diffsynth/extensions/FastBlend/api.py

from .runners import AccurateModeRunner, FastModeRunner, BalancedModeRunner, InterpolationModeRunner, InterpolationModeSingleFrameRunner
from .data import VideoData, get_video_fps, save_video, search_for_images
import os
import gradio as gr


def check_input_for_blending(video_guide, video_guide_folder, video_style, video_style_folder):
    frames_guide = VideoData(video_guide, video_guide_folder)
    frames_style = VideoData(video_style, video_style_folder)
    message = ""
    if len(frames_guide) < len(frames_style):
        message += f"The number of frames mismatches. Only the first {len(frames_guide)} frames of style video will be used.\n"
        frames_style.set_length(len(frames_guide))
    elif len(frames_guide) > len(frames_style):
        message += f"The number of frames mismatches. Only the first {len(frames_style)} frames of guide video will be used.\n"
        frames_guide.set_length(len(frames_style))
    height_guide, width_guide = frames_guide.shape()
    height_style, width_style = frames_style.shape()
    if height_guide != height_style or width_guide != width_style:
        message += f"The shape of frames mismatches. The frames in style video will be resized to (height: {height_guide}, width: {width_guide})\n"
        frames_style.set_shape(height_guide, width_guide)
    return frames_guide, frames_style, message


def smooth_video(
    video_guide,
    video_guide_folder,
    video_style,
    video_style_folder,
    mode,
    window_size,
    batch_size,
    tracking_window_size,
    output_path,
    fps,
    minimum_patch_size,
    num_iter,
    guide_weight,
    initialize,
    progress = None,
):
    # input
    frames_guide, frames_style, message = check_input_for_blending(video_guide, video_guide_folder, video_style, video_style_folder)
    if len(message) > 0:
        print(message)
    # output
    if output_path == "":
        if video_style is None:
            output_path = os.path.join(video_style_folder, "output")
        else:
            output_path = os.path.join(os.path.split(video_style)[0], "output")
        os.makedirs(output_path, exist_ok=True)
        print("No valid output_path. Your video will be saved here:", output_path)
    elif not os.path.exists(output_path):
        os.makedirs(output_path, exist_ok=True)
        print("Your video will be saved here:", output_path)
    frames_path = os.path.join(output_path, "frames")
    video_path = os.path.join(output_path, "video.mp4")
    os.makedirs(frames_path, exist_ok=True)
    # process
    if mode == "Fast" or mode == "Balanced":
        tracking_window_size = 0
    ebsynth_config = {
        "minimum_patch_size": minimum_patch_size,
        "threads_per_block": 8,
        "num_iter": num_iter,
        "gpu_id": 0,
        "guide_weight": guide_weight,
        "initialize": initialize,
        "tracking_window_size": tracking_window_size,
    }
    if mode == "Fast":
        FastModeRunner().run(frames_guide, frames_style, batch_size=batch_size, window_size=window_size, ebsynth_config=ebsynth_config, save_path=frames_path)
    elif mode == "Balanced":
        BalancedModeRunner().run(frames_guide, frames_style, batch_size=batch_size, window_size=window_size, ebsynth_config=ebsynth_config, save_path=frames_path)
    elif mode == "Accurate":
        AccurateModeRunner().run(frames_guide, frames_style, batch_size=batch_size, window_size=window_size, ebsynth_config=ebsynth_config, save_path=frames_path)
    # output
    try:
        fps = int(fps)
    except:
        fps = get_video_fps(video_style) if video_style is not None else 30
    print("Fps:", fps)
    print("Saving video...")
    video_path = save_video(frames_path, video_path, num_frames=len(frames_style), fps=fps)
    print("Success!")
    print("Your frames are here:", frames_path)
    print("Your video is here:", video_path)
    return output_path, fps, video_path


class KeyFrameMatcher:
    def __init__(self):
        pass

    def extract_number_from_filename(self, file_name):
        result = []
        number = -1
        for i in file_name:
            if ord(i)>=ord("0") and ord(i)<=ord("9"):
                if number == -1:
                    number = 0
                number = number*10 + ord(i) - ord("0")
            else:
                if number != -1:
                    result.append(number)
                    number = -1
        if number != -1:
            result.append(number)
        result = tuple(result)
        return result

    def extract_number_from_filenames(self, file_names):
        numbers = [self.extract_number_from_filename(file_name) for file_name in file_names]
        min_length = min(len(i) for i in numbers)
        for i in range(min_length-1, -1, -1):
            if len(set(number[i] for number in numbers))==len(file_names):
                return [number[i] for number in numbers]
        return list(range(len(file_names)))

