Implemented batch_size logic in outpainting_mk2
This commit is contained in:
parent
4281f255d5
commit
91efe138b3
|
@ -176,50 +176,53 @@ 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
|
||||
process_res_w = math.ceil(res_w / 64) * 64
|
||||
process_res_h = math.ceil(res_h / 64) * 64
|
||||
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))
|
||||
mask = Image.new("RGB", (process_res_w, process_res_h), "white")
|
||||
draw = ImageDraw.Draw(mask)
|
||||
draw.rectangle((
|
||||
expand_pixels + mask_blur if is_left else 0,
|
||||
expand_pixels + mask_blur if is_top else 0,
|
||||
mask.width - expand_pixels - mask_blur if is_right else res_w,
|
||||
mask.height - expand_pixels - mask_blur if is_bottom else res_h,
|
||||
), fill="black")
|
||||
img = Image.new("RGB", (process_res_w, process_res_h))
|
||||
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((
|
||||
expand_pixels + mask_blur if is_left else 0,
|
||||
expand_pixels + mask_blur if is_top else 0,
|
||||
mask.width - expand_pixels - mask_blur if is_right else res_w,
|
||||
mask.height - expand_pixels - mask_blur if is_bottom else res_h,
|
||||
), fill="black")
|
||||
|
||||
np_image = (np.asarray(img) / 255.0).astype(np.float64)
|
||||
np_mask = (np.asarray(mask) / 255.0).astype(np.float64)
|
||||
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")
|
||||
np_image = (np.asarray(img) / 255.0).astype(np.float64)
|
||||
np_mask = (np.asarray(mask) / 255.0).astype(np.float64)
|
||||
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,
|
||||
0 if is_top else out.height - target_height,
|
||||
target_width if is_left else out.width,
|
||||
target_height if is_top else out.height,
|
||||
)
|
||||
crop_region = (
|
||||
0 if is_left else out.width - target_width,
|
||||
0 if is_top else out.height - target_height,
|
||||
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)
|
||||
image_to_process = out.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)
|
||||
|
@ -232,44 +235,49 @@ 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
|
||||
|
||||
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
|
||||
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 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:
|
||||
images.save_image(img, p.outpath_samples, "", res.seed, p.prompt, opts.grid_format, info=res.info, p=p)
|
||||
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:
|
||||
images.save_image(combined_grid_image, p.outpath_grids, "grid", res.seed, p.prompt, opts.grid_format, info=res.info, short_filename=not opts.grid_extended_filename, grid=True, p=p)
|
||||
|
|
Loading…
Reference in New Issue