bartool
090865af76
Add PySide6 camera UI, YOLO/Tesseract detection pipeline, capture metadata, configuration, and project gitignore.
130 lines
4.0 KiB
Python
130 lines
4.0 KiB
Python
from __future__ import annotations
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import threading
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import time
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from typing import Any
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import cv2
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import numpy as np
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from PySide6.QtCore import QThread, Signal, Slot
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from app.detection import DetectionPipeline, DetectionResult
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CV_CAP_PROPS = {
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"brightness": cv2.CAP_PROP_BRIGHTNESS,
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"contrast": cv2.CAP_PROP_CONTRAST,
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"saturation": cv2.CAP_PROP_SATURATION,
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"hue": cv2.CAP_PROP_HUE,
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"gain": cv2.CAP_PROP_GAIN,
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"exposure": cv2.CAP_PROP_EXPOSURE,
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"sharpness": cv2.CAP_PROP_SHARPNESS,
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"auto_exposure": cv2.CAP_PROP_AUTO_EXPOSURE,
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"focus": cv2.CAP_PROP_FOCUS,
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"auto_focus": cv2.CAP_PROP_AUTOFOCUS,
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}
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def backend_for_name(name: str) -> int:
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if name == "avfoundation":
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return cv2.CAP_AVFOUNDATION
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if name == "v4l2":
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return cv2.CAP_V4L2
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if name == "dshow":
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return cv2.CAP_DSHOW
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return cv2.CAP_ANY
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class CameraWorker(QThread):
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frame_ready = Signal(object)
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detection_ready = Signal(object)
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camera_error = Signal(str)
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def __init__(self, config: dict[str, Any], app_config: Any) -> None:
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super().__init__()
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self.config = config
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self.app_config = app_config
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self.pipeline = DetectionPipeline(config, app_config)
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self._running = threading.Event()
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self._running.set()
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self._detecting = False
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self._accepted = False
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self._frame_count = 0
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self._capture: cv2.VideoCapture | None = None
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self._lock = threading.Lock()
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def stop(self) -> None:
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self._running.clear()
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@Slot()
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def start_detection(self) -> None:
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with self._lock:
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self._detecting = True
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self._accepted = False
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self._frame_count = 0
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@Slot()
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def accept_detection(self) -> None:
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with self._lock:
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self._detecting = False
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self._accepted = True
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@Slot(dict)
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def update_camera_config(self, camera_config: dict[str, Any]) -> None:
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with self._lock:
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self.config["camera"] = camera_config
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capture = self._capture
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if capture is not None:
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self._apply_camera_settings(capture)
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def run(self) -> None:
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camera_cfg = self.config["camera"]
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capture = cv2.VideoCapture(
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int(camera_cfg.get("index", 0)),
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backend_for_name(str(camera_cfg.get("backend", "auto"))),
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)
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self._capture = capture
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if not capture.isOpened():
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self.camera_error.emit("Nie mozna otworzyc kamery USB")
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return
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self._apply_camera_settings(capture)
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try:
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while self._running.is_set():
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ok, frame = capture.read()
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if not ok or frame is None:
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self.camera_error.emit("Nie mozna odczytac klatki z kamery")
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time.sleep(0.2)
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continue
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self.frame_ready.emit(frame)
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self._maybe_detect(frame)
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finally:
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capture.release()
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self._capture = None
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def _apply_camera_settings(self, capture: cv2.VideoCapture) -> None:
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camera_cfg = self.config["camera"]
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capture.set(cv2.CAP_PROP_FRAME_WIDTH, int(camera_cfg.get("width", 1920)))
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capture.set(cv2.CAP_PROP_FRAME_HEIGHT, int(camera_cfg.get("height", 1080)))
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capture.set(cv2.CAP_PROP_FPS, int(camera_cfg.get("fps", 30)))
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for name, value in camera_cfg.get("properties", {}).items():
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if value is None or name not in CV_CAP_PROPS:
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continue
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capture.set(CV_CAP_PROPS[name], float(value))
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def _maybe_detect(self, frame: np.ndarray) -> None:
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with self._lock:
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detecting = self._detecting and not self._accepted
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frame_stride = max(1, int(self.config["detection"].get("frame_stride", 5)))
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self._frame_count += 1
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should_detect = detecting and self._frame_count % frame_stride == 0
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if not should_detect:
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return
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result: DetectionResult = self.pipeline.process(frame)
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self.detection_ready.emit(result)
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