try ultralytics

poetry.lock

@@ -229,6 +229,46 @@ webencodings = "*"
 [package.extras]
 css = ["tinycss2 (>=1.1.0,<1.3)"]
 
+[[package]]
+name = "boxmot"
+version = "10.0.43"
+description = "SOTA tracking methods for detection, segmentation and pose estimation models."
+optional = false
+python-versions = ">=3.8"
+files = []
+develop = false
+
+[package.dependencies]
+filterpy = ">=1.4.5"
+ftfy = ">=6.1.1"
+gdown = ">=4.7.1"
+GitPython = ">=3.1.0"
+lapx = ">=0.5.4"
+loguru = ">=0.7.0"
+numpy = "1.24.4"
+opencv-python = ">=4.6.0"
+pandas = ">=1.1.4"
+pre-commit = ">=3.3.3"
+PyYAML = ">=5.3.1"
+regex = ">=2023.6.3"
+scikit-learn = ">=1.3.0"
+tensorboard = ">=2.13.0"
+torch = ">=1.7.0"
+torchvision = ">=0.8.1"
+yacs = ">=0.1.8"
+
+[package.extras]
+dev = ["coverage", "pre-commit", "pytest", "pytest-cov"]
+evolve = ["joblib", "kaleido", "optuna", "plotly"]
+export = ["nvidia-pyindex", "nvidia-tensorrt", "onnx (>=1.12.0)", "onnx-graphsurgeon", "onnx2tf (>=1.10.0)", "onnxsim (>=0.4.1)", "openvino-dev (>=2022.3)", "sng4onnx"]
+yolo = ["super-gradients (==3.1.1)", "thop", "ultralytics (==8.0.124)", "yolox (==0.3.0)"]
+
+[package.source]
+type = "git"
+url = "https://github.com/mikel-brostrom/yolo_tracking.git"
+reference = "e672838"
+resolved_reference = "e672838829f9e7bfe1c5b0ffa870d0225124fed5"
+
 [[package]]
 name = "cachetools"
 version = "5.3.1"
@@ -315,6 +355,17 @@ files = [
 [package.dependencies]
 pycparser = "*"
 
+[[package]]
+name = "cfgv"
+version = "3.4.0"
+description = "Validate configuration and produce human readable error messages."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "cfgv-3.4.0-py2.py3-none-any.whl", hash = "sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9"},
+    {file = "cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560"},
+]
+
 [[package]]
 name = "charset-normalizer"
 version = "3.3.0"
@@ -459,6 +510,73 @@ files = [
 docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
 tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
+[[package]]
+name = "cython"
+version = "3.0.4"
+description = "The Cython compiler for writing C extensions in the Python language."
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
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+    {file = "Cython-3.0.4-cp39-cp39-win_amd64.whl", hash = "sha256:003ccc40e0867770db0018274977d1874e4df64983d5e3e36937f107e0b2fdf6"},
+    {file = "Cython-3.0.4-py2.py3-none-any.whl", hash = "sha256:e5e2859f97e9cceb8e70b0934c56157038b8b083245898593008162a70536d7e"},
+    {file = "Cython-3.0.4.tar.gz", hash = "sha256:2e379b491ee985d31e5faaf050f79f4a8f59f482835906efe4477b33b4fbe9ff"},
+]
+
 [[package]]
 name = "debugpy"
 version = "1.8.0"
@@ -553,6 +671,17 @@ files = [
 [package.extras]
 graph = ["objgraph (>=1.7.2)"]
 
+[[package]]
+name = "distlib"
+version = "0.3.7"
+description = "Distribution utilities"
+optional = false
+python-versions = "*"
+files = [
+    {file = "distlib-0.3.7-py2.py3-none-any.whl", hash = "sha256:2e24928bc811348f0feb63014e97aaae3037f2cf48712d51ae61df7fd6075057"},
+    {file = "distlib-0.3.7.tar.gz", hash = "sha256:9dafe54b34a028eafd95039d5e5d4851a13734540f1331060d31c9916e7147a8"},
+]
+
 [[package]]
 name = "exceptiongroup"
 version = "1.1.3"
@@ -595,6 +724,37 @@ files = [
 [package.extras]
 devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"]
 
