Creating a video from a series of frames (images) using Python can be efficiently accomplished with the help of the opencv-python library. OpenCV (Open Source Computer Vision Library) is a highly optimized library for computer vision applications which also includes various utilities for video processing.

Below is a step-by-step Python function that takes a list of frames (where each frame is a numpy array representing an image) and writes them into a video file:

Prerequisites:

Ensure you have the opencv-python package installed. You can install it via pip if it’s not already installed:

pip install opencv-python

Python Function:

import cv2
def write_frames_to_video(frame_paths, output_file, fps=30, frame_size=None):
    """
    Writes a list of image frames (from file paths) to an MP4 video file.
    Args:
    frame_paths (list of str): List of paths to the frame images.
    output_file (str): Path to the output video file.
    fps (int, optional): Frames per second of the output video. Default is 30.
    frame_size (tuple, optional): The size (width, height) of each frame. If not specified, it will use the size of the first frame loaded.
    Returns:
    None
    """
    # Initialize video writer once the first frame is loaded to determine size
    first_frame = cv2.imread(frame_paths[0])
    if first_frame is None:
        raise ValueError(f"Cannot load image at path: {frame_paths[0]}")
    
    if frame_size is None:
        frame_size = (first_frame.shape[1], first_frame.shape[0])  # frame width, frame height
    # Define the codec and create VideoWriter object
    fourcc = cv2.VideoWriter_fourcc(*'MP4V')  # 'MP4V' for .mp4 files
    out = cv2.VideoWriter(output_file, fourcc, fps, frame_size, True)
    # Load each frame and write to the video
    for path in frame_paths:
        frame = cv2.imread(path)
        if frame is None:
            print(f"Warning: Skipping frame. Cannot load image at path: {path}")
            continue
        
        # Convert frame to BGR color format if necessary
        if len(frame.shape) == 3 and frame.shape[2] == 3:  # If frame is in color
            frame_bgr = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
        else:
            frame_bgr = frame
        
        out.write(frame_bgr)
    # Release everything when job is finished
    out.release()
# Example usage:
if __name__ == "__main__":
    frame_paths = ['path_to_frame_{}.png'.format(i) for i in range(1, 10)]  # List of paths to your frames
    write_frames_to_video(frame_paths, 'output_video.mp4', fps=24)  # Specify the output file and fps

Notes:

• Frame Size: It’s crucial that all frames have the same dimensions. If the images are not of the same size, you’ll need to resize them before writing to video.
• Codecs: The choice of codec (fourcc) can depend on the output file format you desire (AVI, MP4, etc.). Make sure that the codec you choose is compatible with your desired file format and supported on your platform.
• File Formats and Compatibility: Some combinations of codec and file format might not work depending on the system and installed codecs. If you encounter issues, try changing the codec or the output format.

  This function provides a basic framework. Depending on your specific needs, you may want to add error handling (e.g., checking if the file paths are correct, if frames are correctly loaded, etc.) or additional video processing features.