Добавлено описание и документация для HVideoTool, включая функционал, требования, установку и запуск приложения для обнаружения цензуры на изображениях.

hvideotool/config.py

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+"""Application configuration and tunable defaults.
+
+Plain dataclasses. The detection thresholds matter most here — this tool is now
+an image-folder inspector for tuning the detectors, so keep them easy to tweak.
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+
+
+@dataclass(frozen=True)
+class DetectionConfig:
+    """Parameters for the detector. Thresholds tuned for the classic-CV detector."""
+
+    proc_max_dim: int = 720      # downscale longer side to this before detection (speed)
+    min_area_frac: float = 0.0008  # ignore regions smaller than this fraction of the image
+
+    # --- solid bars (black or white, achromatic, rectangular) ---
+    black_intensity: int = 40    # V below this = dark-bar candidate
+    white_intensity: int = 225   # V above this = light-bar candidate
+    bar_saturation_max: int = 45  # S below this = achromatic (excludes colored fills)
+    bar_min_extent: float = 0.80  # contour area / bbox area — how rectangular a bar must be
+
+    # --- mosaic / pixelation ---
+    mosaic_block_sizes: tuple[int, ...] = (8, 12, 16, 24)  # candidate tile sizes (px, proc space)
+    mosaic_residual_max: float = 6.0   # max reconstruction error to count as "blocky"
+    mosaic_contrast_min: float = 14.0  # min local contrast (excludes flat gradients)
+    mosaic_grad_min: float = 8.0       # min edge energy in BOTH x and y (excludes straight edges)
+    mosaic_min_side: int = 24          # reject thin regions (px) — kills edge false-positives
+
+    # --- blur ---
+    blur_window: int = 31              # sliding window for local sharpness (odd)
+    blur_sharpness_ratio: float = 0.35  # below this fraction of median sharpness => blurry
+    blur_contrast_min: float = 8.0     # min local contrast (excludes flat regions)
+
+    # --- YOLO detector (used only when detector == "yolo"/"combined") ---
+    yolo_conf: float = 0.2             # confidence threshold (LADA recommends ~0.2)
+    yolo_imgsz: int = 640              # inference image size
+    yolo_device: str | None = None     # None => auto ("cuda" if available, else "cpu")
+
+
+@dataclass(frozen=True)
+class OverlayConfig:
+    """How detections are drawn over the image."""
+
+    # RGB per CensorType value
+    colors: dict[str, tuple[int, int, int]] = field(
+        default_factory=lambda: {
+            "mosaic": (231, 76, 60),     # red
+            "blur": (241, 196, 15),      # yellow
+            "black_bar": (26, 188, 156),  # teal
+            "unknown": (155, 89, 182),   # purple
+        }
+    )
+    line_width: int = 2
+    fill_alpha: int = 48  # 0..255 translucency of the region fill
+    show_labels: bool = True
+
+
+@dataclass
+class AppConfig:
+    detection: DetectionConfig = field(default_factory=DetectionConfig)
+    overlay: OverlayConfig = field(default_factory=OverlayConfig)
+    detector: str = "classic"          # "classic" | "yolo" | "combined"
+    model_path: str | None = None      # weights path, used by the YOLO detector
+    default_threshold: float = 0.20    # initial overlay confidence threshold