+[[package]]
+name = "filelock"
+version = "3.12.4"
+description = "A platform independent file lock."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "filelock-3.12.4-py3-none-any.whl", hash = "sha256:08c21d87ded6e2b9da6728c3dff51baf1dcecf973b768ef35bcbc3447edb9ad4"},
+    {file = "filelock-3.12.4.tar.gz", hash = "sha256:2e6f249f1f3654291606e046b09f1fd5eac39b360664c27f5aad072012f8bcbd"},
+]
+
+[package.extras]
+docs = ["furo (>=2023.7.26)", "sphinx (>=7.1.2)", "sphinx-autodoc-typehints (>=1.24)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.3)", "diff-cover (>=7.7)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)", "pytest-timeout (>=2.1)"]
+typing = ["typing-extensions (>=4.7.1)"]
+
+[[package]]
+name = "filterpy"
+version = "1.4.5"
+description = "Kalman filtering and optimal estimation library"
+optional = false
+python-versions = "*"
+files = [
+    {file = "filterpy-1.4.5.zip", hash = "sha256:4f2a4d39e4ea601b9ab42b2db08b5918a9538c168cff1c6895ae26646f3d73b1"},
+]
+
+[package.dependencies]
+matplotlib = "*"
+numpy = "*"
+scipy = "*"
+
 [[package]]
 name = "fire"
 version = "0.5.0"
@@ -685,6 +845,69 @@ files = [
     {file = "fqdn-1.5.1.tar.gz", hash = "sha256:105ed3677e767fb5ca086a0c1f4bb66ebc3c100be518f0e0d755d9eae164d89f"},
 ]
 
+[[package]]
+name = "ftfy"
+version = "6.1.1"
+description = "Fixes mojibake and other problems with Unicode, after the fact"
+optional = false
+python-versions = ">=3.7,<4"
+files = [
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+    {file = "ftfy-6.1.1.tar.gz", hash = "sha256:bfc2019f84fcd851419152320a6375604a0f1459c281b5b199b2cd0d2e727f8f"},
+]
+
+[package.dependencies]
+wcwidth = ">=0.2.5"
+
+[[package]]
+name = "gdown"
+version = "4.7.1"
+description = "Google Drive direct download of big files."
+optional = false
+python-versions = "*"
+files = [
+    {file = "gdown-4.7.1-py3-none-any.whl", hash = "sha256:65d495699e7c2c61af0d0e9c32748fb4f79abaf80d747a87456c7be14aac2560"},
+    {file = "gdown-4.7.1.tar.gz", hash = "sha256:347f23769679aaf7efa73e5655270fcda8ca56be65eb84a4a21d143989541045"},
+]
+
+[package.dependencies]
+beautifulsoup4 = "*"
+filelock = "*"
+requests = {version = "*", extras = ["socks"]}
+six = "*"
+tqdm = "*"
+
+[[package]]
+name = "gitdb"
+version = "4.0.11"
+description = "Git Object Database"
+optional = false
+python-versions = ">=3.7"
+files = [
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+    {file = "gitdb-4.0.11.tar.gz", hash = "sha256:bf5421126136d6d0af55bc1e7c1af1c397a34f5b7bd79e776cd3e89785c2b04b"},
+]
+
+[package.dependencies]
+smmap = ">=3.0.1,<6"
+
+[[package]]
+name = "gitpython"
+version = "3.1.40"
+description = "GitPython is a Python library used to interact with Git repositories"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "GitPython-3.1.40-py3-none-any.whl", hash = "sha256:cf14627d5a8049ffbf49915732e5eddbe8134c3bdb9d476e6182b676fc573f8a"},
+    {file = "GitPython-3.1.40.tar.gz", hash = "sha256:22b126e9ffb671fdd0c129796343a02bf67bf2994b35449ffc9321aa755e18a4"},
+]
+
+[package.dependencies]
+gitdb = ">=4.0.1,<5"
+
+[package.extras]
+test = ["black", "coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre-commit", "pytest", "pytest-cov", "pytest-instafail", "pytest-subtests", "pytest-sugar"]
+
 [[package]]
 name = "google-auth"
 version = "2.23.3"
@@ -710,17 +933,17 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
 [[package]]
 name = "google-auth-oauthlib"
-version = "0.4.6"
+version = "1.0.0"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [package.dependencies]
-google-auth = ">=1.0.0"
+google-auth = ">=2.15.0"
 requests-oauthlib = ">=0.7.0"
 
