| import os |
| import platform |
| import numpy as np |
| from tqdm import trange |
| import math |
| import subprocess as sp |
| import string |
| import random |
| from functools import reduce |
| import re |
|
|
| import modules.scripts as scripts |
| import gradio as gr |
|
|
| from modules import processing, shared, sd_samplers, images |
| from modules.processing import Processed |
| from modules.sd_samplers import samplers |
| from modules.shared import opts, cmd_opts, state |
| import subprocess |
|
|
|
|
| wave_completed_regex = r'@wave_completed\(([\-]?[0-9]*\.?[0-9]+), ?([\-]?[0-9]*\.?[0-9]+)\)' |
| wave_remaining_regex = r'@wave_remaining\(([\-]?[0-9]*\.?[0-9]+), ?([\-]?[0-9]*\.?[0-9]+)\)' |
|
|
| def run_cmd(cmd): |
| cmd = list(map(lambda arg: str(arg), cmd)) |
| print("Executing %s" % " ".join(cmd)) |
| popen_params = {"stdout": sp.DEVNULL, "stderr": sp.PIPE, "stdin": sp.DEVNULL} |
|
|
| if os.name == "nt": |
| popen_params["creationflags"] = 0x08000000 |
|
|
| proc = sp.Popen(cmd, **popen_params) |
| out, err = proc.communicate() |
| proc.stderr.close() |
|
|
| if proc.returncode: |
| raise IOError(err.decode("utf8")) |
|
|
| del proc |
|
|
| def encode_video(input_pattern, starting_number, output_dir, fps, quality, encoding, create_segments, segment_duration, ffmpeg_path): |
| two_pass = (encoding == "VP9 (webm)") |
| alpha_channel = ("webm" in encoding) |
| suffix = "webm" if "webm" in encoding else "mp4" |
| output_location = output_dir + f".{suffix}" |
|
|
| encoding_lib = { |
| "VP9 (webm)": "libvpx-vp9", |
| "VP8 (webm)": "libvpx", |
| "H.264 (mp4)": "libx264", |
| "H.265 (mp4)": "libx265", |
| }[encoding] |
|
|
| args = [ |
| "-framerate", fps, |
| "-start_number", int(starting_number), |
| "-i", input_pattern, |
| "-c:v", encoding_lib, |
| "-b:v","0", |
| "-crf", quality, |
| ] |
|
|
| if encoding_lib == "libvpx-vp9": |
| args += ["-pix_fmt", "yuva420p"] |
| |
| if(ffmpeg_path == ""): |
| ffmpeg_path = "ffmpeg" |
| if(platform.system == "Windows"): |
| ffmpeg_path += ".exe" |
|
|
| print("\n\n") |
| if two_pass: |
| first_pass_args = args + [ |
| "-pass", "1", |
| "-an", |
| "-f", "null", |
| os.devnull |
| ] |
|
|
| second_pass_args = args + [ |
| "-pass", "2", |
| output_location |
| ] |
|
|
| print("Running first pass ffmpeg encoding") |
|
|
| run_cmd([ffmpeg_path] + first_pass_args) |
| print("Running second pass ffmpeg encoding. This could take awhile...") |
| run_cmd([ffmpeg_path] + second_pass_args) |
| else: |
| print("Running ffmpeg encoding. This could take awhile...") |
| run_cmd([ffmpeg_path] + args + [output_location]) |
|
|
| if(create_segments): |
| print("Segmenting video") |
| run_cmd([ffmpeg_path] + [ |
| "-i", output_location, |
| "-f", "segment", |
| "-segment_time", segment_duration, |
| "-vcodec", "copy", |
| "-acodec", "copy", |
| f"{output_dir}.%d.{suffix}" |
| ]) |
| |
| def set_weights(match_obj, wave_progress): |
| weight_0 = 0 |
| weight_1 = 0 |
| if match_obj.group(1) is not None: |
| weight_0 = float(match_obj.group(1)) |
| if match_obj.group(2) is not None: |
| weight_1 = float(match_obj.group(2)) |
| |
| max_weight = max(weight_0, weight_1) |
| min_weight = min(weight_0, weight_1) |
| |
| weight_range = max_weight - min_weight |
| weight = min_weight + weight_range * wave_progress |
| return str(weight) |
|
|
|
|
| class Script(scripts.Script): |
| def title(self): |
| return "Loopback Wave V1.4.1" |
|
|
| def show(self, is_img2img): |
| return is_img2img |
|
|
| def ui(self, is_img2img): |
| frames = gr.Slider(minimum=1, maximum=2048, step=1, label='Frames', value=100) |
| frames_per_wave = gr.Slider(minimum=0, maximum=120, step=1, label='Frames Per Wave', value=20) |
| denoising_strength_change_amplitude = gr.Slider(minimum=0, maximum=1, step=0.01, label='Max additional denoise', value=0.6) |
