Made project river-agnostic

src/clip_annotator/config.py

@@ -0,0 +1,94 @@
+from dataclasses import dataclass, field
+from pathlib import Path
+
+import yaml
+
+
+@dataclass
+class FilenameConfig:
+    video_in_zip: str = "left.mp4"
+    video_tmp_suffix: str = ".mp4"
+    zip_extension: str = ".zip"
+    mask: str = "mask.png"
+    metadata: str = "metadata.json"
+    frame: str = "frame.png"
+    overlay: str = "overlay.png"
+    mask_vis: str = "mask_vis.png"
+    gif_original_hires: str = "video_original_hires.gif"
+    gif_original_lowres: str = "video_original_lowres.gif"
+    gif_overlay_hires: str = "video_overlay_hires.gif"
+    gif_overlay_lowres: str = "video_overlay_lowres.gif"
+
+
+@dataclass
+class AppConfig:
+    storage: str
+    data_dir: str
+    out_dir: str
+    optical_flow_config_file: str
+    questions_config_file: str
+    display_max: int = 480
+    fps_fallback: int = 25
+    max_frames: int = 100
+    clips_file: str = "config/clips.txt"
+    filenames: FilenameConfig = field(default_factory=FilenameConfig)
+    questions: list = field(default_factory=list, init=False)
+
+    def get_questions(self):
+        return [
+            (
+                s["section"],
+                [
+                    (
+                        item["key"],
+                        item["label"],
+                        [str(o) for o in item["options"]],
+                        str(item["default"])
+                        if item.get("default") is not None
+                        else None,
+                    )
+                    for item in s["items"]
+                ],
+            )
+            for s in self.questions
+        ]
+
+
+@dataclass
+class OpticalFlowConfig:
+    enabled: bool = False
+    norm_squared_threshold: float = 0.3
+    gaussian_kernel: tuple[int, int] = (5, 5)
+    brightness_range: tuple[int, int] = (20, 235)
+
+
+def load_optical_flow_config(path: Path) -> OpticalFlowConfig:
+    with open(path) as f:
+        data = yaml.safe_load(f)
+    data["gaussian_kernel"] = tuple(data["gaussian_kernel"])
+    data["brightness_range"] = tuple(data["brightness_range"])
+    return OpticalFlowConfig(**data)
+
+
+def load_questions_config(path: Path) -> list:
+    with open(path) as f:
+        return yaml.safe_load(f)
+
+
+def load_config(path: Path) -> AppConfig:
+    with open(path) as f:
+        data = yaml.safe_load(f)
+    for required in (
+        "storage",
+        "data_dir",
+        "out_dir",
+        "optical_flow_config_file",
+        "questions_config_file",
+    ):
+        if not data.get(required):
+            raise ValueError(f"{path}: missing required field '{required}'.")
+    fn_data = data.pop("filenames", {})
+    cfg = AppConfig(**data)
+    cfg.filenames = FilenameConfig(**fn_data)
+    cfg.questions = load_questions_config(Path(cfg.questions_config_file))
+    return cfg