 [package.extras]
@@ -792,6 +1015,20 @@ files = [
 [package.extras]
 protobuf = ["grpcio-tools (>=1.59.0)"]
 
+[[package]]
+name = "identify"
+version = "2.5.30"
+description = "File identification library for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.extras]
+license = ["ukkonen"]
+
 [[package]]
 name = "idna"
 version = "3.4"
@@ -1320,6 +1557,67 @@ files = [
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 ]
 
+[[package]]
+name = "lapx"
+version = "0.5.5"
+description = "Linear Assignment Problem solver (LAPJV/LAPMOD)."
+optional = false
+python-versions = "*"
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+numpy = ">=1.21.6"
+
+[[package]]
+name = "loguru"
+version = "0.7.2"
+description = "Python logging made (stupidly) simple"
+optional = false
+python-versions = ">=3.5"
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+[package.dependencies]
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+win32-setctime = {version = ">=1.0.0", markers = "sys_platform == \"win32\""}
+
+[package.extras]
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+
 [[package]]
 name = "markdown"
 version = "3.5"
@@ -1627,6 +1925,20 @@ files = [
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 ]
 
+[[package]]
+name = "nodeenv"
+version = "1.8.0"
+description = "Node.js virtual environment builder"
+optional = false
+python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*"
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+]
+
+[package.dependencies]
+setuptools = "*"
+
 [[package]]
 name = "notebook"
 version = "7.0.6"
@@ -1669,43 +1981,39 @@ test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"
 
 [[package]]
 name = "numpy"
-version = "1.26.1"
+version = "1.24.4"
 description = "Fundamental package for array computing in Python"
 optional = false
-python-versions = "<3.13,>=3.9"
+python-versions = ">=3.8"
 files = [
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 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)"]
 
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+pyyaml = ">=5.1"
+virtualenv = ">=20.10.0"
+
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 name = "prometheus-client"
 version = "0.17.1"
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 name = "protobuf"
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 [[package]]
@@ -2165,6 +2482,17 @@ files = [
 [package.extras]
 tests = ["pytest"]
 
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 [[package]]
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@@ -2281,6 +2609,18 @@ numpy = "*"
 dev = ["mkdocs"]
 test = ["nose"]
 
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+]
+
 [[package]]
 name = "requests"
 version = "2.31.0"
@@ -2539,6 +2976,7 @@ files = [
 certifi = ">=2017.4.17"
 charset-normalizer = ">=2,<4"
 idna = ">=2.5,<4"
+PySocks = {version = ">=1.5.6,<1.5.7 || >1.5.7", optional = true, markers = "extra == \"socks\""}
 urllib3 = ">=1.21.1,<3"
 
 [package.extras]
@@ -2919,6 +3357,17 @@ files = [
     {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
 ]
 
