bout right
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@@ -3,3 +3,4 @@
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*.jsonl filter=lfs diff=lfs merge=lfs -text
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*.png filter=lfs diff=lfs merge=lfs -text
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*.jpg filter=lfs diff=lfs merge=lfs -text
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*.db filter=lfs diff=lfs merge=lfs -text
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@@ -8,5 +8,3 @@ wheels/
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# Virtual environments
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.venv
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Group_project_*
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Submodule
+1
Submodule SmokeDetectionApp added at f20e9a7c76.
@@ -0,0 +1,18 @@
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"""Database abstraction layer.
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Provides a Repository protocol and concrete implementations for SQLite and MySQL.
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The server doesn't care which one it talks to.
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"""
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from db.repository import Repository
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from db.sqlite import SQLiteRepository
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__all__ = ["Repository", "SQLiteRepository"]
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# Optional MySQL import (requires mysql-connector-python)
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try:
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from db.mysql import MySQLRepository
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__all__.append("MySQLRepository")
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except ImportError:
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pass
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+135
@@ -0,0 +1,135 @@
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"""MySQL implementation of the Repository."""
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import os
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from typing import Optional
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import mysql.connector # type: ignore[import-untyped]
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from db.repository import DetectionRecord, User
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class MySQLRepository:
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"""MySQL-backed repository. Needs a running MySQL server + .env config."""
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def __init__(
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self,
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user: Optional[str] = None,
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password: Optional[str] = None,
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host: Optional[str] = None,
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database: Optional[str] = None,
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):
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self.config = {
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"user": user or os.getenv("DB_USER", "smoke_admin"),
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"password": password or os.getenv("DB_PASSWORD", "123456"),
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"host": host or os.getenv("DB_HOST", "localhost"),
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"database": database or os.getenv("DB_NAME", "smoke_detection"),
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}
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def _connect(self):
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return mysql.connector.connect(**self.config)
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def initialize(self) -> None:
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conn = self._connect()
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cursor = conn.cursor()
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cursor.execute(
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"""CREATE TABLE IF NOT EXISTS users (
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id INT AUTO_INCREMENT PRIMARY KEY,
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username VARCHAR(50) UNIQUE NOT NULL,
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password VARCHAR(255) NOT NULL
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)"""
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)
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cursor.execute(
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"""CREATE TABLE IF NOT EXISTS detections (
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id INT AUTO_INCREMENT PRIMARY KEY,
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user_id INT,
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image_path VARCHAR(255) NOT NULL,
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confidence FLOAT,
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timestamp TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
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camera_source VARCHAR(50) DEFAULT 'Laptop Webcam',
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FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE CASCADE
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)"""
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)
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cursor.execute(
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"INSERT IGNORE INTO users (username, password) VALUES ('admin', '123456')"
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)
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conn.commit()
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conn.close()
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# --- Users ---
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def get_user_by_username(self, username: str) -> Optional[User]:
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conn = self._connect()
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cursor = conn.cursor(dictionary=True)
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cursor.execute("SELECT * FROM users WHERE username = %s", (username,))
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row = cursor.fetchone()
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conn.close()
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return User(**row) if row else None
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def get_user_by_credentials(self, username: str, password: str) -> Optional[User]:
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conn = self._connect()
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cursor = conn.cursor(dictionary=True)
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cursor.execute(
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"SELECT * FROM users WHERE username = %s AND password = %s",
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(username, password),
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)
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row = cursor.fetchone()
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conn.close()
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return User(**row) if row else None
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def create_user(self, username: str, password: str) -> int:
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conn = self._connect()
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cursor = conn.cursor()
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cursor.execute(
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"INSERT INTO users (username, password) VALUES (%s, %s)",
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(username, password),
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)
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conn.commit()
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new_id = cursor.lastrowid
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conn.close()
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return new_id # type: ignore[return-value]
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# --- Detections ---
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def save_detection(
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self,
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user_id: int,
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image_path: str,
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confidence: float,
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camera_source: str = "Laptop Webcam",
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) -> int:
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conn = self._connect()
