from __future__ import annotations

import threading
import time
from typing import Any

import cv2
import numpy as np
from PySide6.QtCore import QThread, Signal, Slot

from app.detection import DetectionPipeline, DetectionResult


CV_CAP_PROPS = {
    "brightness": cv2.CAP_PROP_BRIGHTNESS,
    "contrast": cv2.CAP_PROP_CONTRAST,
    "saturation": cv2.CAP_PROP_SATURATION,
    "hue": cv2.CAP_PROP_HUE,
    "gain": cv2.CAP_PROP_GAIN,
    "exposure": cv2.CAP_PROP_EXPOSURE,
    "sharpness": cv2.CAP_PROP_SHARPNESS,
    "auto_exposure": cv2.CAP_PROP_AUTO_EXPOSURE,
    "focus": cv2.CAP_PROP_FOCUS,
    "auto_focus": cv2.CAP_PROP_AUTOFOCUS,
}


def backend_for_name(name: str) -> int:
    if name == "avfoundation":
        return cv2.CAP_AVFOUNDATION
    if name == "v4l2":
        return cv2.CAP_V4L2
    if name == "dshow":
        return cv2.CAP_DSHOW
    return cv2.CAP_ANY


class CameraWorker(QThread):
    frame_ready = Signal(object)
    detection_ready = Signal(object)
    camera_error = Signal(str)

    def __init__(self, config: dict[str, Any], app_config: Any) -> None:
        super().__init__()
        self.config = config
        self.app_config = app_config
        self.pipeline = DetectionPipeline(config, app_config)
        self._running = threading.Event()
        self._running.set()
        self._detecting = False
        self._accepted = False
        self._frame_count = 0
        self._capture: cv2.VideoCapture | None = None
        self._lock = threading.Lock()

    def stop(self) -> None:
        self._running.clear()

    @Slot()
    def start_detection(self) -> None:
        with self._lock:
            self._detecting = True
            self._accepted = False
            self._frame_count = 0

    @Slot()
    def accept_detection(self) -> None:
        with self._lock:
            self._detecting = False
            self._accepted = True

    @Slot(dict)
    def update_camera_config(self, camera_config: dict[str, Any]) -> None:
        with self._lock:
            self.config["camera"] = camera_config
            capture = self._capture
        if capture is not None:
            self._apply_camera_settings(capture)

    def run(self) -> None:
        camera_cfg = self.config["camera"]
        capture = cv2.VideoCapture(
            int(camera_cfg.get("index", 0)),
            backend_for_name(str(camera_cfg.get("backend", "auto"))),
        )
        self._capture = capture
        if not capture.isOpened():
            self.camera_error.emit("Nie mozna otworzyc kamery USB")
            return

        self._apply_camera_settings(capture)

        try:
            while self._running.is_set():
                ok, frame = capture.read()
                if not ok or frame is None:
                    self.camera_error.emit("Nie mozna odczytac klatki z kamery")
                    time.sleep(0.2)
                    continue

                self.frame_ready.emit(frame)
                self._maybe_detect(frame)
        finally:
            capture.release()
            self._capture = None

    def _apply_camera_settings(self, capture: cv2.VideoCapture) -> None:
        camera_cfg = self.config["camera"]
        capture.set(cv2.CAP_PROP_FRAME_WIDTH, int(camera_cfg.get("width", 1920)))
        capture.set(cv2.CAP_PROP_FRAME_HEIGHT, int(camera_cfg.get("height", 1080)))
        capture.set(cv2.CAP_PROP_FPS, int(camera_cfg.get("fps", 30)))

        for name, value in camera_cfg.get("properties", {}).items():
            if value is None or name not in CV_CAP_PROPS:
                continue
            capture.set(CV_CAP_PROPS[name], float(value))

    def _maybe_detect(self, frame: np.ndarray) -> None:
        with self._lock:
            detecting = self._detecting and not self._accepted
            frame_stride = max(1, int(self.config["detection"].get("frame_stride", 5)))
            self._frame_count += 1
            should_detect = detecting and self._frame_count % frame_stride == 0

        if not should_detect:
            return

        result: DetectionResult = self.pipeline.process(frame)
        self.detection_ready.emit(result)