    def match_using_filename(self, file_names_a, file_names_b):
        file_names_b_set = set(file_names_b)
        matched_file_name = []
        for file_name in file_names_a:
            if file_name not in file_names_b_set:
                matched_file_name.append(None)
            else:
                matched_file_name.append(file_name)
        return matched_file_name

    def match_using_numbers(self, file_names_a, file_names_b):
        numbers_a = self.extract_number_from_filenames(file_names_a)
        numbers_b = self.extract_number_from_filenames(file_names_b)
        numbers_b_dict = {number: file_name for number, file_name in zip(numbers_b, file_names_b)}
        matched_file_name = []
        for number in numbers_a:
            if number in numbers_b_dict:
                matched_file_name.append(numbers_b_dict[number])
            else:
                matched_file_name.append(None)
        return matched_file_name

    def match_filenames(self, file_names_a, file_names_b):
        matched_file_name = self.match_using_filename(file_names_a, file_names_b)
        if sum([i is not None for i in matched_file_name]) > 0:
            return matched_file_name
        matched_file_name = self.match_using_numbers(file_names_a, file_names_b)
        return matched_file_name


def detect_frames(frames_path, keyframes_path):
    if not os.path.exists(frames_path) and not os.path.exists(keyframes_path):
        return "Please input the directory of guide video and rendered frames"
    elif not os.path.exists(frames_path):
        return "Please input the directory of guide video"
    elif not os.path.exists(keyframes_path):
        return "Please input the directory of rendered frames"
    frames = [os.path.split(i)[-1] for i in search_for_images(frames_path)]
    keyframes = [os.path.split(i)[-1] for i in search_for_images(keyframes_path)]
    if len(frames)==0:
        return f"No images detected in {frames_path}"
    if len(keyframes)==0:
        return f"No images detected in {keyframes_path}"
    matched_keyframes = KeyFrameMatcher().match_filenames(frames, keyframes)
    max_filename_length = max([len(i) for i in frames])
    if sum([i is not None for i in matched_keyframes])==0:
        message = ""
        for frame, matched_keyframe in zip(frames, matched_keyframes):
            message += frame + " " * (max_filename_length - len(frame) + 1)
            message += "--> No matched keyframes\n"
    else:
        message = ""
        for frame, matched_keyframe in zip(frames, matched_keyframes):
            message += frame + " " * (max_filename_length - len(frame) + 1)
            if matched_keyframe is None:
                message += "--> [to be rendered]\n"
            else:
                message += f"--> {matched_keyframe}\n"
    return message


def check_input_for_interpolating(frames_path, keyframes_path):
    # search for images
    frames = [os.path.split(i)[-1] for i in search_for_images(frames_path)]
    keyframes = [os.path.split(i)[-1] for i in search_for_images(keyframes_path)]
    # match frames
    matched_keyframes = KeyFrameMatcher().match_filenames(frames, keyframes)
    file_list = [file_name for file_name in matched_keyframes if file_name is not None]
    index_style = [i for i, file_name in enumerate(matched_keyframes) if file_name is not None]
    frames_guide = VideoData(None, frames_path)
    frames_style = VideoData(None, keyframes_path, file_list=file_list)
    # match shape
    message = ""
    height_guide, width_guide = frames_guide.shape()
    height_style, width_style = frames_style.shape()
    if height_guide != height_style or width_guide != width_style:
        message += f"The shape of frames mismatches. The rendered keyframes will be resized to (height: {height_guide}, width: {width_guide})\n"
        frames_style.set_shape(height_guide, width_guide)
    return frames_guide, frames_style, index_style, message


