import cv2
import numpy as np
from PIL import Image
from typing import List
import os

def extract_frames(video_path: str, num_frames: int = 10) -> List[Image.Image]:
    """
    Extracts a fixed number of evenly spaced frames from a video file.
    
    Args:
        video_path: Path to the video file
        num_frames: Number of frames to extract
        
    Returns:
        List of PIL Images extracted from the video
        
    Raises:
        ValueError: If video cannot be opened or is invalid
    """
    if not os.path.exists(video_path):
        raise FileNotFoundError(f"Video file not found: {video_path}")
        
    cap = cv2.VideoCapture(video_path)
    if not cap.isOpened():
        raise ValueError(f"Could not open video file: {video_path}")
        
    try:
        total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
        if total_frames <= 0:
            raise ValueError("Video contains no frames or duration cannot be determined")
            
        # If video has fewer frames than requested, take all available frames
        actual_num_frames = min(num_frames, total_frames)
        
        # Calculate frame indices to extract (evenly spaced)
        indices = np.linspace(0, total_frames - 1, actual_num_frames, dtype=int)
        
        frames = []
        for idx in indices:
            # Set the frame position
            cap.set(cv2.CAP_PROP_POS_FRAMES, idx)
            ret, frame = cap.read()
            
            if ret:
                # OpenCV returns BGR, convert to RGB for PIL
                frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
                pil_image = Image.fromarray(frame_rgb)
                frames.append(pil_image)
            else:
                print(f"[Warning] Failed to read frame {idx} from {video_path}")
                
        if not frames:
            raise ValueError("Failed to extract any valid frames from the video")
            
        return frames
        
    finally:
        cap.release()