# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license

import argparse
from collections import defaultdict
from pathlib import Path
from typing import Any, List

import cv2
import numpy as np
from shapely.geometry import Polygon
from shapely.geometry.point import Point

from ultralytics import YOLO
from ultralytics.utils.files import increment_path
from ultralytics.utils.plotting import Annotator, colors

track_history = defaultdict(list)

current_region = None
counting_regions = [
    {
        "name": "YOLOv8 Polygon Region",
        "polygon": Polygon([(50, 80), (250, 20), (450, 80), (400, 350), (100, 350)]),  # Polygon points
        "counts": 0,
        "dragging": False,
        "region_color": (255, 42, 4),  # BGR Value
        "text_color": (255, 255, 255),  # Region Text Color
    },
    {
        "name": "YOLOv8 Rectangle Region",
        "polygon": Polygon([(200, 250), (440, 250), (440, 550), (200, 550)]),  # Polygon points
        "counts": 0,
        "dragging": False,
        "region_color": (37, 255, 225),  # BGR Value
        "text_color": (0, 0, 0),  # Region Text Color
    },
]


def mouse_callback(event: int, x: int, y: int, flags: int, param: Any) -> None:
    """
    Handle mouse events for region manipulation.

    Args:
        event (int): The mouse event type (e.g., cv2.EVENT_LBUTTONDOWN).
        x (int): The x-coordinate of the mouse pointer.
        y (int): The y-coordinate of the mouse pointer.
        flags (int): Additional flags passed by OpenCV.
        param (Any): Additional parameters passed to the callback.

    Global Variables:
        current_region (dict): A dictionary representing the current selected region.

    Notes:
        This function is intended to be used as a callback for OpenCV mouse events.
        It allows for selecting and dragging counting regions within the video frame.

    Examples:
        >>> cv2.setMouseCallback(window_name, mouse_callback)
    """
    global current_region

    # Mouse left button down event
    if event == cv2.EVENT_LBUTTONDOWN:
        for region in counting_regions:
            if region["polygon"].contains(Point((x, y))):
                current_region = region
                current_region["dragging"] = True
                current_region["offset_x"] = x
                current_region["offset_y"] = y

    # Mouse move event
    elif event == cv2.EVENT_MOUSEMOVE:
        if current_region is not None and current_region["dragging"]:
            dx = x - current_region["offset_x"]
            dy = y - current_region["offset_y"]
            current_region["polygon"] = Polygon(
                [(p[0] + dx, p[1] + dy) for p in current_region["polygon"].exterior.coords]
            )
            current_region["offset_x"] = x
            current_region["offset_y"] = y

    # Mouse left button up event
    elif event == cv2.EVENT_LBUTTONUP:
        if current_region is not None and current_region["dragging"]:
            current_region["dragging"] = False


def run(
    weights: str = "yolo11n.pt",
    source: str = None,
    device: str = "cpu",
    view_img: bool = False,
    save_img: bool = False,
    exist_ok: bool = False,
    classes: List[int] = None,
    line_thickness: int = 2,
    track_thickness: int = 2,
    region_thickness: int = 2,
) -> None:
    """
    Run region counting on a video using YOLOv8 and ByteTrack.

    Args:
        weights (str): Model weights path.
        source (str): Video file path.
        device (str): Processing device: 'cpu', '0', '1', etc.
        view_img (bool): Show results in a window.
        save_img (bool): Save results to a video file.
        exist_ok (bool): Overwrite existing files.
        classes (List[int]): Classes to detect and track.
        line_thickness (int): Bounding box thickness.
        track_thickness (int): Tracking line thickness.
        region_thickness (int): Region thickness.

    Notes:
        - Supports movable regions for real-time counting inside specific areas.
        - Supports multiple regions counting.
        - Regions can be Polygons or rectangles in shape.
    """
    vid_frame_count = 0

    # Check source path
    if not Path(source).exists():
        raise FileNotFoundError(f"Source path '{source}' does not exist.")

