video_to_sketch_script_cv2.py

'''
python video_to_sketch_script_cv2.py test test-sketch --copy_others
'''

import gc
import os
import shutil
import argparse
import numpy as np
import torch
import cv2
from huggingface_hub import hf_hub_download
from PIL.Image import Resampling
from pytorchvideo.data.encoded_video import EncodedVideo
from pytorchvideo.transforms.functional import uniform_temporal_subsample
from torchvision.transforms.functional import resize
from tqdm import tqdm

from modeling import Generator

MAX_DURATION = 60
OUT_FPS = 18
DEVICE = "cpu" if not torch.cuda.is_available() else "cuda"

# Load the model
model = Generator(3, 1, 3)
weights_path = hf_hub_download("nateraw/image-2-line-drawing", "pytorch_model.bin")
model.load_state_dict(torch.load(weights_path, map_location=DEVICE))
model.eval()

def process_one_second(vid, start_sec, out_fps):
    """Process one second of a video at a given fps
    Args:
        vid (_type_): A pytorchvideo.EncodedVideo instance containing the video to process
        start_sec (_type_): The second to start processing at
        out_fps (_type_): The fps to output the video at
    Returns:
        np.array: The processed video as a numpy array with shape (T, H, W, C)
    """
    # C, T, H, W
    video_arr = vid.get_clip(start_sec, start_sec + 1)["video"]
    # C, T, H, W where T == frames per second
    x = uniform_temporal_subsample(video_arr, out_fps)
    # C, T, H, W where H has been scaled to 256
    x = resize(x, 256, Resampling.BICUBIC)
    # C, T, H, W -> T, C, H, W (basically T acts as batch size now)
    x = x.permute(1, 0, 2, 3)

    with torch.no_grad():
        # T, 1, H, W
        out = model(x)

    # T, C, H, W -> T, H, W, C Rescaled to 0-255
    out = out.permute(0, 2, 3, 1).clip(0, 1) * 255
    # Greyscale -> RGB
    out = out.repeat(1, 1, 1, 3)
    return out.cpu().numpy().astype(np.uint8)  # Convert to uint8 for OpenCV

def process_video(input_video_path, output_video_path):
    vid = EncodedVideo.from_path(input_video_path)
    duration = min(MAX_DURATION, int(vid.duration))
    
    # Initialize VideoWriter (get frame size from first frame)
    first_frame = process_one_second(vid, start_sec=0, out_fps=OUT_FPS)
    height, width = first_frame.shape[1], first_frame.shape[2]
    
    # Use 'mp4v' for .mp4, 'XVID' for .avi, etc.
    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
    out_video = cv2.VideoWriter(
        output_video_path,
        fourcc,
        OUT_FPS,
        (width, height)
    )
    
    # Write first frame
    for frame in first_frame:
        frame_bgr = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
        out_video.write(frame_bgr)
    
    # Process remaining frames
    for i in tqdm(range(1, duration), desc="Processing video"):
        video_frames = process_one_second(vid, start_sec=i, out_fps=OUT_FPS)
        for frame in video_frames:
            frame_bgr = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
            out_video.write(frame_bgr)
        gc.collect()
    
    out_video.release()

def copy_non_video_files(input_path, output_path):
    """Copy non-video files and directories from input path to output path."""
    for item in os.listdir(input_path):
        item_path = os.path.join(input_path, item)
        if not item.lower().endswith(('.mp4', '.avi', '.mov', '.mkv')):
            dest_path = os.path.join(output_path, item)
            if os.path.isdir(item_path):
                shutil.copytree(item_path, dest_path)
            else:
                shutil.copy2(item_path, dest_path)

def main(input_path, output_path, copy_others=False):
    if not os.path.exists(output_path):
        os.makedirs(output_path)

    if copy_others:
        copy_non_video_files(input_path, output_path)

    for video_name in os.listdir(input_path):
        if video_name.lower().endswith(('.mp4', '.avi', '.mov', '.mkv')):
            input_video_path = os.path.join(input_path, video_name)
            output_video_path = os.path.join(output_path, video_name)
            process_video(input_video_path, output_video_path)

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Process videos to convert them into sketch videos.")
    parser.add_argument("input_path", type=str, help="Path to the input directory containing videos.")
    parser.add_argument("output_path", type=str, help="Path to the output directory for processed videos.")
    parser.add_argument("--copy_others", action="store_true", help="Copy non-video files and directories from input to output.")

    args = parser.parse_args()
    main(args.input_path, args.output_path, args.copy_others)