diff --git a/Makefile b/Makefile new file mode 100644 index 0000000..390faa0 --- /dev/null +++ b/Makefile @@ -0,0 +1,20 @@ +POETRY = poetry run +SOURCEDIR = docs/source +BUILDDIR = docs/build +PACKAGEDIR = client + +.PHONY: docs docs-clean docs-live + +# Build documentation +docs: + $(POETRY) sphinx-build -a "$(SOURCEDIR)" "$(BUILDDIR)/html" + +# Remove documentation outputs +# This includes the api dir as it's autogenerated with sphinx-build +docs-clean: + rm -r "$(BUILDDIR)" "$(SOURCEDIR)/api" + +# Spin up a local server to serve documentation pages +# Auto-reloads when code changes in PACKAGEDIR are made +docs-live: + $(POETRY) sphinx-autobuild --open-browser --watch "$(PACKAGEDIR)" -a "$(SOURCEDIR)" "$(BUILDDIR)/html" diff --git a/README.md b/README.md index 4113c86..9539cfc 100644 --- a/README.md +++ b/README.md @@ -86,15 +86,13 @@ poetry run black client/models/pose_detection/classification.py ## Documentation -To build the docs locally, run from the root of the repo: - +We use [Sphinx](https://www.sphinx-doc.org/) for documentation. To view the documentation locally, run the following command: ```bash -poetry run sphinx-apidoc -f -o docs/source/generated client && -cd docs && -poetry run make html +make docs-live ``` +This spins up a local server which serves the documentation pages, and also hot-reloads and auto-rebuilds whenever code changes are made. -The documentation is generated automatically from the source code, so it isn't stored in the repo (hence why we need to run `sphinx-apidoc`). +You can build the documentation (without spinning up a server) with `make docs`, and clean the documentation output with `make docs-clean`. ## Downloading ML Models From top-level directory. diff --git a/client/models/pose_detection/camera.py b/client/models/pose_detection/camera.py index c2a5bae..c3c805a 100644 --- a/client/models/pose_detection/camera.py +++ b/client/models/pose_detection/camera.py @@ -10,8 +10,14 @@ def is_camera_aligned(pose_landmark_result: PoseLandmarkerResult) -> np.bool_: - """ - Returns whether the camera is aligned to capture the person's side view. + """Checks whether the camera is aligned to capture the person's side view. + + Args: + pose_landmarker_result: Landmarker result as returned by a + mediapipe.tasks.vision.PoseLandmarker + + Returns: + True if the camera is aligned, False otherwise """ landmarks: list[list[Landmark]] = pose_landmark_result.pose_world_landmarks diff --git a/client/models/pose_detection/classification.py b/client/models/pose_detection/classification.py index b9c2821..b056a6b 100644 --- a/client/models/pose_detection/classification.py +++ b/client/models/pose_detection/classification.py @@ -13,18 +13,25 @@ def posture_angle(p1: Landmark, p2: Landmark) -> np.float64: - """ - Returns the angle (in degrees) between P2 and P3, where P3 is a point on the - vertical axis of P1 (i.e. its x coordinate is the same as P1's), and is the "ideal" - location of the P2 landmark for good posture. + """Calculates the neck or torso posture angle (in degrees). + + In particular, this calculates the angle (in degrees) between p2 and p3, where p3 + is a point on the vertical axis of p1 (i.e. same x coordinate as p1), and + represents the "ideal" location of the p2 landmark for good posture. + + The y coordinate of p3 is irrelevant but for simplicity we set it to zero. + + For neck posture, take p1 to be the shoulder, p2 to be the ear. For torso posture, + take p1 to be the hip, p2 to be the shoulder. - The y coordinate of P3 is irrelevant but for simplicity we set it to zero. + REF: https://learnopencv.com/wp-content/uploads/2022/03/MediaPipe-pose-neckline-inclination.jpg - For a neck inclination calculation, take P1 to be the shoulder location and pivot - point, and P2 to be the ear location. + Parameters: + p1: Landmark for P1 as described above + p2: Landmark for P2 as described above - For a torso inclination calculation, take P1 to be the hip location and pivot - point, and P2 to be the hip location. + Returns: + Neck or torso posture angle (in degrees) """ x1, y1 = p1.x, p1.y x2, y2 = p2.x, p2.y @@ -33,13 +40,19 @@ def posture_angle(p1: Landmark, p2: Landmark) -> np.float64: def posture_classify(pose_landmark_result: PoseLandmarkerResult) -> np.bool_: - """ - Returns whether the pose in the image has good (True) or bad (False) posture. + """Classifies the pose in the image as either good or bad posture. Note: The camera should be aligned to capture the person's side view; the output may not be accurate otherwise. See `is_camera_aligned()`. REF: https://learnopencv.com/building-a-body-posture-analysis-system-using-mediapipe + + Parameters: + pose_landmarker_result: Landmarker result as returned by a + mediapipe.tasks.vision.PoseLandmarker + + Returns: + True if the pose has good posture, False otherwise """ landmarks: list[list[Landmark]] = pose_landmark_result.pose_world_landmarks diff --git a/client/models/pose_detection/landmarking.py