+[[package]]
+name = "smmap"
+version = "5.0.1"
+description = "A pure Python implementation of a sliding window memory map manager"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "smmap-5.0.1-py3-none-any.whl", hash = "sha256:e6d8668fa5f93e706934a62d7b4db19c8d9eb8cf2adbb75ef1b675aa332b69da"},
+    {file = "smmap-5.0.1.tar.gz", hash = "sha256:dceeb6c0028fdb6734471eb07c0cd2aae706ccaecab45965ee83f11c8d3b1f62"},
+]
+
 [[package]]
 name = "sniffio"
 version = "1.3.0"
@@ -2962,49 +3411,38 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
 [[package]]
 name = "tensorboard"
-version = "2.11.0"
+version = "2.14.1"
 description = "TensorBoard lets you watch Tensors Flow"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
-    {file = "tensorboard-2.11.0-py3-none-any.whl", hash = "sha256:a0e592ee87962e17af3f0dce7faae3fbbd239030159e9e625cce810b7e35c53d"},
+    {file = "tensorboard-2.14.1-py3-none-any.whl", hash = "sha256:3db108fb58f023b6439880e177743c5f1e703e9eeb5fb7d597871f949f85fd58"},
 ]
 
 [package.dependencies]
 absl-py = ">=0.4"
 google-auth = ">=1.6.3,<3"
-google-auth-oauthlib = ">=0.4.1,<0.5"
+google-auth-oauthlib = ">=0.5,<1.1"
-grpcio = ">=1.24.3"
+grpcio = ">=1.48.2"
 markdown = ">=2.6.8"
 numpy = ">=1.12.0"
-protobuf = ">=3.9.2,<4"
+protobuf = ">=3.19.6"
 requests = ">=2.21.0,<3"
 setuptools = ">=41.0.0"
-tensorboard-data-server = ">=0.6.0,<0.7.0"
+six = ">1.9"
-tensorboard-plugin-wit = ">=1.6.0"
+tensorboard-data-server = ">=0.7.0,<0.8.0"
 werkzeug = ">=1.0.1"
-wheel = ">=0.26"
 
 [[package]]
 name = "tensorboard-data-server"
-version = "0.6.1"
+version = "0.7.1"
 description = "Fast data loading for TensorBoard"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 files = [
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-]
-
-[[package]]
-name = "tensorboard-plugin-wit"
-version = "1.8.1"
-description = "What-If Tool TensorBoard plugin."
-optional = false
-python-versions = "*"
-files = [
-    {file = "tensorboard_plugin_wit-1.8.1-py3-none-any.whl", hash = "sha256:ff26bdd583d155aa951ee3b152b3d0cffae8005dc697f72b44a8e8c2a77a8cbe"},
 ]
 
 [[package]]
@@ -3057,6 +3495,19 @@ tornado = ">=6.1.0"
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
 test = ["pre-commit", "pytest (>=7.0)", "pytest-timeout"]
 
+[[package]]
+name = "thop"
+version = "0.1.1.post2209072238"
+description = "A tool to count the FLOPs of PyTorch model."
+optional = false
+python-versions = "*"
+files = [
+    {file = "thop-0.1.1.post2209072238-py3-none-any.whl", hash = "sha256:01473c225231927d2ad718351f78ebf7cffe6af3bed464c4f1ba1ef0f7cdda27"},
+]
+
+[package.dependencies]
+torch = "*"
+
 [[package]]
 name = "threadpoolctl"
 version = "3.2.0"
@@ -3218,7 +3669,7 @@ scikit-learn = "^1.3.1"
 scipy = "^1.11.3"
 seaborn = "^0.13.0"
 setuptools = "^68.2.2"
-tensorboard = "2.11"
+tensorboard = "^2.11"
 tensorboardx = "^2.6.2.2"
 torch = [
     {url = "https://download.pytorch.org/whl/cu113/torch-1.12.1%2Bcu113-cp310-cp310-linux_x86_64.whl", markers = "python_version ~= \"3.10\" and sys_platform == \"linux\""},
@@ -3263,6 +3714,38 @@ files = [
     {file = "tzdata-2023.3.tar.gz", hash = "sha256:11ef1e08e54acb0d4f95bdb1be05da659673de4acbd21bf9c69e94cc5e907a3a"},
 ]
 
