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
93 lines
3.1 KiB
Python
93 lines
3.1 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 Point
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def angle(a: Point, b: Point, c: Point) -> float:
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ba = np.array([a.x - b.x, a.y - b.y], dtype=np.float32)
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bc = np.array([c.x - b.x, c.y - b.y], dtype=np.float32)
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denom = float(np.linalg.norm(ba) * np.linalg.norm(bc))
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if denom == 0:
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return 0.0
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cos_value = float(np.dot(ba, bc) / denom)
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return float(np.degrees(np.arccos(np.clip(cos_value, -1.0, 1.0))))
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def distance(a: Point, b: Point) -> float:
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return float(np.hypot(a.x - b.x, a.y - b.y))
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def calculate_metrics(
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lm: list[Point],
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*,
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left_shoulder: int,
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right_shoulder: int,
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left_elbow: int,
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right_elbow: int,
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left_wrist: int,
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right_wrist: int,
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left_hip: int,
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right_hip: int,
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left_knee: int,
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right_knee: int,
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left_ankle: int,
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right_ankle: int,
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visibility_threshold: float = 0.45,
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) -> dict:
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left_elbow_angle = angle(lm[left_shoulder], lm[left_elbow], lm[left_wrist])
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right_elbow_angle = angle(lm[right_shoulder], lm[right_elbow], lm[right_wrist])
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left_knee_angle = angle(lm[left_hip], lm[left_knee], lm[left_ankle])
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right_knee_angle = angle(lm[right_hip], lm[right_knee], lm[right_ankle])
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shoulder_width = distance(lm[left_shoulder], lm[right_shoulder])
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hip_width = distance(lm[left_hip], lm[right_hip])
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scale = max(shoulder_width, hip_width, 0.08)
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left_arm_extended = (
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left_elbow_angle >= 145
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and distance(lm[left_shoulder], lm[left_wrist]) >= scale * 1.15
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and lm[left_wrist].y <= lm[left_shoulder].y + scale * 0.35
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)
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right_arm_extended = (
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right_elbow_angle >= 145
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and distance(lm[right_shoulder], lm[right_wrist]) >= scale * 1.15
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and lm[right_wrist].y <= lm[right_shoulder].y + scale * 0.35
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)
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left_leg_extended = (
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left_knee_angle >= 150
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and distance(lm[left_hip], lm[left_ankle]) >= scale * 1.55
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and lm[left_ankle].y >= lm[left_knee].y - scale * 0.2
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)
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right_leg_extended = (
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right_knee_angle >= 150
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and distance(lm[right_hip], lm[right_ankle]) >= scale * 1.55
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and lm[right_ankle].y >= lm[right_knee].y - scale * 0.2
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)
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feedback: list[str] = []
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if left_arm_extended and left_elbow_angle < 160:
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feedback.append("Straighten left arm")
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if right_arm_extended and right_elbow_angle < 160:
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feedback.append("Straighten right arm")
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if left_leg_extended and left_knee_angle < 165:
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feedback.append("Straighten left leg")
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if right_leg_extended and right_knee_angle < 165:
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feedback.append("Straighten right leg")
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return {
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"left_arm_extended": left_arm_extended,
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"right_arm_extended": right_arm_extended,
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"left_leg_extended": left_leg_extended,
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"right_leg_extended": right_leg_extended,
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"left_elbow_angle": left_elbow_angle,
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"right_elbow_angle": right_elbow_angle,
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"left_knee_angle": left_knee_angle,
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"right_knee_angle": right_knee_angle,
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"scale": scale,
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"feedback": feedback,
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}
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