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cursor = conn.cursor()
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cursor.execute(
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"INSERT INTO detections (user_id, image_path, confidence, camera_source) VALUES (%s, %s, %s, %s)",
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(user_id, image_path, confidence, camera_source),
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)
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conn.commit()
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new_id = cursor.lastrowid
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conn.close()
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return new_id # type: ignore[return-value]
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def get_detections(self, user_id: Optional[int] = None) -> list[DetectionRecord]:
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conn = self._connect()
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cursor = conn.cursor(dictionary=True)
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if user_id is not None:
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cursor.execute(
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"SELECT * FROM detections WHERE user_id = %s ORDER BY timestamp DESC",
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(user_id,),
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)
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else:
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cursor.execute("SELECT * FROM detections ORDER BY timestamp DESC")
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rows = cursor.fetchall()
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conn.close()
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return [DetectionRecord(**r) for r in rows]
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def clear_detections(self, user_id: int) -> int:
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conn = self._connect()
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cursor = conn.cursor()
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cursor.execute("DELETE FROM detections WHERE user_id = %s", (user_id,))
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conn.commit()
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count = cursor.rowcount
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conn.close()
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return count
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def close(self) -> None:
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pass # MySQL uses per-call connections
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@@ -0,0 +1,68 @@
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"""Repository protocol - the interface all DB backends must implement."""
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from dataclasses import dataclass
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from typing import Optional, Protocol, runtime_checkable
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@dataclass
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class User:
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id: int
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username: str
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password: str # plaintext for now (legacy compat) - hash this later
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@dataclass
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class DetectionRecord:
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id: int
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user_id: int
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image_path: str
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confidence: float
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timestamp: str
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camera_source: str
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@runtime_checkable
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class Repository(Protocol):
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"""Database operations for the smoking detection server."""
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def initialize(self) -> None:
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"""Create tables if they don't exist."""
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...
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# --- Users ---
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def get_user_by_username(self, username: str) -> Optional[User]:
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"""Find a user by username. Returns None if not found."""
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...
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def get_user_by_credentials(self, username: str, password: str) -> Optional[User]:
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"""Find a user by username + password. Returns None if invalid."""
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...
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def create_user(self, username: str, password: str) -> int:
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"""Create a new user. Returns the new user ID."""
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...
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# --- Detections ---
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def save_detection(
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self,
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user_id: int,
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image_path: str,
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confidence: float,
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camera_source: str = "Laptop Webcam",
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) -> int:
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"""Save a detection record. Returns the new record ID."""
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...
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def get_detections(self, user_id: Optional[int] = None) -> list[DetectionRecord]:
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"""Get detection history, optionally filtered by user. Newest first."""
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...
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def clear_detections(self, user_id: int) -> int:
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"""Delete all detections for a user. Returns number of rows deleted."""
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...
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def close(self) -> None:
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"""Close the database connection."""
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...
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+121
@@ -0,0 +1,121 @@
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"""SQLite implementation of the Repository."""
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import sqlite3
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from pathlib import Path
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from typing import Optional
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from db.repository import DetectionRecord, User
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# Schema that works with SQLite (no MySQL-specific syntax)
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SCHEMA = """\
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CREATE TABLE IF NOT EXISTS users (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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username TEXT UNIQUE NOT NULL,
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password TEXT NOT NULL
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);
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CREATE TABLE IF NOT EXISTS detections (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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user_id INTEGER,
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image_path TEXT NOT NULL,
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confidence REAL,
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timestamp TEXT DEFAULT (datetime('now', 'localtime')),
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camera_source TEXT DEFAULT 'Laptop Webcam',
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FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE CASCADE
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);
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INSERT OR IGNORE INTO users (username, password) VALUES ('admin', '123456');
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"""
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class SQLiteRepository:
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"""SQLite-backed repository. Zero setup, file-based."""