    # Setup Model
    model = YOLO(f"{weights}")
    model.to("cuda") if device == "0" else model.to("cpu")

    # Extract classes names
    names = model.names

    # Video setup
    videocapture = cv2.VideoCapture(source)
    frame_width = int(videocapture.get(3))
    frame_height = int(videocapture.get(4))
    fps = int(videocapture.get(5))
    fourcc = cv2.VideoWriter_fourcc(*"mp4v")

    # Output setup
    save_dir = increment_path(Path("ultralytics_rc_output") / "exp", exist_ok)
    save_dir.mkdir(parents=True, exist_ok=True)
    video_writer = cv2.VideoWriter(str(save_dir / f"{Path(source).stem}.avi"), fourcc, fps, (frame_width, frame_height))

    # Iterate over video frames
    while videocapture.isOpened():
        success, frame = videocapture.read()
        if not success:
            break
        vid_frame_count += 1

        # Extract the results
        results = model.track(frame, persist=True, classes=classes)

        if results[0].boxes.id is not None:
            boxes = results[0].boxes.xyxy.cpu()
            track_ids = results[0].boxes.id.int().cpu().tolist()
            clss = results[0].boxes.cls.cpu().tolist()

            annotator = Annotator(frame, line_width=line_thickness, example=str(names))

            for box, track_id, cls in zip(boxes, track_ids, clss):
                annotator.box_label(box, str(names[cls]), color=colors(cls, True))
                bbox_center = (box[0] + box[2]) / 2, (box[1] + box[3]) / 2  # Bbox center

                track = track_history[track_id]  # Tracking Lines plot
                track.append((float(bbox_center[0]), float(bbox_center[1])))
                if len(track) > 30:
                    track.pop(0)
                points = np.hstack(track).astype(np.int32).reshape((-1, 1, 2))
                cv2.polylines(frame, [points], isClosed=False, color=colors(cls, True), thickness=track_thickness)

                # Check if detection inside region
                for region in counting_regions:
                    if region["polygon"].contains(Point((bbox_center[0], bbox_center[1]))):
                        region["counts"] += 1

        # Draw regions (Polygons/Rectangles)
        for region in counting_regions:
            region_label = str(region["counts"])
            region_color = region["region_color"]
            region_text_color = region["text_color"]

            polygon_coordinates = np.array(region["polygon"].exterior.coords, dtype=np.int32)
            centroid_x, centroid_y = int(region["polygon"].centroid.x), int(region["polygon"].centroid.y)

            text_size, _ = cv2.getTextSize(
                region_label, cv2.FONT_HERSHEY_SIMPLEX, fontScale=0.7, thickness=line_thickness
            )
            text_x = centroid_x - text_size[0] // 2
            text_y = centroid_y + text_size[1] // 2
            cv2.rectangle(
                frame,
                (text_x - 5, text_y - text_size[1] - 5),
                (text_x + text_size[0] + 5, text_y + 5),
                region_color,
                -1,
            )
            cv2.putText(
                frame, region_label, (text_x, text_y), cv2.FONT_HERSHEY_SIMPLEX, 0.7, region_text_color, line_thickness
            )
            cv2.polylines(frame, [polygon_coordinates], isClosed=True, color=region_color, thickness=region_thickness)

        if view_img:
            if vid_frame_count == 1:
                cv2.namedWindow("Ultralytics YOLOv8 Region Counter Movable")
                cv2.setMouseCallback("Ultralytics YOLOv8 Region Counter Movable", mouse_callback)
            cv2.imshow("Ultralytics YOLOv8 Region Counter Movable", frame)

        if save_img:
            video_writer.write(frame)

        for region in counting_regions:  # Reinitialize count for each region
            region["counts"] = 0

        if cv2.waitKey(1) & 0xFF == ord("q"):
            break

    del vid_frame_count
    video_writer.release()
    videocapture.release()
    cv2.destroyAllWindows()


def parse_opt() -> argparse.Namespace:
    """Parse command line arguments for the region counting application."""
    parser = argparse.ArgumentParser()
    parser.add_argument("--weights", type=str, default="yolo11n.pt", help="initial weights path")
    parser.add_argument("--device", default="", help="cuda device, i.e. 0 or 0,1,2,3 or cpu")
    parser.add_argument("--source", type=str, required=True, help="video file path")
    parser.add_argument("--view-img", action="store_true", help="show results")
    parser.add_argument("--save-img", action="store_true", help="save results")
    parser.add_argument("--exist-ok", action="store_true", help="existing project/name ok, do not increment")
    parser.add_argument("--classes", nargs="+", type=int, help="filter by class: --classes 0, or --classes 0 2 3")
    parser.add_argument("--line-thickness", type=int, default=2, help="bounding box thickness")
    parser.add_argument("--track-thickness", type=int, default=2, help="Tracking line thickness")
    parser.add_argument("--region-thickness", type=int, default=4, help="Region thickness")

    return parser.parse_args()


def main(options: argparse.Namespace) -> None:
    """Execute the main region counting functionality with the provided options."""
    run(**vars(options))


if __name__ == "__main__":
    opt = parse_opt()
    main(opt)
