images\": 0,\n", - " \"num_imu\": 0,\n", - " \"num_joint_states\": 0,\n", - " \"num_joint_commands\": 0,\n", - " \"num_game_states\": 0,\n", - " \"num_messages\": 0,\n", - " }\n", - "\n", - " for _, channel, _, ros_msg in reader.iter_decoded_messages(topics=USED_TOPICS):\n", - " if channel.topic == \"/camera/image_proc\":\n", - " metric[\"num_images\"] += 1\n", - " elif channel.topic == \"/imu/data\" and has_imu_data:\n", - " metric[\"num_imu\"] += 1\n", - " elif channel.topic == \"/joint_states\":\n", - " metric[\"num_joint_states\"] += 1\n", - " elif channel.topic == \"/DynamixelController/command\":\n", - " metric[\"num_joint_commands\"] += 1\n", - " elif channel.topic == \"/gamestate\":\n", - " metric[\"num_game_states\"] += 1\n", - " elif channel.topic == \"/tf\" and not has_imu_data:\n", - " for tf_msg in ros_msg.transforms:\n", - " if tf_msg.child_frame_id == \"base_footprint\" and tf_msg.header.frame_id == \"base_link\":\n", - " metric[\"num_imu\"] += 1\n", - " else:\n", - " pass\n", - "\n", - " metric[\"num_messages\"] = (\n", - " metric[\"num_images\"]\n", - " + metric[\"num_imu\"]\n", - " + metric[\"num_joint_states\"]\n", - " + metric[\"num_joint_commands\"]\n", - " + metric[\"num_game_states\"]\n", - " )\n", - "\n", - " return metric" + "# def get_metrics(file_path: Path) -> Metric:\n", + "# with _mcap_reader(file_path) as reader:\n", + "# summary = reader.get_summary()\n", + "# assert summary is not None, \"Summary is None\"\n", + "#\n", + "# has_imu_data = any(channel.topic == \"/imu/data\" for channel in summary.channels.values())\n", + "#\n", + "# metric: Metric = {\n", + "# \"mcap_file_name\": file_path.name,\n", + "# \"mcap_file_path\": file_path,\n", + "# \"mcap_file_size_B\": file_path.stat().st_size,\n", + "# \"duration_s\": duration(summary).total_seconds(),\n", + "# \"num_images\": 0,\n", + "# \"num_imu\": 0,\n", + "# \"num_joint_states\": 0,\n", + "# \"num_joint_commands\": 0,\n", + "# \"num_game_states\": 0,\n", + "# \"num_messages\": 0,\n", + "# }\n", + "#\n", + "# for _, channel, _, ros_msg in reader.iter_decoded_messages(topics=USED_TOPICS):\n", + "# if channel.topic == \"/camera/image_proc\":\n", + "# metric[\"num_images\"] += 1\n", + "# elif channel.topic == \"/imu/data\" and has_imu_data:\n", + "# metric[\"num_imu\"] += 1\n", + "# elif channel.topic == \"/joint_states\":\n", + "# metric[\"num_joint_states\"] += 1\n", + "# elif channel.topic == \"/DynamixelController/command\":\n", + "# metric[\"num_joint_commands\"] += 1\n", + "# elif channel.topic == \"/gamestate\":\n", + "# metric[\"num_game_states\"] += 1\n", + "# elif channel.topic == \"/tf\" and not has_imu_data:\n", + "# for tf_msg in ros_msg.transforms:\n", + "# if tf_msg.child_frame_id == \"base_footprint\" and tf_msg.header.frame_id == \"base_link\":\n", + "# metric[\"num_imu\"] += 1\n", + "# else:\n", + "# pass\n", + "#\n", + "# metric[\"num_messages\"] = (\n", + "# metric[\"num_images\"]\n", + "# + metric[\"num_imu\"]\n", + "# + metric[\"num_joint_states\"]\n", + "# + metric[\"num_joint_commands\"]\n", + "# + metric[\"num_game_states\"]\n", + "# )\n", + "#\n", + "# return metric" ] }, { @@ -246,28 +244,84 @@ "source": [ "# For every file, get the metrics\n", "# metrics = pd.DataFrame()\n", - "metrics = pd.read_csv(\"mcap_file_metrics.csv\")\n", - "for _, row in files.iterrows():\n", - " if row[\"mcap_file_name\"] in metrics[\"mcap_file_name\"].values:\n", - " print(f\"Skipping {row['mcap_file_name']} because it is already processed\")\n", - " continue\n", - " print(f\"Processing {row['mcap_file_name']}...\")\n", - " if pd.isna(row[\"mcap_file_path\"]):\n", - " print(f\"Skipping {row['mcap_file_name']} because file path is NaN\")\n", - " continue\n", - " file_path = Path(row[\"mcap_file_path\"])\n", - " if not file_path.exists():\n", - " print(f\"Skipping {row['mcap_file_name']} because file {file_path} does not exist\")\n", + "# metrics = pd.read_csv(\"raw_data_metrics.csv\")\n", + "# for _, row in files.iterrows():\n", + "# if row[\"mcap_file_name\"] in metrics[\"mcap_file_name\"].values:\n", + "# print(f\"Skipping {row['mcap_file_name']} because it is already processed\")\n", + "# continue\n", + "# print(f\"Processing {row['mcap_file_name']}...\")\n", + "# if pd.isna(row[\"mcap_file_path\"]):\n", + "# print(f\"Skipping {row['mcap_file_name']} because file path is NaN\")\n", + "# continue\n", + "# file_path = Path(row[\"mcap_file_path\"])\n", + "# if not file_path.exists():\n", + "# print(f\"Skipping {row['mcap_file_name']} because file {file_path} does not exist\")\n", + "# continue\n", + "# metric = get_metrics(file_path)\n", + "# metrics = pd.concat([metrics, pd.DataFrame([metric])], ignore_index=True)\n", + "# metrics.to_csv(\"raw_data_metrics.csv\", index=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Describe the metrics" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv(\"raw_data_metrics.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df[\"duration_m\"] = df[\"duration_s\"] / 60\n", + "df[\"mcap_file_size_MB\"] = df[\"mcap_file_size_B\"] / (1024 * 1024)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = df.sort_values(by=\"duration_s\", ascending=False)\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Print latex for each column\n", + "for column in df.columns:\n", + " if column in [\"mcap_file_name\", \"mcap_file_path\"]:\n", " continue\n", - " metric = get_metrics(file_path)\n", - " metrics = pd.concat([metrics, pd.DataFrame([metric])], ignore_index=True)\n", - " metrics.to_csv(\"mcap_file_metrics.csv\", index=False)" + " if column in [\"duration_s\", \"duration_m\"]:\n", + " print(\n", + " f\"{column} & {df[column].min():.2f} & {df[column].mean():.2f}±{df[column].std():.2f} & {df[column].max():.2f} & {df[column].sum():.2f}\\\\\\\\\" # noqa: E501\n", + " )\n", + " else:\n", + " print(\n", + " f\"{column} & {df[column].min():.0f} & {df[column].mean():.0f}±{df[column].std():.0f} & {df[column].max():.0f} & {df[column].sum():.0f}\\\\\\\\\" # noqa: E501\n", + " )" ] } ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "soccer-diffusion-BHG-jKSn-py3.12", "language": "python", "name": "python3" }, @@ -281,7 +335,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.2" + "version": "3.12.3" } }, "nbformat": 4,