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def __init__(self, db_path: str | Path = "data/smoke.db"):
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self.db_path = Path(db_path)
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self.db_path.parent.mkdir(parents=True, exist_ok=True)
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self._conn: Optional[sqlite3.Connection] = None
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def _get_conn(self) -> sqlite3.Connection:
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if self._conn is None:
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self._conn = sqlite3.connect(str(self.db_path), check_same_thread=False)
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self._conn.row_factory = sqlite3.Row
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self._conn.execute("PRAGMA journal_mode=WAL")
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self._conn.execute("PRAGMA foreign_keys=ON")
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return self._conn
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def initialize(self) -> None:
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conn = self._get_conn()
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conn.executescript(SCHEMA)
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conn.commit()
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# --- Users ---
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def get_user_by_username(self, username: str) -> Optional[User]:
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row = (
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self._get_conn()
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.execute("SELECT * FROM users WHERE username = ?", (username,))
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.fetchone()
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)
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return User(**dict(row)) if row else None
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def get_user_by_credentials(self, username: str, password: str) -> Optional[User]:
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row = (
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self._get_conn()
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.execute(
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"SELECT * FROM users WHERE username = ? AND password = ?",
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(username, password),
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)
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.fetchone()
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)
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return User(**dict(row)) if row else None
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def create_user(self, username: str, password: str) -> int:
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conn = self._get_conn()
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cursor = conn.execute(
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"INSERT INTO users (username, password) VALUES (?, ?)",
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(username, password),
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)
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conn.commit()
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return cursor.lastrowid # type: ignore[return-value]
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# --- Detections ---
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def save_detection(
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self,
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user_id: int,
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image_path: str,
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confidence: float,
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camera_source: str = "Laptop Webcam",
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) -> int:
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conn = self._get_conn()
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cursor = conn.execute(
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"INSERT INTO detections (user_id, image_path, confidence, camera_source) VALUES (?, ?, ?, ?)",
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(user_id, image_path, confidence, camera_source),
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)
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conn.commit()
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return cursor.lastrowid # type: ignore[return-value]
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def get_detections(self, user_id: Optional[int] = None) -> list[DetectionRecord]:
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conn = self._get_conn()
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if user_id is not None:
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rows = conn.execute(
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"SELECT * FROM detections WHERE user_id = ? ORDER BY timestamp DESC",
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(user_id,),
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).fetchall()
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else:
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rows = conn.execute(
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"SELECT * FROM detections ORDER BY timestamp DESC"
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).fetchall()
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return [DetectionRecord(**dict(r)) for r in rows]
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def clear_detections(self, user_id: int) -> int:
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conn = self._get_conn()
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cursor = conn.execute("DELETE FROM detections WHERE user_id = ?", (user_id,))
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conn.commit()
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return cursor.rowcount
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def close(self) -> None:
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if self._conn:
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self._conn.close()
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self._conn = None
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@@ -1,6 +1,7 @@
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"""Sinks for pipeline output handling."""
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from pipeline.sinks.alerts import FileAlertStore
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from pipeline.sinks.database import DatabaseSink
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from pipeline.sinks.display import WindowDisplaySink
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from pipeline.sinks.events import SmartEventSink
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from pipeline.sinks.metrics import MetricsSink
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@@ -8,6 +9,7 @@ from pipeline.sinks.screenshots import ScreenshotSink
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from pipeline.sinks.video import VideoFileStore
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__all__ = [
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"DatabaseSink",
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"FileAlertStore",
|
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"MetricsSink",
|
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"ScreenshotSink",
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@@ -0,0 +1,74 @@
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"""Database sink - saves detection alerts to the database."""
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|
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import logging
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import time
|
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from pathlib import Path
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import cv2
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from db.repository import Repository
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from pipeline.ops.drawing import draw_alert_banner, draw_detections
|
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from pipeline.types import Frame
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|
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logger = logging.getLogger(__name__)
|
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|
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class DatabaseSink:
|
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"""
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Pipeline sink that saves smoking alerts to a database.
