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#354 + playground.py update
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hlky
parent
cfc9f00a93
commit
dffdaaaf77
@ -153,7 +153,7 @@ def draw_gradio_ui(opt, img2img=lambda x: x, txt2img=lambda x: x, txt2img_defaul
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value=3, visible=False)
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img2img_resize = gr.Radio(label="Resize mode",
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choices=["Just resize", "Crop and resize", "Resize and fill"],
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choices=["Just resize"],
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type="index",
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value=img2img_resize_modes[img2img_defaults['resize_mode']])
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32
webui.py
32
webui.py
@ -847,13 +847,10 @@ def process_images(
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if use_GFPGAN and GFPGAN is not None and not use_RealESRGAN:
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skip_save = True # #287 >_>
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torch_gc()
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cropped_faces, restored_faces, restored_img = GFPGAN.enhance(x_sample[:,:,::-1], has_aligned=False, only_center_face=False, paste_back=True)
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cropped_faces, restored_faces, restored_img = GFPGAN.enhance(original_sample[:,:,::-1], has_aligned=False, only_center_face=False, paste_back=True)
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gfpgan_sample = restored_img[:,:,::-1]
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gfpgan_image = Image.fromarray(gfpgan_sample)
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gfpgan_filename = original_filename + '-gfpgan'
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save_sample(image, sample_path_i, original_filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
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normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
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save_sample(gfpgan_image, sample_path_i, gfpgan_filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
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normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
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@ -866,13 +863,10 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
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torch_gc()
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if RealESRGAN.model.name != realesrgan_model_name:
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try_loading_RealESRGAN(realesrgan_model_name)
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output, img_mode = RealESRGAN.enhance(x_sample[:,:,::-1])
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output, img_mode = RealESRGAN.enhance(original_sample[:,:,::-1])
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esrgan_filename = original_filename + '-esrgan4x'
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esrgan_sample = output[:,:,::-1]
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esrgan_image = Image.fromarray(esrgan_sample)
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save_sample(image, sample_path_i, original_filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
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normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
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save_sample(esrgan_image, sample_path_i, esrgan_filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
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normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
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@ -891,9 +885,6 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
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gfpgan_esrgan_filename = original_filename + '-gfpgan-esrgan4x'
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gfpgan_esrgan_sample = output[:,:,::-1]
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gfpgan_esrgan_image = Image.fromarray(gfpgan_esrgan_sample)
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save_sample(image, sample_path_i, original_filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
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normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
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save_sample(gfpgan_esrgan_image, sample_path_i, gfpgan_esrgan_filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
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normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
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@ -901,7 +892,7 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
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if simple_templating:
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grid_captions.append( captions[i] + "\ngfpgan_esrgan" )
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if not skip_save or (not use_GFPGAN or not use_RealESRGAN):
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if not skip_save:
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save_sample(image, sample_path_i, filename, jpg_sample, prompts, seeds, width, height, steps, cfg_scale,
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normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
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skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
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@ -1126,7 +1117,7 @@ def img2img(prompt: str, image_editor_mode: str, init_info, mask_mode: str, mask
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if image_editor_mode == 'Mask':
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init_img = init_info["image"]
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init_img = init_img.convert("RGBA")
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init_img = init_img.convert("RGB")
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init_img = resize_image(resize_mode, init_img, width, height)
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init_mask = init_info["mask"]
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init_mask = init_mask.convert("RGB")
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@ -1134,7 +1125,7 @@ def img2img(prompt: str, image_editor_mode: str, init_info, mask_mode: str, mask
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keep_mask = mask_mode == 0
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init_mask = init_mask if keep_mask else ImageOps.invert(init_mask)
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else:
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init_img = init_info
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init_img = init_info.convert("RGB")
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init_mask = None
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keep_mask = False
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@ -1150,7 +1141,7 @@ def img2img(prompt: str, image_editor_mode: str, init_info, mask_mode: str, mask
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mask_channel = None
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if image_editor_mode == "Uncrop":
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alpha = init_img.convert("RGBA")
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alpha = init_img.convert("RGB")
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alpha = resize_image(resize_mode, alpha, width // 8, height // 8)
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mask_channel = alpha.split()[-1]
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mask_channel = mask_channel.filter(ImageFilter.GaussianBlur(4))
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@ -1229,7 +1220,7 @@ def img2img(prompt: str, image_editor_mode: str, init_info, mask_mode: str, mask
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return samples_ddim
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try:
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if loopback:
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output_images, info = None, None
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history = []
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@ -1329,14 +1320,7 @@ def img2img(prompt: str, image_editor_mode: str, init_info, mask_mode: str, mask
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del sampler
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return output_images, seed, info, stats
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except RuntimeError as e:
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err = e
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err_msg = f'CRASHED:<br><textarea rows="5" style="color:white;background: black;width: -webkit-fill-available;font-family: monospace;font-size: small;font-weight: bold;">{str(e)}</textarea><br><br>Please wait while the program restarts.'
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stats = err_msg
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return [], seed, 'err', stats
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finally:
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if err:
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crash(err, '!!Runtime error (img2img)!!')
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prompt_parser = re.compile("""
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(?P<prompt> # capture group for 'prompt'
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@ -100,7 +100,9 @@ txt2img_defaults = {
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'height': 512,
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'width': 512,
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'fp': None,
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'submit_on_enter': 'Yes'
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'submit_on_enter': 'Yes',
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'variant_amount': 0,
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'variant_seed': ''
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}
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if 'txt2img' in user_defaults:
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