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Implemented batch_size logic in outpainting_mk2

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wywywywy 2022-10-20 16:02:32 +01:00 committed by GitHub
parent 4281f255d5
commit 91efe138b3
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1 changed files with 57 additions and 49 deletions
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54
scripts/outpainting_mk_2.py
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@ -176,19 +176,21 @@ class Script(scripts.Script):
state.job_count = (1 if left > 0 else 0) + (1 if right > 0 else 0) + (1 if up > 0 else 0) + (1 if down > 0 else 0)
def expand(init, expand_pixels, is_left=False, is_right=False, is_top=False, is_bottom=False):
def expand(init, count, expand_pixels, is_left=False, is_right=False, is_top=False, is_bottom=False):
is_horiz = is_left or is_right
is_vert = is_top or is_bottom
pixels_horiz = expand_pixels if is_horiz else 0
pixels_vert = expand_pixels if is_vert else 0
res_w = init.width + pixels_horiz
res_h = init.height + pixels_vert
images_to_process = []
for n in range(count):
res_w = init[n].width + pixels_horiz
res_h = init[n].height + pixels_vert
process_res_w = math.ceil(res_w / 64) * 64
process_res_h = math.ceil(res_h / 64) * 64
img = Image.new("RGB", (process_res_w, process_res_h))
img.paste(init, (pixels_horiz if is_left else 0, pixels_vert if is_top else 0))
img.paste(init[n], (pixels_horiz if is_left else 0, pixels_vert if is_top else 0))
mask = Image.new("RGB", (process_res_w, process_res_h), "white")
draw = ImageDraw.Draw(mask)
draw.rectangle((
@ -203,8 +205,10 @@ class Script(scripts.Script):
noised = get_matched_noise(np_image, np_mask, noise_q, color_variation)
out = Image.fromarray(np.clip(noised * 255., 0., 255.).astype(np.uint8), mode="RGB")
target_width = min(process_width, init.width + pixels_horiz) if is_horiz else img.width
target_height = min(process_height, init.height + pixels_vert) if is_vert else img.height
target_width = min(process_width, init[n].width + pixels_horiz) if is_horiz else img.width
target_height = min(process_height, init[n].height + pixels_vert) if is_vert else img.height
p.width = target_width if is_horiz else img.width
p.height = target_height if is_vert else img.height
crop_region = (
0 if is_left else out.width - target_width,
@ -212,14 +216,13 @@ class Script(scripts.Script):
target_width if is_left else out.width,
target_height if is_top else out.height,
)
mask = mask.crop(crop_region)
p.image_mask = mask
image_to_process = out.crop(crop_region)
mask = mask.crop(crop_region)
images_to_process.append(image_to_process)
p.width = target_width if is_horiz else img.width
p.height = target_height if is_vert else img.height
p.init_images = [image_to_process]
p.image_mask = mask
p.init_images = images_to_process
latent_mask = Image.new("RGB", (p.width, p.height), "white")
draw = ImageDraw.Draw(latent_mask)
@ -232,43 +235,48 @@ class Script(scripts.Script):
p.latent_mask = latent_mask
proc = process_images(p)
proc_img = proc.images[0]
if initial_seed_and_info[0] is None:
initial_seed_and_info[0] = proc.seed
initial_seed_and_info[1] = proc.info
for proc_img in proc.images:
out.paste(proc_img, (0 if is_left else out.width - proc_img.width, 0 if is_top else out.height - proc_img.height))
out = out.crop((0, 0, res_w, res_h))
return out
return proc.images
batch_count = p.n_iter
batch_size = p.batch_size
p.n_iter = 1
state.job_count = batch_count
all_images = []
all_processed_images = []
for i in range(batch_count):
img = init_image
state.job = f"Batch {i + 1} out of {state.job_count}"
imgs = [init_img] * batch_size
state.job = f"Batch {i + 1} out of {batch_count}"
if left > 0:
img = expand(img, left, is_left=True)
imgs = expand(imgs, batch_size, left, is_left=True)
if right > 0:
img = expand(img, right, is_right=True)
imgs = expand(imgs, batch_size, right, is_right=True)
if up > 0:
img = expand(img, up, is_top=True)
imgs = expand(imgs, batch_size, up, is_top=True)
if down > 0:
img = expand(img, down, is_bottom=True)
imgs = expand(imgs, batch_size, down, is_bottom=True)
all_images.append(img)
all_processed_images += imgs
combined_grid_image = images.image_grid(all_processed_images)
all_images = all_processed_images
combined_grid_image = images.image_grid(all_images)
if opts.return_grid:
all_images = [combined_grid_image] + all_images
all_images = [combined_grid_image] + all_processed_images
res = Processed(p, all_images, initial_seed_and_info[0], initial_seed_and_info[1])
if opts.samples_save:
for img in all_processed_images:
images.save_image(img, p.outpath_samples, "", res.seed, p.prompt, opts.grid_format, info=res.info, p=p)
if opts.grid_save: