mirror of
https://github.com/lllyasviel/stable-diffusion-webui-forge.git
synced 2026-07-21 21:01:24 +08:00
209 lines
7.4 KiB
Python
209 lines
7.4 KiB
Python
import os
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import av
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import numpy as np
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from PIL import Image
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from tqdm import tqdm
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from modules import devices, images, infotext_utils, scripts, scripts_postprocessing, shared, ui_common
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from modules.shared import opts
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def run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir, show_extras_results, _, *args, save_output: bool = True):
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devices.torch_gc()
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shared.state.begin(job="extras")
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outputs = []
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if isinstance(image, dict):
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image = image["composite"]
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def get_images(extras_mode, image, image_folder, input_dir):
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if extras_mode == 1:
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for img in image_folder:
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if isinstance(img, Image.Image):
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image = images.fix_image(img)
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fn = ""
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else:
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image = images.read(os.path.abspath(img.name))
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fn = os.path.splitext(img.name)[0]
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yield image, fn
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elif extras_mode == 2:
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assert not shared.cmd_opts.hide_ui_dir_config, "--hide-ui-dir-config option must be disabled"
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assert input_dir, "input directory not selected"
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image_list = shared.listfiles(input_dir)
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for filename in image_list:
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yield filename, filename
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else:
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assert image, "image not selected"
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yield image, None
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if extras_mode == 2 and output_dir != "":
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outpath = output_dir
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else:
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outpath = opts.outdir_samples or opts.outdir_extras_samples
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infotext = ""
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data_to_process = list(get_images(extras_mode, image, image_folder, input_dir))
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shared.state.job_count = len(data_to_process)
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for image_placeholder, name in data_to_process:
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image_data: Image.Image
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shared.state.nextjob()
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shared.state.textinfo = name
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shared.state.skipped = False
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if shared.state.interrupted or shared.state.stopping_generation:
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break
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if isinstance(image_placeholder, str):
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try:
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image_data = images.read(image_placeholder)
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except Exception:
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continue
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else:
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image_data = image_placeholder
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image_data = image_data if image_data.mode in ("RGBA", "RGB") else image_data.convert("RGB")
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parameters, existing_pnginfo = images.read_info_from_image(image_data)
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if parameters:
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existing_pnginfo["parameters"] = parameters
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initial_pp = scripts_postprocessing.PostprocessedImage(image_data)
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scripts.scripts_postproc.run(initial_pp, args)
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if shared.state.skipped:
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continue
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used_suffixes = {}
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for pp in [initial_pp, *initial_pp.extra_images]:
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suffix = pp.get_suffix(used_suffixes)
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if opts.use_original_name_batch and name is not None:
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basename = os.path.splitext(os.path.basename(name))[0]
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forced_filename = basename + suffix
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else:
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basename = ""
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forced_filename = None
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infotext = ", ".join([k if k == v else f"{k}: {infotext_utils.quote(v)}" for k, v in pp.info.items() if v is not None])
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if opts.enable_pnginfo:
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pp.image.info = existing_pnginfo
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shared.state.assign_current_image(pp.image)
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if save_output:
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fullfn, _ = images.save_image(pp.image, path=outpath, basename=basename, extension=opts.samples_format, info=infotext, short_filename=True, no_prompt=True, grid=False, pnginfo_section_name="postprocessing", existing_info=existing_pnginfo, forced_filename=forced_filename, suffix=suffix)
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if extras_mode != 2 or show_extras_results:
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outputs.append(pp.image)
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devices.torch_gc()
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shared.state.end()
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return outputs, ui_common.plaintext_to_html(infotext), ""
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def run_postprocessing_video(_mode, _img, _folder, _in_dir, _out_dir, _show, video_input, *args, save_output: bool = True):
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devices.torch_gc()
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shared.state.begin(job="extras")
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outputs: list[np.ndarray] = []
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container = av.open(video_input)
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video_stream = container.streams.best("video")
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frames = video_stream.frames
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def get_frames():
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for frame in tqdm(container.decode(video=0), desc="Processing Video", total=frames, unit="frame"):
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yield frame.to_image()
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infotext = None
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shared.state.job_count = frames
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for i, image_data in enumerate(get_frames()):
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shared.state.nextjob()
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shared.state.textinfo = str(i)
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shared.state.skipped = False
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if shared.state.interrupted or shared.state.stopping_generation:
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break
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initial_pp = scripts_postprocessing.PostprocessedImage(image_data)
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scripts.scripts_postproc.run(initial_pp, args)
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if shared.state.skipped:
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continue
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if infotext is None:
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infotext = ", ".join([k if k == v else f"{k}: {infotext_utils.quote(v)}" for k, v in initial_pp.info.items() if v is not None])
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shared.state.assign_current_image(initial_pp.image)
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outputs.append(np.array(initial_pp.image, dtype=np.uint8))
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if not (shared.state.interrupted or shared.state.stopping_generation):
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images.save_video(
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os.path.splitext(os.path.basename(video_input))[0],
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outputs,
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fps=round(float(container.streams.video[0].average_rate)),
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basename=None,
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info=infotext,
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audio_copy=video_input,
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)
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container.close()
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devices.torch_gc()
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shared.state.end()
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return outputs[-1:], ui_common.plaintext_to_html(infotext), ""
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def run_postprocessing_webui(id_task, *args, **kwargs):
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if args[0] == 3:
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return run_postprocessing_video(*args, **kwargs)
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else:
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return run_postprocessing(*args, **kwargs)
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def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, upscale_first: bool, save_output: bool = True, max_side_length: int = 0):
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"""old handler for API"""
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args = scripts.scripts_postproc.create_args_for_run(
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{
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"Upscale": {
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"upscale_enabled": True,
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"upscale_mode": resize_mode,
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"upscale_by": upscaling_resize,
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"max_side_length": max_side_length,
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"upscale_to_width": upscaling_resize_w,
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"upscale_to_height": upscaling_resize_h,
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"upscale_crop": upscaling_crop,
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"upscaler_1_name": extras_upscaler_1,
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"upscaler_2_name": extras_upscaler_2,
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"upscaler_2_visibility": extras_upscaler_2_visibility,
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},
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"GFPGAN": {
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"enable": True,
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"gfpgan_visibility": gfpgan_visibility,
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},
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"CodeFormer": {
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"enable": True,
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"codeformer_visibility": codeformer_visibility,
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"codeformer_weight": codeformer_weight,
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},
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}
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)
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return run_postprocessing(extras_mode, image, image_folder, input_dir, output_dir, show_extras_results, *args, save_output=save_output)
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