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201b13c fb4ca0a 201b13c fb4ca0a c36c5e5 fb4ca0a a3abb2d fb4ca0a 201b13c c36c5e5 201b13c a3abb2d 201b13c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 | import os
from dataclasses import dataclass, field
from pathlib import Path
from dotenv import load_dotenv
BASE_DIR = Path(__file__).resolve().parent.parent
load_dotenv(BASE_DIR / ".env")
def _resolve_path(env_name: str, default_relative_path: str) -> str:
raw_value = os.getenv(env_name)
path = Path(raw_value) if raw_value else BASE_DIR / default_relative_path
return str(path if path.is_absolute() else (BASE_DIR / path).resolve())
def _resolve_optional_path(
env_name: str,
default_relative_path: str | None = None,
) -> str | None:
raw_value = os.getenv(env_name)
if raw_value:
path = Path(raw_value)
return str(path if path.is_absolute() else (BASE_DIR / path).resolve())
if not default_relative_path:
return None
default_path = (BASE_DIR / default_relative_path).resolve()
if default_path.exists():
return str(default_path)
return None
def _parse_origins() -> tuple[str, ...]:
raw_origins = os.getenv(
"CORS_ORIGINS",
"http://127.0.0.1:5173,http://localhost:5173",
)
return tuple(
origin.strip()
for origin in raw_origins.split(",")
if origin.strip()
)
def _parse_bool(name: str, default: bool) -> bool:
raw_value = os.getenv(name)
if raw_value is None:
return default
return raw_value.strip().lower() in {"1", "true", "yes", "on"}
@dataclass(frozen=True)
class Settings:
"""
Central configuration for the inspection system.
"""
# -----------------------------
# PATHS
# -----------------------------
BASE_DIR: str = str(BASE_DIR)
MODEL_PATH: str = field(
default_factory=lambda: _resolve_path("MODEL_PATH", "models/steel_inspection.pt")
)
IMAGE_FOLDER: str = field(
default_factory=lambda: _resolve_path("IMAGE_FOLDER", "test_images")
)
REPORT_FOLDER: str = field(
default_factory=lambda: _resolve_path("REPORT_FOLDER", "reports")
)
FRONTEND_DIST: str = field(
default_factory=lambda: _resolve_path("FRONTEND_DIST", "dashboard/dist")
)
# -----------------------------
# DEMO / SIMULATION SETTINGS
# -----------------------------
IMAGE_REPEAT: int = field(default_factory=lambda: int(os.getenv("IMAGE_REPEAT", "5")))
BLANK_FRAMES: int = field(default_factory=lambda: int(os.getenv("BLANK_FRAMES", "3")))
# -----------------------------
# TRACKING / LIFECYCLE
# -----------------------------
MAX_MISSING_FRAMES: int = field(
default_factory=lambda: int(os.getenv("MAX_MISSING_FRAMES", "5"))
)
# -----------------------------
# MODEL / INFERENCE SETTINGS
# -----------------------------
CONF_THRESHOLD: float = field(default_factory=lambda: float(os.getenv("CONF_THRESHOLD", "0.20")))
SECONDARY_CONF_THRESHOLD: float = field(
default_factory=lambda: float(os.getenv("SECONDARY_CONF_THRESHOLD", "0.25"))
)
IMAGE_SIZE: int = field(default_factory=lambda: int(os.getenv("IMAGE_SIZE", "896")))
MIN_DEFECT_AREA: int = field(default_factory=lambda: int(os.getenv("MIN_DEFECT_AREA", "120")))
MAX_AREA_RATIO: float = field(default_factory=lambda: float(os.getenv("MAX_AREA_RATIO", "0.12")))
SURFACE_GATE_ENABLED: bool = field(
default_factory=lambda: _parse_bool("SURFACE_GATE_ENABLED", False)
)
SURFACE_DETECTOR_PATH: str | None = field(
default_factory=lambda: _resolve_optional_path(
"SURFACE_DETECTOR_PATH",
"models/steel_surface_detector.pt",
)
)
SURFACE_DETECTOR_CLASS_NAME: str = field(
default_factory=lambda: os.getenv("SURFACE_DETECTOR_CLASS_NAME", "steel_surface")
)
SURFACE_DETECTOR_CONFIDENCE: float = field(
default_factory=lambda: float(os.getenv("SURFACE_DETECTOR_CONFIDENCE", "0.40"))
)