+[[package]]
+name = "ultralytics"
+version = "8.0.200"
+description = "Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "ultralytics-8.0.200-py3-none-any.whl", hash = "sha256:68de5a0db71eb3c1eadc55d2303e559804630e3b07d30b66415520ca135716bc"},
+    {file = "ultralytics-8.0.200.tar.gz", hash = "sha256:d6f46048dcc0827e370e391c825c2aa26136e40da5464a8c667d2424c2bffd2f"},
+]
+
+[package.dependencies]
+matplotlib = ">=3.3.0"
+numpy = ">=1.22.2"
+opencv-python = ">=4.6.0"
+pandas = ">=1.1.4"
+pillow = ">=7.1.2"
+psutil = "*"
+py-cpuinfo = "*"
+pyyaml = ">=5.3.1"
+requests = ">=2.23.0"
+scipy = ">=1.4.1"
+seaborn = ">=0.11.0"
+thop = ">=0.1.1"
+torch = ">=1.8.0"
+torchvision = ">=0.9.0"
+tqdm = ">=4.64.0"
+
+[package.extras]
+dev = ["check-manifest", "coverage", "ipython", "mkdocs-material", "mkdocs-redirects", "mkdocs-ultralytics-plugin (>=0.0.29)", "mkdocstrings[python]", "pre-commit", "pytest", "pytest-cov"]
+export = ["coremltools (>=7.0)", "openvino-dev (>=2023.0)", "tensorflow (<=2.13.1)", "tensorflowjs"]
+
 [[package]]
 name = "uri-template"
 version = "1.3.0"
@@ -3294,6 +3777,26 @@ secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.
 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]
 
+[[package]]
+name = "virtualenv"
+version = "20.24.5"
+description = "Virtual Python Environment builder"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "virtualenv-20.24.5-py3-none-any.whl", hash = "sha256:b80039f280f4919c77b30f1c23294ae357c4c8701042086e3fc005963e4e537b"},
+    {file = "virtualenv-20.24.5.tar.gz", hash = "sha256:e8361967f6da6fbdf1426483bfe9fca8287c242ac0bc30429905721cefbff752"},
+]
+
+[package.dependencies]
+distlib = ">=0.3.7,<1"
+filelock = ">=3.12.2,<4"
+platformdirs = ">=3.9.1,<4"
+
+[package.extras]
+docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
+test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
+
 [[package]]
 name = "wcwidth"
 version = "0.2.8"
@@ -3365,20 +3868,35 @@ MarkupSafe = ">=2.1.1"
 watchdog = ["watchdog (>=2.3)"]
 
 [[package]]
-name = "wheel"
+name = "win32-setctime"
-version = "0.41.2"
+version = "1.1.0"
-description = "A built-package format for Python"
+description = "A small Python utility to set file creation time on Windows"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.5"
 files = [
-    {file = "wheel-0.41.2-py3-none-any.whl", hash = "sha256:75909db2664838d015e3d9139004ee16711748a52c8f336b52882266540215d8"},
+    {file = "win32_setctime-1.1.0-py3-none-any.whl", hash = "sha256:231db239e959c2fe7eb1d7dc129f11172354f98361c4fa2d6d2d7e278baa8aad"},
-    {file = "wheel-0.41.2.tar.gz", hash = "sha256:0c5ac5ff2afb79ac23ab82bab027a0be7b5dbcf2e54dc50efe4bf507de1f7985"},
+    {file = "win32_setctime-1.1.0.tar.gz", hash = "sha256:15cf5750465118d6929ae4de4eb46e8edae9a5634350c01ba582df868e932cb2"},
 ]
 