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|
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On ticket (alert), saves an annotated screenshot and inserts a detection record.
|
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"""
|
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|
||||
def __init__(
|
||||
self,
|
||||
db: Repository,
|
||||
user_id: int = 1,
|
||||
image_dir: str = "static/alerts",
|
||||
camera_source: str = "Pipeline",
|
||||
):
|
||||
self.db = db
|
||||
self.user_id = user_id
|
||||
self.camera_source = camera_source
|
||||
self.image_dir = Path(image_dir)
|
||||
self.image_dir.mkdir(parents=True, exist_ok=True)
|
||||
self.count = 0
|
||||
|
||||
logger.info("DatabaseSink initialized (user_id=%d, dir=%s)", user_id, image_dir)
|
||||
|
||||
def handle(self, frame: Frame):
|
||||
if not frame.ticket:
|
||||
return
|
||||
|
||||
self.count += 1
|
||||
ticket = frame.ticket
|
||||
|
||||
# Save annotated image
|
||||
filename = f"alert_{int(time.time())}_{self.count}.jpg"
|
||||
filepath = self.image_dir / filename
|
||||
|
||||
img = frame.data.copy()
|
||||
draw_detections(img, frame.detections)
|
||||
draw_alert_banner(img, f"SMOKING {ticket.confidence:.0%}")
|
||||
cv2.imwrite(str(filepath), img)
|
||||
|
||||
# Insert into database
|
||||
web_path = f"/static/alerts/{filename}"
|
||||
try:
|
||||
self.db.save_detection(
|
||||
user_id=self.user_id,
|
||||
image_path=web_path,
|
||||
confidence=ticket.confidence,
|
||||
camera_source=self.camera_source,
|
||||
)
|
||||
logger.info(
|
||||
"Alert #%d saved to DB: %s (%.2f)",
|
||||
self.count,
|
||||
filename,
|
||||
ticket.confidence,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error("Failed to save alert to DB: %s", e)
|
||||
|
||||
def close(self):
|
||||
pass # DB connection is managed by the repository
|
||||
@@ -5,11 +5,16 @@ description = "Add your description here"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.13"
|
||||
dependencies = [
|
||||
"dotenv>=0.9.9",
|
||||
"fastapi>=0.133.0",
|
||||
"mysql-connector-python>=9.6.0",
|
||||
"numpy>=2.4.0",
|
||||
"opencv-python>=4.11.0.86",
|
||||
"python-dotenv>=1.2.1",
|
||||
"torch>=2.9.1",
|
||||
"torchvision>=0.24.1",
|
||||
"ultralytics>=8.3.248",
|
||||
"uvicorn>=0.41.0",
|
||||
]
|
||||
|
||||
[[tool.uv.index]]
|
||||
|
||||
@@ -0,0 +1,308 @@
|
||||
"""
|
||||
Smoking Detection Server
|
||||
========================
|
||||
|
||||
FastAPI server that runs the full detection pipeline on a live webcam feed
|
||||
and exposes REST endpoints for the frontend (auth, history, video stream).