def interpolate_video(
    frames_path,
    keyframes_path,
    output_path,
    fps,
    batch_size,
    tracking_window_size,
    minimum_patch_size,
    num_iter,
    guide_weight,
    initialize,
    progress = None,
):
    # input
    frames_guide, frames_style, index_style, message = check_input_for_interpolating(frames_path, keyframes_path)
    if len(message) > 0:
        print(message)
    # output
    if output_path == "":
        output_path = os.path.join(keyframes_path, "output")
        os.makedirs(output_path, exist_ok=True)
        print("No valid output_path. Your video will be saved here:", output_path)
    elif not os.path.exists(output_path):
        os.makedirs(output_path, exist_ok=True)
        print("Your video will be saved here:", output_path)
    output_frames_path = os.path.join(output_path, "frames")
    output_video_path = os.path.join(output_path, "video.mp4")
    os.makedirs(output_frames_path, exist_ok=True)
    # process
    ebsynth_config = {
        "minimum_patch_size": minimum_patch_size,
        "threads_per_block": 8,
        "num_iter": num_iter,
        "gpu_id": 0,
        "guide_weight": guide_weight,
        "initialize": initialize,
        "tracking_window_size": tracking_window_size
    }
    if len(index_style)==1:
        InterpolationModeSingleFrameRunner().run(frames_guide, frames_style, index_style, batch_size=batch_size, ebsynth_config=ebsynth_config, save_path=output_frames_path)
    else:
        InterpolationModeRunner().run(frames_guide, frames_style, index_style, batch_size=batch_size, ebsynth_config=ebsynth_config, save_path=output_frames_path)
    try:
        fps = int(fps)
    except:
        fps = 30
    print("Fps:", fps)
    print("Saving video...")
    video_path = save_video(output_frames_path, output_video_path, num_frames=len(frames_guide), fps=fps)
    print("Success!")
    print("Your frames are here:", output_frames_path)
    print("Your video is here:", video_path)
    return output_path, fps, video_path


def on_ui_tabs():
    with gr.Blocks(analytics_enabled=False) as ui_component:
        with gr.Tab("Blend"):
            gr.Markdown("""
# Blend

Given a guide video and a style video, this algorithm will make the style video fluent according to the motion features of the guide video. Click [here](https://github.com/Artiprocher/sd-webui-fastblend/assets/35051019/208d902d-6aba-48d7-b7d5-cd120ebd306d) to see the example. Note that this extension doesn't support long videos. Please use short videos (e.g., several seconds). The algorithm is mainly designed for 512*512 resolution. Please use a larger `Minimum patch size` for higher resolution.
            """)
            with gr.Row():
                with gr.Column():
                    with gr.Tab("Guide video"):
                        video_guide = gr.Video(label="Guide video")
                    with gr.Tab("Guide video (images format)"):
                        video_guide_folder = gr.Textbox(label="Guide video (images format)", value="")
                with gr.Column():
                    with gr.Tab("Style video"):
                        video_style = gr.Video(label="Style video")
                    with gr.Tab("Style video (images format)"):
                        video_style_folder = gr.Textbox(label="Style video (images format)", value="")
                with gr.Column():
                    output_path = gr.Textbox(label="Output directory", value="", placeholder="Leave empty to use the directory of style video")
                    fps = gr.Textbox(label="Fps", value="", placeholder="Leave empty to use the default fps")
                    video_output = gr.Video(label="Output video", interactive=False, show_share_button=True)
            btn = gr.Button(value="Blend")
            with gr.Row():
                with gr.Column():
                    gr.Markdown("# Settings")
                    mode = gr.Radio(["Fast", "Balanced", "Accurate"], label="Inference mode", value="Fast", interactive=True)
                    window_size = gr.Slider(label="Sliding window size", value=15, minimum=1, maximum=1000, step=1, interactive=True)
                    batch_size = gr.Slider(label="Batch size", value=8, minimum=1, maximum=128, step=1, interactive=True)
                    tracking_window_size = gr.Slider(label="Tracking window size (only for accurate mode)", value=0, minimum=0, maximum=10, step=1, interactive=True)
                    gr.Markdown("## Advanced Settings")
                    minimum_patch_size = gr.Slider(label="Minimum patch size (odd number)", value=5, minimum=5, maximum=99, step=2, interactive=True)
                    num_iter = gr.Slider(label="Number of iterations", value=5, minimum=1, maximum=10, step=1, interactive=True)
                    guide_weight = gr.Slider(label="Guide weight", value=10.0, minimum=0.0, maximum=100.0, step=0.1, interactive=True)
                    initialize = gr.Radio(["identity", "random"], label="NNF initialization", value="identity", interactive=True)
                with gr.Column():
                    gr.Markdown("""
# Reference

* Output directory: the directory to save the video.
* Inference mode

|Mode|Time|Memory|Quality|Frame by frame output|Description|
|-|-|-|-|-|-|
|Fast|■|■■■|■■|No|Blend the frames using a tree-like data structure, which requires much RAM but is fast.|
|Balanced|■■|■|■■|Yes|Blend the frames naively.|
|Accurate|■■■|■|■■■|Yes|Blend the frames and align them together for higher video quality. When [batch size] >= [sliding window size] * 2 + 1, the performance is the best.|