 [package.extras]
-test = ["pytest (>=6.0.0)", "setuptools (>=65)"]
+dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"]
+
+[[package]]
+name = "yacs"
+version = "0.1.8"
+description = "Yet Another Configuration System"
+optional = false
+python-versions = "*"
+files = [
+    {file = "yacs-0.1.8-py2-none-any.whl", hash = "sha256:d43d1854c1ffc4634c5b349d1c1120f86f05c3a294c9d141134f282961ab5d94"},
+    {file = "yacs-0.1.8-py3-none-any.whl", hash = "sha256:99f893e30497a4b66842821bac316386f7bd5c4f47ad35c9073ef089aa33af32"},
+    {file = "yacs-0.1.8.tar.gz", hash = "sha256:efc4c732942b3103bea904ee89af98bcd27d01f0ac12d8d4d369f1e7a2914384"},
+]
+
+[package.dependencies]
+PyYAML = "*"
 
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10,<3.12,"
-content-hash = "54eabff3ca832efc7790a1044ace59b882e134b536d45c42df91701a7001a6c0"
+content-hash = "d220aef575cc8223929a215a2a6094bb9bc2644a674ae1a2fca93f39b7fca9b4"

pyproject.toml

@@ -25,7 +25,7 @@ torchvision = [
        { url = "https://download.pytorch.org/whl/cu113/torchvision-0.13.1%2Bcu113-cp310-cp310-linux_x86_64.whl", markers = "python_version ~= '3.10' and sys_platform == 'linux'" },
 ]
 deep-sort-realtime = "^1.3.2"
-
+ultralytics = "^8.0.200"
 
 [build-system]
 requires = ["poetry-core"]

run_server.py

@@ -1,5 +0,0 @@
-from trap import plumber
-
-if __name__ == "__main__":
-    plumber.start()
-

trap/config.py

@@ -2,6 +2,8 @@ import argparse
 from pathlib import Path
 import types
 
+from trap.tracker import DETECTORS
+
 from pyparsing import Optional
 
 class LambdaParser(argparse.ArgumentParser):
@@ -208,6 +210,10 @@ tracker_parser.add_argument("--save-for-training",
                     help="Specify the path in which to save",
                     type=Path,
                     default=None)
+tracker_parser.add_argument("--detector",
+                    help="Specify the detector to use",
+                    type=str,
+                    choices=DETECTORS)
 
 # Renderer
 

trap/plumber.py

@@ -93,3 +93,6 @@ def start():
     
     logger.info('Stop')
 
+
+if __name__ == "__main__":
+    start()

trap/renderer.py

@@ -22,14 +22,13 @@ class Renderer:
         self.prediction_sock = context.socket(zmq.SUB)
         self.prediction_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. NB. make sure this comes BEFORE connect, otherwise it's ignored!!
         self.prediction_sock.setsockopt(zmq.SUBSCRIBE, b'')
-        self.prediction_sock.connect(config.zmq_prediction_addr)
+        self.prediction_sock.connect(config.zmq_prediction_addr if not self.config.bypass_prediction else config.zmq_trajectory_addr)
         
         self.frame_sock = context.socket(zmq.SUB)
         self.frame_sock.setsockopt(zmq.CONFLATE, 1) # only keep latest frame. NB. make sure this comes BEFORE connect, otherwise it's ignored!!
         self.frame_sock.setsockopt(zmq.SUBSCRIBE, b'')
         self.frame_sock.connect(config.zmq_frame_addr)
     
-    
         self.H = np.loadtxt(self.config.homography, delimiter=',')
 
         self.inv_H = np.linalg.pinv(self.H)
@@ -73,10 +72,12 @@ class Renderer:
             for track_id, prediction in predictions.items():
                 if not 'history' in prediction or not len(prediction['history']):
                     continue
+                
                 coords = cv2.perspectiveTransform(np.array([prediction['history']]), self.inv_H)[0]
                 # logger.warning(f"{coords=}")
                 center = [int(p) for p in coords[-1]]
                 cv2.circle(img, center, 5, (0,255,0))
+                cv2.putText(img, track_id, (center[0]+8, center[1]), cv2.FONT_HERSHEY_SIMPLEX, fontScale=.8, color=(0,255,0))
 
                 for ci in range(1, len(coords)):
                     start = [int(p) for p in coords[ci-1]]
@@ -91,7 +92,7 @@ class Renderer:
                     for ci in range(1, len(pred_coords)):
                         start = [int(p) for p in pred_coords[ci-1]]
                         end = [int(p) for p in pred_coords[ci]]
-                        cv2.line(img, start, end, (0,0,255), 2)
+                        cv2.line(img, start, end, (0,0,255), 1)
 
