"""Stub file for predict directory."""
from typing import Any

from .io_utils import temporary_file_from_bytes
from .schemas import ActionPrediction, ClassificationPrediction, DetectionPrediction, FramewiseActionPredictions
from .schemas import DetectionPrediction

# Constants
FramewiseActionPredictions: Any = ...  # From schemas

# Functions
# From io_utils
def download_remote_file(url: str) -> str:
    """
    Download a remote artifact into a temporary file and return its local path.
    
        The file is intentionally not auto-deleted because model runtimes can keep
        lazy references to checkpoint files after constructor return.
    """
    ...

# From io_utils
def is_remote_path(path: str) -> bool:
    """
    Return True when a path is an HTTP(S) URL.
    """
    ...

# From io_utils
def prepare_torch_model_for_inference(model: Any.Any.Any, device: Any.Any | None = None) -> Any.Any.Any:
    """
    Move a torch model to the target device and switch to eval mode.
    """
    ...

# From io_utils
def resolve_torch_device() -> Any.Any:
    """
    Resolve best available torch device for inference.
    """
    ...

# From io_utils
def temporary_file_from_bytes(data: Any) -> Any[str, None, None]:
    """
    Write bytes to a temporary file and clean up when done.
    """
    ...

# From model_loader
def load_model_with_strategies(action_tracker: Any, strategies: Any) -> Any:
    """
    Load model according to checkpoint -> predefined -> scratch priority.
    """
    ...

# From model_loader
def report_model_load_failure(action_tracker: Any) -> None:
    """
    Best-effort status and error reporting without raising secondary exceptions.
    """
    ...

# From postprocessor
def classification_top1_from_raw_output(raw_output: Any) -> Any:
    """
    Normalize common runtime outputs and return top-1 prediction.
    """
    ...

# From postprocessor
def classification_top1_prediction(logits: Any.Any) -> Any:
    """
    Return top-1 class prediction with confidence from logits.
    """
    ...

# From postprocessor
def format_detection_from_normalized_tensors(labels: Any.Any, boxes_xyxy_normalized: Any.Any, scores: Any.Any) -> list[Any]:
    """
    Convert normalized detection tensors into API-ready dict records.
    """
    ...

# From postprocessor
def framewise_action_results(inference_results: Any[Any[str, Any]]) -> Any:
    """
    Group frame-level action predictions keyed by frame index string.
    """
    ...

# From preprocessor
def build_image_transform(config: Any) -> Any.Any:
    """
    Construct torchvision transform pipeline for model inference.
    """
    ...

# From preprocessor
def get_model_device(model: Any.Any.Any) -> Any.Any:
    """
    Return model parameter device, or CPU for parameter-less models.
    """
    ...

# From preprocessor
def load_rgb_image_from_bytes(image_bytes: Any) -> Any.Any:
    """
    Decode image bytes into an RGB PIL image.
    """
    ...

# From preprocessor
def preprocess_image_from_bytes(image_bytes: Any) -> tuple[Any.Any, Any.Any]:
    """
    Decode and transform image bytes into batched tensor [1, C, H, W].
    """
    ...

# From preprocessor
def probe_video_fps(video_bytes: Any) -> float:
    """
    Extract FPS from video bytes using OpenCV with temp-file isolation.
    """
    ...

# From status_handler
def safe_log_error(action_tracker: Any, file_path: str, location: str, message: str) -> None:
    """
    Best-effort ActionTracker error logging.
    """
    ...

# From status_handler
def safe_update_status(action_tracker: Any, step_code: str, status: str, description: str) -> None:
    """
    Best-effort status update that never raises to caller.
    """
    ...

# From tensorrt_adapter
def adapt_tensorrt_yolo_output(output: Any) -> list[Any]:
    """
    Normalize YOLO detections from TensorRT/trtexec/Ultralytics outputs.
    
        Supported styles:
        - Ultralytics results list (result.boxes.xyxy/conf/cls)
        - TensorRT NMS plugin output (`num_dets`, `boxes`, `scores`, `classes`)
        - Dense detection matrix shaped [N, 6+] with `[x1,y1,x2,y2,score,cls,...]`
        - Raw head-like matrix [N, 5 + num_classes] or [N, 4 + num_classes]
    """
    ...

# Classes
# From model_loader
class ModelLoadStrategies:
    # Strategy callbacks for checkpoint/predefined/scratch model loading.
    #
    #     Each BYOM project injects task-specific loader callbacks while reusing the
    #     common branching logic.

    ...

# From preprocessor
class ImagePreprocessConfig:
    # Standard image preprocessing configuration.

    ...

# From schemas
class ActionPrediction:
    # Per-frame action prediction for video recognition.

    ...

# From schemas
class BoundingBox:
    # Axis-aligned bounding box in absolute pixel coordinates.

    ...

# From schemas
class ClassificationPrediction:
    # Single-label classification prediction.

    ...

# From schemas
class DetectionPrediction:
    # Object detection prediction record.

    ...

# From status_handler
class PredictionStatusCodes:
    # Canonical prediction-related status step codes.

    ...

# From status_handler
class PredictionStatusReporter:
    # Semantic status reporter for prediction error transitions.

    def __init__(self: Any, action_tracker: Any, codes: Any | None = None) -> None:
        """
        Create a reporter backed by an ActionTracker-like object.
        """
        ...

    def model_load_failed(self: Any, msg: str = 'Error in loading model') -> None:
        """
        Emit model-load failure status.
        """
        ...

    def prediction_failed(self: Any, msg: str = 'Error during prediction') -> None:
        """
        Emit prediction failure status.
        """
        ...


# From tensorrt_adapter
class TensorRTYOLOAdapterConfig:
    # Configuration for adapting TensorRT YOLO detections.

    ...

from . import io_utils, model_loader, postprocessor, preprocessor, schemas, status_handler, tensorrt_adapter