wsy182
4485cbf702
Split monolithic files into focused modules: - app/core: settings, logging, lifecycle - app/signaling: websocket server, ICE parser, message models - app/webrtc: peer session, video receiver, frame source - app/vision: pose landmarker wrapper, model config, pose types - app/exercises/dead_bug: detector, metrics, rules, state machine, types - app/rendering: skeleton renderer, status overlay, window display - app/audio: rep announcer - app/diagnostics: perf timer, crash handler - configs: environment-based settings - tests: unit tests for rules, state machine, ICE parser - run.py: entry point
47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
from __future__ import annotations
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import cv2
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import numpy as np
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from app.exercises.dead_bug.types import DeadBugResult, Point
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from app.vision.pose_types import _POSE_CONNECTIONS
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def draw_landmarks(
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image: np.ndarray,
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landmarks: list[Point],
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required_indices: tuple[int, ...],
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connections: tuple[tuple[int, int], ...] | None = None,
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visibility_threshold: float = 0.45,
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line_color: tuple[int, int, int] = (65, 180, 255),
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point_color: tuple[int, int, int] = (80, 255, 120),
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line_thickness: int = 2,
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point_radius: int = 4,
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) -> None:
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if connections is None:
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connections = _POSE_CONNECTIONS
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h, w = image.shape[:2]
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for start, end in connections:
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if start >= len(landmarks) or end >= len(landmarks):
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continue
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p1 = landmarks[start]
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p2 = landmarks[end]
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if p1.visibility < visibility_threshold or p2.visibility < visibility_threshold:
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continue
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cv2.line(
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image,
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(int(p1.x * w), int(p1.y * h)),
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(int(p2.x * w), int(p2.y * h)),
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line_color,
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line_thickness,
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)
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for idx in required_indices:
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if idx >= len(landmarks):
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continue
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p = landmarks[idx]
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if p.visibility >= visibility_threshold:
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cv2.circle(image, (int(p.x * w), int(p.y * h)), point_radius, point_color, -1)
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