 
 

trap/tracker.py

@@ -1,5 +1,7 @@
 from argparse import Namespace
+from collections import defaultdict
 import csv
+from dataclasses import dataclass, field
 import json
 import logging
 from multiprocessing import Event
@@ -11,9 +13,12 @@ import torch
 import zmq
 import cv2
 
-from torchvision.models.detection import retinanet_resnet50_fpn_v2, RetinaNet_ResNet50_FPN_V2_Weights
+from torchvision.models.detection import retinanet_resnet50_fpn_v2, RetinaNet_ResNet50_FPN_V2_Weights, keypointrcnn_resnet50_fpn, KeypointRCNN_ResNet50_FPN_Weights
 from deep_sort_realtime.deepsort_tracker import DeepSort
-from deep_sort_realtime.deep_sort.track import Track
+from deep_sort_realtime.deep_sort.track import Track as DeepsortTrack
+
+from ultralytics import YOLO
+from ultralytics.engine.results import Results as YOLOResult
 
 from trap.frame_emitter import Frame
 
@@ -28,6 +33,33 @@ TARGET_DT = .1
 
 logger = logging.getLogger("trap.tracker")
 
+DETECTOR_RESNET = 'resnet'
+DETECTOR_YOLOv8 = 'ultralytics'
+
+DETECTORS = [DETECTOR_RESNET, DETECTOR_YOLOv8]
+
+@dataclass
+class Track:
+    track_id: str = None
+    history: [Detection]= field(default_factory=lambda: [])
+
+@dataclass
+class Detection:
+    track_id: str
+    l: int # left
+    t: int # top
+    w: int # width
+    h: int # height
+
+    def get_foot_coords(self):
+        return [self.l + 0.5 * self.w, self.t+self.h]
+
+    @classmethod
+    def from_deepsort(cls, dstrack: DeepsortTrack):
+        return cls(dstrack.track_id, *dstrack.to_ltwh())
+
+    
+
 class Tracker:
     def __init__(self, config: Namespace, is_running: Event):
         self.config = config
@@ -46,20 +78,30 @@ class Tracker:
         # # TODO: config device
         self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-        weights = RetinaNet_ResNet50_FPN_V2_Weights.DEFAULT
+        # TODO: support removal
-        self.model = retinanet_resnet50_fpn_v2(weights=weights, score_thresh=0.35)
+        self.tracks = defaultdict(lambda: Track())
+
+        if self.config.detector == DETECTOR_RESNET:
+            # weights = RetinaNet_ResNet50_FPN_V2_Weights.DEFAULT
+            # self.model = retinanet_resnet50_fpn_v2(weights=weights, score_thresh=0.2)
+            weights = KeypointRCNN_ResNet50_FPN_Weights.DEFAULT
+            self.model = keypointrcnn_resnet50_fpn(weights=weights, box_score_thresh=0.20)
             self.model.to(self.device)
             # Put the model in inference mode
             self.model.eval()
             # Get the transforms for the model's weights
             self.preprocess = weights.transforms().to(self.device)
+        elif self.config.detector == DETECTOR_YOLOv8:
+            self.model = YOLO('EXPERIMENTS/yolov8x.pt')
+        else: 
+            raise RuntimeError("No valid detector specified. See --help")
 
 
         # homography = list(source.glob('*img2world.txt'))[0]
 
         self.H = np.loadtxt(self.config.homography, delimiter=',')
 