* Sliding window size: our algorithm will blend the frames in a sliding windows. If the size is n, each frame will be blended with the last n frames and the next n frames. A large sliding window can make the video fluent but sometimes smoggy.
* Batch size: a larger batch size makes the program faster but requires more VRAM.
* Tracking window size (only for accurate mode): The size of window in which our algorithm tracks moving objects. Empirically, 1 is enough.
* Advanced settings
    * Minimum patch size (odd number): the minimum patch size used for patch matching. (Default: 5)
    * Number of iterations: the number of iterations of patch matching. (Default: 5)
    * Guide weight: a parameter that determines how much motion feature applied to the style video. (Default: 10)
    * NNF initialization: how to initialize the NNF (Nearest Neighbor Field). (Default: identity)
                    """)
            btn.click(
                smooth_video,
                inputs=[
                    video_guide,
                    video_guide_folder,
                    video_style,
                    video_style_folder,
                    mode,
                    window_size,
                    batch_size,
                    tracking_window_size,
                    output_path,
                    fps,
                    minimum_patch_size,
                    num_iter,
                    guide_weight,
                    initialize
                ],
                outputs=[output_path, fps, video_output]
            )
        with gr.Tab("Interpolate"):
            gr.Markdown("""
# Interpolate

Given a guide video and some rendered keyframes, this algorithm will render the remaining frames. Click [here](https://github.com/Artiprocher/sd-webui-fastblend/assets/35051019/3490c5b4-8f67-478f-86de-f9adc2ace16a) to see the example. The algorithm is experimental and is only tested for 512*512 resolution.
            """)
            with gr.Row():
                with gr.Column():
                    with gr.Row():
                        with gr.Column():
                            video_guide_folder_ = gr.Textbox(label="Guide video (images format)", value="")
                        with gr.Column():
                            rendered_keyframes_ = gr.Textbox(label="Rendered keyframes (images format)", value="")
                    with gr.Row():
                        detected_frames = gr.Textbox(label="Detected frames", value="Please input the directory of guide video and rendered frames", lines=9, max_lines=9, interactive=False)
                    video_guide_folder_.change(detect_frames, inputs=[video_guide_folder_, rendered_keyframes_], outputs=detected_frames)
                    rendered_keyframes_.change(detect_frames, inputs=[video_guide_folder_, rendered_keyframes_], outputs=detected_frames)
                with gr.Column():
                    output_path_ = gr.Textbox(label="Output directory", value="", placeholder="Leave empty to use the directory of rendered keyframes")
                    fps_ = gr.Textbox(label="Fps", value="", placeholder="Leave empty to use the default fps")
                    video_output_ = gr.Video(label="Output video", interactive=False, show_share_button=True)
            btn_ = gr.Button(value="Interpolate")
            with gr.Row():
                with gr.Column():
                    gr.Markdown("# Settings")
                    batch_size_ = gr.Slider(label="Batch size", value=8, minimum=1, maximum=128, step=1, interactive=True)
                    tracking_window_size_ = gr.Slider(label="Tracking window size", value=0, minimum=0, maximum=10, step=1, interactive=True)
                    gr.Markdown("## Advanced Settings")
                    minimum_patch_size_ = gr.Slider(label="Minimum patch size (odd number, larger is better)", value=15, minimum=5, maximum=99, step=2, interactive=True)
                    num_iter_ = gr.Slider(label="Number of iterations", value=5, minimum=1, maximum=10, step=1, interactive=True)
                    guide_weight_ = gr.Slider(label="Guide weight", value=10.0, minimum=0.0, maximum=100.0, step=0.1, interactive=True)
                    initialize_ = gr.Radio(["identity", "random"], label="NNF initialization", value="identity", interactive=True)
                with gr.Column():
                    gr.Markdown("""
# Reference

* Output directory: the directory to save the video.
* Batch size: a larger batch size makes the program faster but requires more VRAM.
* Tracking window size (only for accurate mode): The size of window in which our algorithm tracks moving objects. Empirically, 1 is enough.
* Advanced settings
    * Minimum patch size (odd number): the minimum patch size used for patch matching. **This parameter should be larger than that in blending. (Default: 15)**
    * Number of iterations: the number of iterations of patch matching. (Default: 5)
    * Guide weight: a parameter that determines how much motion feature applied to the style video. (Default: 10)
    * NNF initialization: how to initialize the NNF (Nearest Neighbor Field). (Default: identity)
                    """)
            btn_.click(
                interpolate_video,
                inputs=[
                    video_guide_folder_,
                    rendered_keyframes_,
                    output_path_,
                    fps_,
                    batch_size_,
                    tracking_window_size_,
                    minimum_patch_size_,
                    num_iter_,
                    guide_weight_,
                    initialize_,
                ],
                outputs=[output_path_, fps_, video_output_]
            )

        return [(ui_component, "FastBlend", "FastBlend_ui")]