| denoising_strength_change_offset = gr.Number(minimum=0, maximum=180, step=1, label='Wave offset (ignore this if you don\'t know what it means)', value=0) |
| initial_image_number = gr.Number(minimum=0, label='Initial generated image number', value=0) |
|
|
| save_prompts = gr.Checkbox(label='Save prompts as text file', value=True) |
| prompts = gr.Textbox(label="Prompt Changes", lines=5, value="") |
|
|
| save_video = gr.Checkbox(label='Save results as video', value=True) |
| output_dir = gr.Textbox(label="Video Name", lines=1, value="") |
| video_fps = gr.Slider(minimum=1, maximum=120, step=1, label='Frames per second', value=10) |
| video_quality = gr.Slider(minimum=0, maximum=60, step=1, label='Video Quality (crf)', value=40) |
| video_encoding = gr.Dropdown(label='Video encoding', value="VP9 (webm)", choices=["VP9 (webm)", "VP8 (webm)", "H.265 (mp4)", "H.264 (mp4)"]) |
| ffmpeg_path = gr.Textbox(label="ffmpeg binary. Only set this if it fails otherwise.", lines=1, value="") |
|
|
| segment_video = gr.Checkbox(label='Cut video in to segments', value=True) |
| video_segment_duration = gr.Slider(minimum=10, maximum=60, step=1, label='Video Segment Duration (seconds)', value=20) |
|
|
|
|
| return [frames, denoising_strength_change_amplitude, frames_per_wave, denoising_strength_change_offset,initial_image_number, prompts, save_prompts, save_video, output_dir, video_fps, video_quality, video_encoding, ffmpeg_path, segment_video, video_segment_duration] |
|
|
| def run(self, p, frames, denoising_strength_change_amplitude, frames_per_wave, denoising_strength_change_offset, initial_image_number, prompts: str,save_prompts, save_video, output_dir, video_fps, video_quality, video_encoding, ffmpeg_path, segment_video, video_segment_duration): |
| processing.fix_seed(p) |
| batch_count = p.n_iter |
| p.extra_generation_params = { |
| "Max Additional Denoise": denoising_strength_change_amplitude, |
| "Frames per wave": frames_per_wave, |
| "Wave Offset": denoising_strength_change_offset, |
| } |
|
|
| |
| p.do_not_save_samples = True |
|
|
| changes_dict = {} |
|
|
|
|
| p.batch_size = 1 |
| p.n_iter = 1 |
|
|
| output_images, info = None, None |
| initial_seed = None |
| initial_info = None |
|
|
| grids = [] |
| all_images = [] |
| original_init_image = p.init_images |
| state.job_count = frames * batch_count |
|
|
| initial_color_corrections = [processing.setup_color_correction(p.init_images[0])] |
| initial_denoising_strength = p.denoising_strength |
|
|
| if(output_dir==""): |
| output_dir = str(p.seed) |
| else: |
| output_dir = output_dir + "-" + str(p.seed) |
|
|
| loopback_wave_path = os.path.join(p.outpath_samples, "loopback-wave") |
| loopback_wave_images_path = os.path.join(loopback_wave_path, output_dir) |
|
|
| os.makedirs(loopback_wave_images_path, exist_ok=True) |
|
|
| p.outpath_samples = loopback_wave_images_path |
| |
| prompts = prompts.strip() |
| |
| if save_prompts: |
| with open(loopback_wave_images_path + "-prompts.txt", "w") as f: |
| generation_settings = [ |
| "Generation Settings", |
| f"Total Frames: {frames}", |
| f"Frames Per Wave: {frames_per_wave}", |
| f"Wave Offset: {denoising_strength_change_offset}", |
| f"Base Denoising Strength: {initial_denoising_strength}", |
| f"Max Additional Denoise: {denoising_strength_change_amplitude}", |
| f"Initial Image Number: {initial_image_number}", |
| "", |
| "Video Encoding Settings", |
| f"Save Video: {save_video}" |
| ] |
| |
| if save_video: |
| generation_settings = generation_settings + [ |
| f"Framerate: {video_fps}", |
| f"Quality: {video_quality}", |
| f"Encoding: {video_encoding}", |
| f"Create Segmented Video: {segment_video}" |
| ] |
| |
| if segment_video: |
| generation_settings = generation_settings + [f"Segment Duration: {video_segment_duration}"] |
| |