-        self.mot_tracker = DeepSort(max_age=5)
+        self.mot_tracker = DeepSort(max_age=30, nms_max_overlap=0.9)
         logger.debug("Set up tracker")
         
 
@@ -94,30 +136,46 @@ class Tracker:
             # logger.info(f"Frame delivery delay = {time.time()-frame.time}s")
             start_time = time.time()
 
-            detections = self.detect_persons(frame.img)
-            tracks: [Track] = self.mot_tracker.update_tracks(detections, frame=frame.img)
 
-            TEMP_boxes = [t.to_ltwh() for t in tracks]
+            if self.config.detector == DETECTOR_YOLOv8:
-            TEMP_coords = np.array([[[det[0] + 0.5 * det[2], det[1]+det[3]]] for det in TEMP_boxes])
+                detections: [Detection]  = self._yolov8_track(frame.img)
-            if len(TEMP_coords):
-                TEMP_proj_coords = cv2.perspectiveTransform(TEMP_coords,self.H)
             else :
-                TEMP_proj_coords = []
+                detections: [Detection] = self._resnet_track(frame.img)
+            
+                
+            # Store detections into tracklets
+            for detection in detections:
+                track = self.tracks[detection.track_id]
+                track.track_id = detection.track_id # for new tracks
+
+                track.history.append(detection) 
+                # if len(track.history) > 30:  # retain 90 tracks for 90 frames
+                #     track.history.pop(0)
+
+            foot_coordinates = np.array([[t.get_foot_coords()] for t in detections])
+            if len(foot_coordinates):
+                projected_coordinates = cv2.perspectiveTransform(foot_coordinates,self.H)
+            else:
+                projected_coordinates = []
 
             # print(TEMP_proj_coords)
             trajectories = {}
-            for i, coords in enumerate(TEMP_proj_coords):
+            for detection, coords in zip(detections, projected_coordinates):
-                 tid = tracks[i].track_id
+                 tid = str(detection.track_id)
                  trajectories[tid] = {
                      "id": tid,
-                     "history": [{"x":c[0], "y":c[1]} for c in coords] # already doubles nested, fine for test
+                     "history": [{"x":c[0], "y":c[1]} for c in coords] if not self.config.bypass_prediction else coords.tolist() # already doubles nested, fine for test
                  }
-            # logger.debug(f"{trajectories}")
+            # logger.info(f"{trajectories}")
             frame.trajectories = trajectories
 
             current_time = time.time()
             logger.debug(f"Trajectories: {len(trajectories)}. Current frame delay = {current_time-frame.time}s (trajectories: {current_time - start_time}s)")
+            if self.config.bypass_prediction:
+                self.trajectory_socket.send_string(json.dumps(trajectories))
+            else:
                 self.trajectory_socket.send(pickle.dumps(frame))
+                
             # self.trajectory_socket.send_string(json.dumps(trajectories))
             # provide a {ID: {id: ID, history: [[x,y],[x,y],...]}}
             # TODO: provide a track object that actually keeps history (unlike tracker)
@@ -154,8 +212,16 @@ class Tracker:
                     
         logger.info('Stopping')
 
+    def _yolov8_track(self, img) -> [Detection]:
+        results: [YOLOResult] = self.model.track(img, persist=True)
+        return [Detection(track_id, *bbox) for bbox, track_id in zip(results[0].boxes.xywh.cpu(), results[0].boxes.id.int().cpu().tolist())]
         
-    def detect_persons(self, frame) -> Detections:
+    def _resnet_track(self, img) -> [Detection]:
+        detections = self._resnet_detect_persons(img)
+        tracks: [DeepsortTrack] = self.mot_tracker.update_tracks(detections, frame=img)
+        return [Detection.from_deepsort(t) for t in tracks]
+
+    def _resnet_detect_persons(self, frame) -> Detections:
         t = torch.from_numpy(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
         # change axes of image loaded image to be compatilbe with torch.io.read_image (which has C,W,H format instead of W,H,C)
         t = t.permute(2, 0, 1)