Would this or another approach help with overloading  my system (android Motorola g power 2024) from multiprocessing import Pool
import os

# Path for saving frames
folder = "temp_frames"
os.makedirs(folder, exist_ok=True)

# Function for generating frames
def generate_frame_range(start, end, folder, cache_size=10):
    cache = []
    for i in range(start, end):
        frame = None  # Your frame generation logic here, keeping high quality
        cache.append(frame)
        
        # When cache is full, save the frames to disk
        if len(cache) >= cache_size:
            for idx, cached_frame in enumerate(cache):
                frame_path = os.path.join(folder, f"frame_{i - cache_size + idx}.png")
                cached_frame.save(frame_path)  # Save high-quality frame
            cache.clear()  # Clear cache to free up memory

    # Save remaining frames in the cache
    for idx, cached_frame in enumerate(cache):
        frame_path = os.path.join(folder, f"frame_{end - len(cache) + idx}.png")
        cached_frame.save(frame_path)

# Multi-processing to handle different frame ranges
if __name__ == "__main__":
    frame_ranges = [(0, 100), (100, 200), (200, 300), (300, 400)]  # Example
    with Pool(processes=4) as pool:  # Adjust processes as per your phone's CPU cores
        pool.starmap(generate_frame_range, [(start, end, folder) for start, end in frame_ranges])

# After generating frames, you can combine them into a video with MoviePy or similar
This is the script in question, I don't want to lose output quality import numpy as np
import os
import time
from PIL import Image
from moviepy.editor import VideoClip
from moviepy.video.fx.all import fadein, fadeout
from tqdm import tqdm

# Paths
image_one_path = '/home/daddy/morph/one.jpeg'
image_two_path = '/home/daddy/morph/two.jpeg'
output_path = '/home/daddy/morph/output'
output_filename = f'morph{int(time.time())}.mp4'

# Function to create each frame of the video
def make_frame(t):
    if t < duration1:
        # Display the first image
        frame_array = img1_array.copy()
    elif t < duration1 + duration2:
        # Morphing effect with particle explosion and implosion
        progress = (t - duration1) / duration2  # Normalize progress to [0, 1]

        # Create an empty frame with transparency
        frame_array = np.zeros_like(img1_array)

        for idx, (x, y) in enumerate(particle_positions):
            # Extract the patch from the first image
            patch = img1_array[y:y+particle_size, x:x+particle_size].copy()

            # Explosion offsets
            offset_x, offset_y = explosion_offsets[idx]

            if progress < 0.5:
                # Explosion phase
                explosion_progress = progress * 2  # Scale progress to [0, 1]
                current_x = x + explosion_progress * offset_x
                current_y = y + explosion_progress * offset_y
            else:
                # Implosion phase
                implosion_progress = (progress - 0.5) * 2  # Scale progress to [0, 1]

                # Target positions in the second image
                target_x, target_y = particle_to_target_position.get((x, y), (x, y))

                # Current position moves from exploded position to target position
                current_x = (x + offset_x) + implosion_progress * (target_x - (x + offset_x))
                current_y = (y + offset_y) + implosion_progress * (target_y - (y + offset_y))

            # Convert positions to integers and ensure they stay within frame boundaries
            current_x = int(np.clip(current_x, 0, width - particle_size))
            current_y = int(np.clip(current_y, 0, height - particle_size))

            # Place the current patch onto the frame
            frame_array[current_y:current_y+particle_size, current_x:current_x+particle_size] = patch

    else:
        # Hold the last frame where particles have formed the letters
        # Place particles at their target positions
        frame_array = np.zeros_like(img1_array)
        for idx, (x, y) in enumerate(particle_positions):
            # Extract the patch from the first image
            patch = img1_array[y:y+particle_size, x:x+particle_size].copy()
            # Target positions in the second image
            target_x, target_y = particle_to_target_position.get((x, y), (x, y))
            # Ensure positions are within frame boundaries
            current_x = int(np.clip(target_x, 0, width - particle_size))
            current_y = int(np.clip(target_y, 0, height - particle_size))
            # Place the patch at the target position
            frame_array[current_y:current_y+particle_size, current_x:current_x+particle_size] = patch

