"""
Export loading screen animation as a list of unique, ordered frames.

Outputs:
  - frames/frame_XXXX.png  — one PNG per unique frame
  - frames/frames.npy      — numpy array of shape (n_unique, H, W), dtype bool

Run with:
  uv run export_loading_frames.py [--out-dir frames]
"""

import argparse
import os
import sys

import numpy as np

from frontend.views.loading import LoadingView


def render_all_frames(view: LoadingView) -> list:
    """Render every animation frame and return as list of PIL Images."""
    frames = []
    while True:
        im, done = view.get_frame()
        frames.append(im)
        if done:
            break
    return frames


def deduplicate(frames: list) -> list:
    """Keep only frames that differ from the previous one."""
    unique = [frames[0]]
    prev = frames[0].tobytes()
    for im in frames[1:]:
        b = im.tobytes()
        if b != prev:
            unique.append(im)
            prev = b
    return unique


def main():
    parser = argparse.ArgumentParser(description="Export loading screen frames.")
    parser.add_argument("--out-dir", default="frames", help="Output directory")
    args = parser.parse_args()

    size = (168, 144)
    center = (168 // 2, 144 // 2)

    view = LoadingView(size, center)
    all_frames = render_all_frames(view)
    unique_frames = deduplicate(all_frames)

    print(f"Total frames rendered : {len(all_frames)}")
    print(f"Unique frames exported: {len(unique_frames)}")

    os.makedirs(args.out_dir, exist_ok=True)

    # Save individual PNGs
    for i, im in enumerate(unique_frames):
        im.save(os.path.join(args.out_dir, f"frame_{i:04d}.png"))

    # Save as numpy array (bool, shape: n_frames x H x W)
    arr = np.stack([np.array(im) for im in unique_frames])  # shape (N, H, W)
    npy_path = os.path.join(args.out_dir, "frames.npy")
    np.save(npy_path, arr)
    print(f"Saved PNGs and {npy_path} ({arr.shape}, {arr.dtype})")


if __name__ == "__main__":
    main()