vfi_utilities.py

# https://github.com/Fannovel16/ComfyUI-Frame-Interpolation/blob/main/vfi_utils.py

import os
import torch
import typing
import einops
from comfy.model_management import soft_empty_cache, get_torch_device
import numpy as np
from comfy.utils import ProgressBar
from colored import Fore, Back, Style

DEVICE = get_torch_device()

def load_file_from_github_release(model_type, ckpt_name):
    error_strs = []
    for i, base_model_download_url in enumerate(BASE_MODEL_DOWNLOAD_URLS):
        try:
            return load_file_from_url(base_model_download_url + ckpt_name, get_ckpt_container_path(model_type))
        except Exception:
            traceback_str = traceback.format_exc()
            if i < len(BASE_MODEL_DOWNLOAD_URLS) - 1:
                print("Failed! Trying another endpoint.")
            error_strs.append(f"Error when downloading from: {base_model_download_url + ckpt_name}\n\n{traceback_str}")

    error_str = '\n\n'.join(error_strs)
    raise Exception(f"Tried all GitHub base urls to download {ckpt_name} but no suceess. Below is the error log:\n\n{error_str}")

def logger(msg):
    print(f'{Style.reset}{Fore.cyan}⚡ [Rife Tensorrt] - {msg}{Style.reset}')

def preprocess_frames(frames):
    return einops.rearrange(frames[..., :3], "n h w c -> n c h w")

def postprocess_frames(frames):
    return einops.rearrange(frames, "n c h w -> n h w c")[..., :3].cpu()

def generate_frames_rife(
        frames,
        clear_cache_after_n_frames,
        multiplier,
        return_middle_frame_function
        ):

    output_frames = torch.zeros(multiplier*frames.shape[0], *frames.shape[1:], device="cpu")
    out_len = 0

    number_of_frames_processed_since_last_cleared_cuda_cache = 0
    # pbar = ProgressBar(len(frames))

    for frame_itr in range(len(frames) - 1): # Skip the final frame since there are no frames after it

        frame_0 = frames[frame_itr:frame_itr+1]
        frame_1 = frames[frame_itr+1:frame_itr+2]
        output_frames[out_len] = frame_0 # Start with first frame
        out_len += 1

        for middle_i in range(1, multiplier):
            timestep = middle_i/multiplier
            middle_frame = return_middle_frame_function(frame_0, frame_1, timestep).detach().cpu()

            # Copy middle frames to output
            output_frames[out_len] = middle_frame
            out_len +=1

            # Try to avoid a memory overflow by clearing cuda cache regularly
            number_of_frames_processed_since_last_cleared_cuda_cache += 1
            if number_of_frames_processed_since_last_cleared_cuda_cache >= clear_cache_after_n_frames:
                soft_empty_cache()
                number_of_frames_processed_since_last_cleared_cuda_cache = 0
                logger("Clearing cache...")

            # pbar.update(1)


    # Append final frame
    output_frames[out_len] = frames[-1:]
    logger(f"done! - {(len(frames) -1) * (multiplier-1)} new frames generated at resolution: {output_frames[0].shape}")
    out_len += 1

    # clear cache for courtesy
    soft_empty_cache()
    logger("Final clearing cache done ...")
#
    res = output_frames[:out_len]

    return res