Sygil-Dev/sygil-webui
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Revert "Original grid captions bugfix"

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This reverts commit 9119ca4b57.
This commit is contained in:
hlky 2022-08-30 10:19:45 +01:00
parent c620391c91
commit 73754a1b29
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GPG Key ID: 55A99F1E80D907D5
1 changed files with 7 additions and 17 deletions
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webui.py
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@ -399,13 +399,10 @@ def image_grid(imgs, batch_size, force_n_rows=None, captions=None):
for i, img in enumerate(imgs):
grid.paste(img, box=(i % cols * w, i // cols * h))
try:
if captions:
d = ImageDraw.Draw( grid )
size = d.textbbox( (0,0), captions[i], font=fnt, stroke_width=2, align="center" )
d.multiline_text((i % cols * w + w/2, i // cols * h + h - size[3]), captions[i], font=fnt, fill=(255,255,255), stroke_width=2, stroke_fill=(0,0,0), anchor="mm", align="center")
except:
pass
if captions:
d = ImageDraw.Draw( grid )
size = d.textbbox( (0,0), captions[i], font=fnt, stroke_width=2, align="center" )
d.multiline_text((i % cols * w + w/2, i // cols * h + h - size[3]), captions[i], font=fnt, fill=(255,255,255), stroke_width=2, stroke_fill=(0,0,0), anchor="mm", align="center")
return grid
@ -726,17 +723,14 @@ def process_images(
precision_scope = autocast if opt.precision == "autocast" else nullcontext
output_images = []
new_prompt_matrix_parts = []
stats = []
with torch.no_grad(), precision_scope("cuda"), (model.ema_scope() if not opt.optimized else nullcontext()):
init_data = func_init()
tic = time.time()
for n in range(n_iter):
print(f"Iteration: {n+1}/{n_iter}")
prompts = all_prompts[n * batch_size:(n + 1) * batch_size]
parts = prompt_matrix_parts[n * batch_size:(n + 1) * batch_size]
seeds = all_seeds[n * batch_size:(n + 1) * batch_size]
if opt.optimized:
@ -816,7 +810,6 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
output_images.append(gfpgan_image) #287
new_prompt_matrix_parts.append(parts[i]+"\ngfpgan")
if use_RealESRGAN and RealESRGAN is not None and not use_GFPGAN:
skip_save = True # #287 >_>
@ -834,7 +827,6 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
output_images.append(esrgan_image) #287
new_prompt_matrix_parts.append(parts[i]+"\nesrgan4x")
if use_RealESRGAN and RealESRGAN is not None and use_GFPGAN and GFPGAN is not None:
skip_save = True # #287 >_>
@ -854,7 +846,6 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
output_images.append(gfpgan_esrgan_image) #287
new_prompt_matrix_parts.append(parts[i]+"\ngfpgan-esrgan4x")
if init_mask:
@ -881,7 +872,6 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
normalize_prompt_weights, use_GFPGAN, write_info_files, prompt_matrix, init_img, uses_loopback, uses_random_seed_loopback, skip_save,
skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoising_strength, resize_mode)
output_images.append(image)
new_prompt_matrix_parts.append(parts[i])
if opt.optimized:
mem = torch.cuda.memory_allocated()/1e6
@ -892,11 +882,11 @@ skip_grid, sort_samples, sampler_name, ddim_eta, n_iter, batch_size, i, denoisin
if (prompt_matrix or not skip_grid) and not do_not_save_grid:
if prompt_matrix:
if prompt.startswith("@"):
grid = image_grid(output_images, batch_size, force_n_rows=frows, captions=new_prompt_matrix_parts)
grid = image_grid(output_images, batch_size, force_n_rows=frows, captions=prompt_matrix_parts)
else:
grid = image_grid(output_images, batch_size, force_n_rows=1 << ((len(new_prompt_matrix_parts)-1)//2))
grid = image_grid(output_images, batch_size, force_n_rows=1 << ((len(prompt_matrix_parts)-1)//2))
try:
grid = draw_prompt_matrix(grid, width, height, new_prompt_matrix_parts)
grid = draw_prompt_matrix(grid, width, height, prompt_matrix_parts)
except:
import traceback
print("Error creating prompt_matrix text:", file=sys.stderr)