SURFACE_DETECTOR_MIN_AREA_RATIO: float = field(
default_factory=lambda: float(os.getenv("SURFACE_DETECTOR_MIN_AREA_RATIO", "0.12"))
)
SURFACE_DETECTOR_EXPAND_RATIO: float = field(
default_factory=lambda: float(os.getenv("SURFACE_DETECTOR_EXPAND_RATIO", "0.04"))
)
SURFACE_DETECTOR_IMAGE_SIZE: int = field(
default_factory=lambda: int(os.getenv("SURFACE_DETECTOR_IMAGE_SIZE", "640"))
)
SURFACE_CLASSIFIER_PATH: str | None = field(
default_factory=lambda: _resolve_optional_path(
"SURFACE_CLASSIFIER_PATH",
"models/steel_surface_classifier.pt",
)
)
SURFACE_CLASSIFIER_STEEL_LABEL: str = field(
default_factory=lambda: os.getenv("SURFACE_CLASSIFIER_STEEL_LABEL", "steel")
)
SURFACE_MIN_STEEL_CONFIDENCE: float = field(
default_factory=lambda: float(os.getenv("SURFACE_MIN_STEEL_CONFIDENCE", "0.55"))
)
SURFACE_GRAY_DELTA: int = field(
default_factory=lambda: int(os.getenv("SURFACE_GRAY_DELTA", "16"))
)
SURFACE_MIN_GRAY_RATIO: float = field(
default_factory=lambda: float(os.getenv("SURFACE_MIN_GRAY_RATIO", "0.72"))
)
SURFACE_LOW_SAT_PIXEL_THRESHOLD: int = field(
default_factory=lambda: int(os.getenv("SURFACE_LOW_SAT_PIXEL_THRESHOLD", "45"))
)
SURFACE_MIN_LOW_SAT_RATIO: float = field(
default_factory=lambda: float(os.getenv("SURFACE_MIN_LOW_SAT_RATIO", "0.78"))
)
SURFACE_MAX_MEAN_SATURATION: float = field(
default_factory=lambda: float(os.getenv("SURFACE_MAX_MEAN_SATURATION", "40"))
)
SURFACE_MAX_COLORFULNESS: float = field(
default_factory=lambda: float(os.getenv("SURFACE_MAX_COLORFULNESS", "24"))
)
SURFACE_MAX_SKIN_RATIO: float = field(
default_factory=lambda: float(os.getenv("SURFACE_MAX_SKIN_RATIO", "0.16"))
)
SURFACE_MIN_TEXTURE_VARIANCE: float = field(
default_factory=lambda: float(os.getenv("SURFACE_MIN_TEXTURE_VARIANCE", "80"))
)
# -----------------------------
# API / UI
# -----------------------------
CORS_ORIGINS: tuple[str, ...] = field(default_factory=_parse_origins)
REPORT_FETCH_LIMIT: int = field(
default_factory=lambda: int(os.getenv("REPORT_FETCH_LIMIT", "50"))
)
MAX_UPLOAD_SIZE_MB: int = field(
default_factory=lambda: int(os.getenv("MAX_UPLOAD_SIZE_MB", "8"))
)
WEBSOCKET_HEARTBEAT_SECONDS: int = field(
default_factory=lambda: int(os.getenv("WEBSOCKET_HEARTBEAT_SECONDS", "20"))
)
ENABLE_LLM_REPORTS: bool = field(
default_factory=lambda: _parse_bool("ENABLE_LLM_REPORTS", True)
)
LLM_PROVIDER: str = field(
default_factory=lambda: os.getenv("LLM_PROVIDER", "auto")
)
OLLAMA_BASE_URL: str = field(
default_factory=lambda: os.getenv("OLLAMA_BASE_URL", "http://127.0.0.1:11434")
)
OLLAMA_MODEL: str = field(
default_factory=lambda: os.getenv("OLLAMA_MODEL", "llama3")
)
OLLAMA_TIMEOUT_SECONDS: float = field(
default_factory=lambda: float(os.getenv("OLLAMA_TIMEOUT_SECONDS", "6"))
)
HF_TOKEN: str | None = field(default_factory=lambda: os.getenv("HF_TOKEN"))
HF_CHAT_MODEL: str = field(
default_factory=lambda: os.getenv("HF_CHAT_MODEL", "meta-llama/Llama-3.1-8B-Instruct:cerebras")
)
HF_ROUTER_BASE_URL: str = field(
default_factory=lambda: os.getenv("HF_ROUTER_BASE_URL", "https://router.huggingface.co/v1")
)
OPENROUTER_API_KEY: str | None = field(default_factory=lambda: os.getenv("OPENROUTER_API_KEY"))
OPENROUTER_MODEL: str = field(
default_factory=lambda: os.getenv("OPENROUTER_MODEL", "openrouter/free")
)
OPENROUTER_BASE_URL: str = field(
default_factory=lambda: os.getenv("OPENROUTER_BASE_URL", "https://openrouter.ai/api/v1")
)
# -----------------------------
# DATABASE
# -----------------------------
DATABASE_URL: str | None = field(default_factory=lambda: os.getenv("DATABASE_URL"))
@property
def max_upload_bytes(self) -> int:
return self.MAX_UPLOAD_SIZE_MB * 1024 * 1024
settings = Settings()
|