| generation_settings = generation_settings + [ |
| "", |
| "Prompt Details", |
| "Initial Prompt:" + p.prompt, |
| "", |
| "Negative Prompt:" + p.negative_prompt, |
| "", |
| "Frame change prompts:", |
| prompts |
| ] |
| |
|
|
|
|
| f.write('\n'.join(generation_settings)) |
|
|
| if prompts: |
| lines = prompts.split("\n") |
| for prompt_line in lines: |
| params = prompt_line.split("::") |
| if len(params) == 2: |
| changes_dict[params[0]] = { "prompt": params[1] } |
| elif len(params) == 3: |
| changes_dict[params[0]] = { "seed": params[1], "prompt": params[2] } |
| else: |
| raise IOError(f"Invalid input in prompt line: {prompt_line}") |
| |
| raw_prompt = p.prompt |
| |
| for n in range(batch_count): |
| history = [] |
|
|
| |
| p.init_images = original_init_image |
| |
| seed_state = "adding" |
| current_seed = p.seed |
|
|
| for i in range(frames): |
| current_seed = p.seed |
| state.job = "" |
| |
| if str(i) in changes_dict: |
| raw_prompt = changes_dict[str(i)]["prompt"] |
| state.job = "New prompt: %s\n" % raw_prompt |
| |
| if "seed" in changes_dict[str(i)]: |
| current_seed = changes_dict[str(i)]["seed"] |
| |
| if current_seed.startswith("+"): |
| seed_state = "adding" |
| current_seed = current_seed.strip("+") |
| elif current_seed.startswith("-"): |
| seed_state = "subtracting" |
| current_seed = current_seed.strip("-") |
| else: |
| seed_state = "constant" |
| |
| current_seed = int(current_seed) |
| p.seed = current_seed |
| |
| |
| |
| p.n_iter = 1 |
| p.batch_size = 1 |
| p.do_not_save_grid = True |
|
|
| if opts.img2img_color_correction: |
| p.color_corrections = initial_color_corrections |
| |
| |
| wave_progress = float(1)/(float(frames_per_wave - 1))*float(((float(i)%float(frames_per_wave)) + ((float(1)/float(180))*denoising_strength_change_offset))) |
| print(wave_progress) |
| new_prompt = re.sub(wave_completed_regex, lambda x: set_weights(x, wave_progress), raw_prompt) |
| new_prompt = re.sub(wave_remaining_regex, lambda x: set_weights(x, 1 - wave_progress), new_prompt) |
| p.prompt = new_prompt |
| |
| print(new_prompt) |
|
|
| denoising_strength_change_rate = 180/frames_per_wave |
|
|
| cos = abs(math.cos(math.radians(i*denoising_strength_change_rate + denoising_strength_change_offset))) |
| p.denoising_strength = initial_denoising_strength + denoising_strength_change_amplitude - (cos * denoising_strength_change_amplitude) |
|
|
| state.job += f"Iteration {i + 1}/{frames}, batch {n + 1}/{batch_count}. Denoising Strength: {p.denoising_strength}" |
|
|
| processed = processing.process_images(p) |
|
|
| if initial_seed is None: |
| initial_seed = processed.seed |
| initial_info = processed.info |
|
|
| init_img = processed.images[0] |
|
|
| p.init_images = [init_img] |
| |
| if seed_state == "adding": |
| p.seed = processed.seed + 1 |
| elif seed_state == "subtracting": |
| p.seed = processed.seed - 1 |
| |
| image_number = int(initial_image_number + i) |
| images.save_image(init_img, p.outpath_samples, "", processed.seed, processed.prompt, forced_filename=str(image_number)) |
|
|
| history.append(init_img) |
|
|
| grid = images.image_grid(history, rows=1) |
| if opts.grid_save: |
| images.save_image(grid, p.outpath_grids, "grid", initial_seed, p.prompt, opts.grid_format, info=info, short_filename=not opts.grid_extended_filename, grid=True, p=p) |
|
|
| grids.append(grid) |
| all_images += history |
|
|
| if opts.return_grid: |
| all_images = grids + all_images |
|
|
| if save_video: |
| input_pattern = os.path.join(loopback_wave_images_path, "%d.png") |
| encode_video(input_pattern, initial_image_number, loopback_wave_images_path, video_fps, video_quality, video_encoding, segment_video, video_segment_duration, ffmpeg_path) |
|
|
| processed = Processed(p, all_images, initial_seed, initial_info) |
|
|
| return processed |
|
|
|
|
|
|