"""Centralized configuration for the navigation system."""
import os

# Model paths
YOLO_MODEL = os.environ.get("NAV_YOLO_MODEL", "yolov8n.pt")
POSE_MODEL = os.environ.get("NAV_POSE_MODEL", os.path.join(os.path.dirname(__file__), "pose_landmarker_heavy.task"))
# Depth model options: "small", "base", "v2-small", "v2-base"
# v2 models are more accurate. "small" variants are faster.
DEPTH_MODEL = os.environ.get("NAV_DEPTH_MODEL", "small")
DEPTH_INPUT_SIZE = int(os.environ.get("NAV_DEPTH_INPUT_SIZE", 384))  # resize before inference
DEVICE = os.environ.get("NAV_DEVICE", "cpu")

# Auto-detect GPU if not explicitly set
if "NAV_DEVICE" not in os.environ:
    try:
        import torch
        if torch.cuda.is_available():
            DEVICE = "cuda"
    except ImportError:
        pass

# Detection
YOLO_CONF = 0.25
OBSTACLE_CLASSES = {
    0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 5: 'bus', 7: 'truck',
    9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 13: 'bench',
    15: 'cat', 16: 'dog', 24: 'backpack', 25: 'umbrella', 28: 'suitcase',
    39: 'bottle', 56: 'chair', 57: 'sofa', 58: 'potted plant',
    59: 'bed', 60: 'table', 62: 'tv', 63: 'laptop',
    66: 'keyboard', 72: 'refrigerator', 73: 'book',
}

# Depth / slope
GROUND_RATIO = 0.55          # default ground region starts at 55% of frame height
SLOPE_MULTIPLIER = 20.0      # arctan scaling — calibrate on known slopes
SLOPE_CLAMP = 35.0           # max slope angle (degrees)
SLOPE_DEADZONE = 3.0         # angles below this → FLAT
SLOPE_SMOOTHING = 0.7        # EMA alpha for temporal smoothing (0=no smoothing, 1=full cache)

# Terrain roughness thresholds (std of ground depth)
TERRAIN_ROCKY_THRESH = 0.25
TERRAIN_ROUGH_THRESH = 0.15

# Pose landmark indices
LM = {
    'L_SHOULDER': 11, 'R_SHOULDER': 12,
    'L_HIP': 23, 'R_HIP': 24,
    'L_KNEE': 25, 'R_KNEE': 26,
    'L_ANKLE': 27, 'R_ANKLE': 28,
    'L_HEEL': 29, 'R_HEEL': 30,
    'L_FOOT': 31, 'R_FOOT': 32,
}
SKELETON_CONNS = [
    (11, 13), (13, 15), (12, 14), (14, 16), (11, 12), (11, 23), (12, 24), (23, 24),
    (23, 25), (25, 27), (27, 29), (27, 31), (29, 31),
    (24, 26), (26, 28), (28, 30), (28, 32), (30, 32),
]

# Risk thresholds
RISK_HIGH = 60
RISK_MEDIUM = 30
RISK_LOW = 10

# User mobility profiles: "default", "elderly", "athletic"
RISK_PROFILE = os.environ.get("NAV_RISK_PROFILE", "default")

# Voice throttle
VOICE_COOLDOWN_SEC = 2.5     # min seconds between repeated messages
VOICE_SLOPE_DELTA = 5.0      # slope must change by this much to re-announce

# Video processing
DEFAULT_SKIP_FRAMES = 2
DEFAULT_DEPTH_EVERY = 5