|
||||
|
||||
Usage:
|
||||
uvicorn server:app --host 0.0.0.0 --port 8000
|
||||
python server.py # dev mode
|
||||
python server.py --staged # use stage-based pipeline
|
||||
python server.py --source rtsp://... # RTSP camera
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import logging
|
||||
import os
|
||||
import threading
|
||||
import time
|
||||
from contextlib import asynccontextmanager
|
||||
from pathlib import Path
|
||||
|
||||
import cv2
|
||||
from fastapi import FastAPI, Form, Response
|
||||
from fastapi.responses import StreamingResponse
|
||||
from fastapi.staticfiles import StaticFiles
|
||||
|
||||
from db import SQLiteRepository
|
||||
from db.repository import Repository
|
||||
from pipeline.config import PipelineConfig
|
||||
from pipeline.core import SmokingDetectionPipeline
|
||||
from pipeline.models import YoloCigaretteDetector, YoloClassifier, YoloPersonDetector
|
||||
from pipeline.protocols import Sink
|
||||
from pipeline.sinks import DatabaseSink, FileAlertStore, MetricsSink
|
||||
from pipeline.sources.stream import ThreadedStreamSource
|
||||
from pipeline.staged_core import StageBasedPipeline
|
||||
from pipeline.types import Frame
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Global state (set during lifespan)
|
||||
# ---------------------------------------------------------------------------
|
||||
db: Repository = SQLiteRepository() # default: data/smoke.db
|
||||
pipeline = None # set at startup
|
||||
source: ThreadedStreamSource | None = None # set at startup
|
||||
live_frame: Frame | None = None # latest frame for MJPEG / snapshot
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Sink that exposes frames to the web layer
|
||||
# ---------------------------------------------------------------------------
|
||||
class LiveFrameSink:
|
||||
"""Captures the latest frame so API endpoints can stream it."""
|
||||
|
||||
def handle(self, frame: Frame):
|
||||
global live_frame
|
||||
live_frame = frame
|
||||
|
||||
def close(self):
|
||||
pass
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Pipeline runner (background thread)
|
||||
# ---------------------------------------------------------------------------
|
||||
def _run_pipeline():
|
||||
"""Blocking call: runs in a daemon thread."""
|
||||
assert pipeline is not None and source is not None
|
||||
try:
|
||||
pipeline.process_stream(source)
|
||||
except Exception: # noqa: BLE001
|
||||
logger.exception("Pipeline crashed")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# CLI args (parsed before uvicorn when run as __main__)
|
||||
# ---------------------------------------------------------------------------
|
||||
def parse_args():
|
||||
p = argparse.ArgumentParser(description="Smoking Detection Server")
|
||||
p.add_argument(
|
||||
"--source", type=str, default="0", help="Webcam index or RTSP URL (default: 0)"
|
||||
)
|
||||
p.add_argument("--person-model", default="models/human-det-best.pt")
|
||||
p.add_argument("--cig-model", default="models/cig-det-best.pt")
|
||||
p.add_argument("--verify-model", default="models/cig-cls-best.pt")
|
||||
p.add_argument("--staged", action="store_true", help="Use stage-based pipeline")
|
||||
p.add_argument("--vlm", action="store_true")
|
||||
p.add_argument("--vlm-key", default=None)
|
||||
p.add_argument("--vlm-provider", default="openai", choices=["openai", "anthropic"])
|
||||
p.add_argument("--vlm-model", default="gpt-4-vision-preview")
|
||||
p.add_argument("--host", default="0.0.0.0")
|
||||
p.add_argument("--port", type=int, default=8000)
|
||||
p.add_argument("--debug", action="store_true")
|
||||
return p.parse_args()
|
||||
|
||||
|
||||
# Module-level defaults (overridden by __main__ block or env)
|
||||
_args = argparse.Namespace(
|
||||
source=os.environ.get("CAMERA_SOURCE", "0"),
|
||||
person_model=os.environ.get("PERSON_MODEL", "models/human-det-best.pt"),
|
||||
cig_model=os.environ.get("CIG_MODEL", "models/cig-det-best.pt"),
|
||||
verify_model=os.environ.get("VERIFY_MODEL", "models/cig-cls-best.pt"),
|
||||
staged=os.environ.get("STAGED", "").lower() in ("1", "true", "yes"),
|
||||
vlm=os.environ.get("USE_VLM", "").lower() in ("1", "true", "yes"),
|
||||
vlm_key=os.environ.get("VLM_API_KEY"),
|
||||
vlm_provider=os.environ.get("VLM_PROVIDER", "openai"),
|
||||
vlm_model=os.environ.get("VLM_MODEL", "gpt-4-vision-preview"),
|
||||
debug=False,
|
||||
)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Lifespan – startup & shutdown
|
||||
# ---------------------------------------------------------------------------
|
||||
@asynccontextmanager
|
||||
async def app_lifespan(_app: FastAPI):
|
||||
global pipeline, source # noqa: PLW0603
|
||||
|
||||
logging.basicConfig(
|
||||
level=logging.DEBUG if _args.debug else logging.INFO,
|
||||
format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
|
||||
datefmt="%H:%M:%S",
|
||||
)
|
||||
logging.getLogger("ultralytics").setLevel(logging.WARNING)
|
||||
|
||||
# 1. Database
|
||||
logger.info("Initializing database...")