    # Convert the NumPy array back to an image
    frame_image = Image.fromarray(frame_array, 'RGBA')
    # Return frame as an RGB image (MoviePy expects RGB format)
    return np.array(frame_image.convert('RGB'))

# Main program
if __name__ == "__main__":
    # Input parameters with default values
    duration1 = int(input("Enter duration for first image display (seconds, default 5): ") or 5)
    duration2 = int(input("Enter duration for morphing effect (seconds, default 5): ") or 5)
    duration3 = int(input("Enter duration for final image hold (seconds, default 5): ") or 5)
    particle_size = int(input("Enter particle size (pixels, default 4): ") or 4)

    # Load images and ensure they are in RGBA format
    img1 = Image.open(image_one_path).convert('RGBA').resize((1024, 1024))
    img2 = Image.open(image_two_path).convert('RGBA').resize((1024, 1024))

    # Convert images to NumPy arrays
    img1_array = np.array(img1)
    img2_array = np.array(img2)

    # Get image dimensions
    width, height = img1.size

    # Generate particle positions
    particle_positions = []
    for y in range(0, height - particle_size + 1, particle_size):
        for x in range(0, width - particle_size + 1, particle_size):
            particle_positions.append((x, y))

    # Prepare explosion offsets
    explosion_offsets = []
    for _ in particle_positions:
        # Randomize explosion offsets for more dynamic effect
        offset_x = np.random.uniform(-width, width)
        offset_y = np.random.uniform(-height, height)
        explosion_offsets.append((offset_x, offset_y))

    # Detect target pixels in the second image (e.g., black pixels)
    target_threshold = int(input("Enter threshold for target pixel detection (0-765, default 100): ") or 100)

    # Prepare target pixel positions
    target_pixel_positions = []

    # Loop over the image, stepping by particle size
    for y in range(0, height - particle_size + 1, particle_size):
        for x in range(0, width - particle_size + 1, particle_size):
            # Extract the patch from the second image
            patch = img2_array[y:y+particle_size, x:x+particle_size, :3]
            # Calculate the sum of RGB values
            patch_sum = patch.sum()
            if patch_sum < target_threshold * particle_size * particle_size * 3:
                # This patch is dark enough to be considered part of the letters
                target_pixel_positions.append((x, y))

    # Map particles to target pixels
    particle_to_target_position = {}
    num_particles = len(particle_positions)
    num_targets = len(target_pixel_positions)

    if num_targets > 0:
        if num_particles <= num_targets:
            # Assign each particle to a unique target pixel
            selected_targets = np.random.choice(num_targets, num_particles, replace=False)
            for idx, particle_pos in enumerate(particle_positions):
                target_idx = selected_targets[idx]
                target_pos = target_pixel_positions[target_idx]
                particle_to_target_position[particle_pos] = target_pos
        else:
            # More particles than target positions, assign multiple particles to the same target
            repeats = num_particles // num_targets
            remainder = num_particles % num_targets
            target_positions_extended = target_pixel_positions * repeats + target_pixel_positions[:remainder]
            for idx, particle_pos in enumerate(particle_positions):
                target_pos = target_positions_extended[idx]
                particle_to_target_position[particle_pos] = target_pos
    else:
        # If no target pixels detected, map particles to their original positions
        for particle_pos in particle_positions:
            particle_to_target_position[particle_pos] = particle_pos

    total_duration = duration1 + duration2 + duration3

    # Create the video clip
    animation = VideoClip(make_frame, duration=total_duration)

    # Apply fade-in and fade-out effects
    animation = fadein(animation, 1.5).fx(fadeout, 1.5)

    # Add progress bar with TQDM
    print("Rendering Video:")
    with tqdm(total=int(total_duration * 24)) as pbar:
        animation = animation.set_fps(24)  # Set FPS to 24
        animation = animation.fl(lambda gf, t: (pbar.update(), gf(t))[1], apply_to="mask")

        # Write the video file
        animation.write_videofile(os.path.join(output_path, output_filename))