b/client/models/pose_detection/landmarking.py index 0725eae..76c82b6 100644 --- a/client/models/pose_detection/landmarking.py +++ b/client/models/pose_detection/landmarking.py @@ -14,8 +14,10 @@ @dataclass class AnnotatedImage: - """Represents mutable annoted image through data attribute. Can be used to set annotated image - within a callback asynchronously without raising an error. + """Represents mutable annotated image through data attribute. + + Can be used to set annotated image within a callback asynchronously without raising + an error. """ data: Optional[np.ndarray] = None @@ -26,11 +28,11 @@ def draw_landmarks_on_image( ) -> np.ndarray: """ Args: - bgr_image (np.ndarray): CxWxH image array where channels are sorted in BGR. - detection_result (PoseLandmarkerResult): Landmarker result as returned by a - mediapipe.tasks.vision.PoseLandmarker + bgr_image: CxWxH image array where channels are sorted in BGR. + detection_result: Landmarker result as returned by a + mediapipe.tasks.vision.PoseLandmarker. Returns: - (np.ndarray): Image with landmarks annotated. + Image with landmarks annotated. """ pose_landmarks_list = detection_result.pose_landmarks annotated_image = np.copy(bgr_image) @@ -58,17 +60,17 @@ def display_landmarking( result: PoseLandmarkerResult, output_image: mp.Image, timestamp: int, - annotated_image=AnnotatedImage, + annotated_image: AnnotatedImage, ) -> None: """Mutates annotated image to contain visualization of detected landmarks. + Also prints debugging info to the standard output. Args: - result (PoseLandmarkerResult): Landmarker result as returned by a - mediapipe.tasks.vision.PoseLandmarker - output_image (mp.Image): Raw image used for landmarking. - timestamp (int): Video timestamp in milliseconds. - annotated_image (AnnotatedImage): Image to mutate. + result: Landmarker result as returned by a mediapipe.tasks.vision.PoseLandmarker + output_image: Raw image used for landmarking. + timestamp: Video timestamp in milliseconds. + annotated_image: Image to mutate. """ annotated_image.data = draw_landmarks_on_image(output_image.numpy_view(), result) print( diff --git a/client/models/pose_detection/routines.py b/client/models/pose_detection/routines.py index 246ec08..59e261f 100644 --- a/client/models/pose_detection/routines.py +++ b/client/models/pose_detection/routines.py @@ -38,8 +38,8 @@ def __init__( self.video_capture = cv2.VideoCapture(0) def track_posture(self) -> None: - """Get frame from video capture device and process with pose model, then posture algorithm. - Print debugging info and display landmark annotated frame. + """Get frame from video capture device and process with pose model, then posture + algorithm. Print debugging info and display landmark annotated frame. """ success, frame = self.video_capture.read() if not success: @@ -61,8 +61,9 @@ def __exit__(self, unused_exc_type, unused_exc_value, unused_traceback) -> None: def create_debug_posture_tracker() -> DebugPostureTracker: """Handles config of livestreamed input and model loading. + Returns: - (DebugPostureTracker): Tracker object which acts as context manager. + Tracker object which acts as context manager. """ annotated_image = AnnotatedImage() options = PoseLandmarkerOptions( diff --git a/docs/source/conf.py b/docs/source/conf.py index de31542..46dad33 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -3,6 +3,9 @@ # For the full list of built-in configuration values, see the documentation: # https://www.sphinx-doc.org/en/master/usage/configuration.html +import os +import sys + # -- Project information ----------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information @@ -15,20 +18,27 @@ # -- General configuration --------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration + +sys.path.insert(0, os.path.abspath("../..")) + extensions = [ "sphinx.ext.duration", - "sphinx.ext.autodoc", - "sphinx.ext.autosummary", "sphinx.ext.napoleon", + "sphinxcontrib.apidoc", ] templates_path = ["_templates"] exclude_patterns = [] +apidoc_module_dir = "../../client" +apidoc_output_dir = "api" + +napoleon_google_docstring = True +napoleon_numpy_docstring = False # -- Options for HTML output ------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output -html_theme = "alabaster" +html_theme = "piccolo_theme" html_static_path = ["_static"] diff --git a/docs/source/index.rst b/docs/source/index.rst index c845810..4e2af4a 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -17,4 +17,4 @@ Contents .. toctree:: - generated/modules + api/modules diff --git a/poetry.lock b/poetry.lock index 972c26f..107e3d4 100644 --- a/poetry.lock +++ b/poetry.lock @@ -22,6 +22,28 @@ files = [ {file = "alabaster-1.0.0.tar.gz", hash = "sha256:c00dca57bca26fa62a6d7d0a9fcce65f3e026e9bfe33e9c538fd3fbb2144fd9e"}, ] +[[package]] +name = "anyio" +version = "4.4.0" +description = "High level compatibility layer for multiple asynchronous event loop 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