|
||||
db.initialize()
|
||||
|
||||
# 2. Models
|
||||
logger.info("Loading models...")
|
||||
person_model = YoloPersonDetector(_args.person_model)
|
||||
cig_model = YoloCigaretteDetector(_args.cig_model)
|
||||
verifier = YoloClassifier(_args.verify_model)
|
||||
logger.info("Models loaded.")
|
||||
|
||||
# 3. Source (webcam / RTSP)
|
||||
cam = int(_args.source) if _args.source.isdigit() else _args.source
|
||||
source = ThreadedStreamSource(cam)
|
||||
logger.info("Camera source ready: %s (%.1f FPS)", _args.source, source.fps)
|
||||
|
||||
# 4. Sinks
|
||||
sinks: list[Sink] = [
|
||||
LiveFrameSink(),
|
||||
DatabaseSink(db, image_dir="static/alerts"),
|
||||
MetricsSink(log_interval=200),
|
||||
FileAlertStore("alerts.jsonl"),
|
||||
]
|
||||
|
||||
# 5. Pipeline config
|
||||
config = PipelineConfig(
|
||||
idle_interval=0.5,
|
||||
active_interval=0.0,
|
||||
cooldown_frames=int(source.fps * 2),
|
||||
)
|
||||
|
||||
# 6. Build pipeline
|
||||
if _args.staged or _args.vlm:
|
||||
vlm_key = _args.vlm_key or os.environ.get(
|
||||
"OPENAI_API_KEY" if _args.vlm_provider == "openai" else "ANTHROPIC_API_KEY"
|
||||
)
|
||||
pipeline = StageBasedPipeline(
|
||||
person_model=person_model,
|
||||
cigarette_model=cig_model,
|
||||
verifier_model=verifier,
|
||||
vlm_api_key=vlm_key if _args.vlm else None,
|
||||
vlm_provider=_args.vlm_provider,
|
||||
vlm_model=_args.vlm_model,
|
||||
use_vlm=_args.vlm,
|
||||
sinks=sinks,
|
||||
config=config,
|
||||
)
|
||||
else:
|
||||
pipeline = SmokingDetectionPipeline(
|
||||
person_model=person_model,
|
||||
cigarette_model=cig_model,
|
||||
verifier_model=verifier,
|
||||
sinks=sinks,
|
||||
config=config,
|
||||
)
|
||||
|
||||
# 7. Launch pipeline in background thread
|
||||
t = threading.Thread(target=_run_pipeline, daemon=True, name="pipeline")
|
||||
t.start()
|
||||
logger.info("Pipeline running in background.")
|
||||
|
||||
yield # --- app serves requests ---
|
||||
|
||||
# Shutdown
|
||||
logger.info("Shutting down...")
|
||||
source.stop()
|
||||
for s in sinks:
|
||||
s.close()
|
||||
db.close()
|
||||
logger.info("Goodbye.")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# FastAPI app
|
||||
# ---------------------------------------------------------------------------
|
||||
app = FastAPI(title="Smoking Detection", lifespan=app_lifespan) # type: ignore
|
||||
|
||||
# Serve static assets (alert images, CSS/JS, etc.)
|
||||
Path("static/alerts").mkdir(parents=True, exist_ok=True)
|
||||
app.mount("/static", StaticFiles(directory="static"), name="static")
|
||||
|
||||
|
||||
# -- Auth ------------------------------------------------------------------
|
||||
|
||||
|
||||
@app.post("/register")
|
||||
def register(username: str = Form(...), password: str = Form(...)):
|
||||
try:
|
||||
if db.get_user_by_username(username):
|
||||
return {"status": "fail", "message": "Username already taken"}
|
||||
new_id = db.create_user(username, password)
|
||||
return {"status": "success", "user_id": new_id, "message": "Account created"}
|
||||
except Exception as e:
|
||||
return {"status": "error", "message": str(e)}
|
||||
|
||||
|
||||
@app.post("/login")
|
||||
def login(username: str = Form(...), password: str = Form(...)):
|
||||
try:
|
||||
user = db.get_user_by_credentials(username, password)
|
||||
if user:
|
||||
return {"status": "success", "user_id": user.id, "username": user.username}
|
||||
return {"status": "fail", "message": "Invalid username or password"}
|
||||
except Exception as e:
|
||||
return {"status": "error", "message": str(e)}
|
||||
|
||||
|
||||
# -- Detection history -----------------------------------------------------
|
||||
|
||||
|
||||
@app.get("/history")
|
||||
def get_history(user_id: int):
|
||||
try:
|
||||
records = db.get_detections(user_id)
|
||||
return [
|
||||
{
|
||||
"id": r.id,
|
||||
"user_id": r.user_id,
|
||||
"image_path": r.image_path,
|
||||
"confidence": r.confidence,
|
||||
"timestamp": r.timestamp,
|
||||
"camera_source": r.camera_source,
|
||||
}
|
||||
for r in records
|
||||
]
|
||||
except Exception:
|
||||
return []
|
||||
|
||||
|
||||
@app.post("/clear_history")
|
||||
def clear_history(user_id: int = Form(...)):
|
||||
try:
|
||||
deleted = db.clear_detections(user_id)
|
||||
logger.info("Cleared %d records for user %d", deleted, user_id)
|
||||
return {"status": "success", "message": "History cleared"}
|
||||
except Exception as e:
|
||||
return {"status": "error", "message": str(e)}
|
||||
|
||||
|
||||
# -- Video / Snapshot ------------------------------------------------------
|
||||
|
||||
|
||||
@app.get("/snapshot")
|
||||
def snapshot():
|
||||
"""Return the latest frame as a JPEG."""
|
||||
if live_frame is not None:
|
||||
_, jpg = cv2.imencode(".jpg", live_frame.data)
|
||||
return Response(content=jpg.tobytes(), media_type="image/jpeg")
|
||||
return Response(status_code=404)
|
||||
|
||||
|
||||
@app.get("/video_feed")
|
||||
def video_feed():
|
||||
"""MJPEG stream – drop into an <img> tag."""
|
||||
|
||||
def generate():
|
||||
while True:
|
||||
if live_frame is not None:
|
||||
from pipeline.ops.drawing import draw_detections
|
||||
|
||||
img = live_frame.data.copy()
|
||||
draw_detections(img, live_frame.detections)
|
||||
_, jpg = cv2.imencode(".jpg", img)
|
||||
yield (
|
||||
b"--frame\r\n"
|
||||
b"Content-Type: image/jpeg\r\n\r\n" + jpg.tobytes() + b"\r\n"
|
||||
)
|
||||
time.sleep(0.033) # ~30 FPS cap
|
||||
|
||||
return StreamingResponse(
|
||||
generate(), media_type="multipart/x-mixed-replace;boundary=frame"
|
||||
)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Entry-point
|
||||
# ---------------------------------------------------------------------------
|
||||
if __name__ == "__main__":
|
||||
import uvicorn
|
||||
|
||||
_args = parse_args()
|
||||
uvicorn.run(app, host=_args.host, port=_args.port)
|
||||
Reference in new issue
Block a user