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infinite-zoom-automatic1111-webui
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Include alpha masks - preview

exit_image
Charles Fettinger 2023-04-26 02:03:06 -07:00
parent 601f874d27
commit 379b0f51fc
6 changed files with 71 additions and 35 deletions
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11
iz_helpers/image.py
View File

@ -42,3 +42,14 @@ def open_image(image_path):
img = Image.open(image_path)
return img
def apply_alpha_mask(current_image, mask_image):
# Resize the mask to match the current image size
mask_image = mask_image.resize(current_image.size)
# Apply the mask as the alpha layer of the current image
result_image = current_image.copy()
result_image.putalpha(mask_image.convert('L')) # convert to grayscale
return result_image

8
iz_helpers/promptschema.json
View File

@ -26,6 +26,12 @@
},
{
"type": "string"
},
{
"type": "string"
},
{
"type": "boolean"
}
],
"minItems": 0,
@ -39,7 +45,7 @@
"items": {
"type": "string"
},
"minItems": 3
"minItems": 5
}
},
"required": ["data", "headers"]

67
iz_helpers/run.py
View File

@ -11,7 +11,7 @@ from .helpers import (
do_upscaleImg,
)
from .sd_helpers import renderImg2Img, renderTxt2Img
from .image import shrink_and_paste_on_blank, open_image
from .image import shrink_and_paste_on_blank, open_image, apply_alpha_mask
from .video import write_video
@ -112,14 +112,20 @@ def create_zoom_single(
prompts = {}
prompt_images = {}
prompt_alpha_mask_images = {}
prompt_image_is_keyframe = {}
for x in prompts_array:
try:
key = int(x[0])
value = str(x[1])
file_loc = str(x[2])
alpha_mask_loc = str(x[3])
is_keyframe = bool(x[4])
prompts[key] = value
prompt_images[key] = file_loc
prompt_alpha_mask_images[key] = alpha_mask_loc
prompt_image_is_keyframe[key] = is_keyframe
except ValueError:
pass
assert len(prompts_array) > 0, "prompts is empty"
@ -143,9 +149,9 @@ def create_zoom_single(
print("using Custom Initial Image")
else:
if prompt_images[min(k for k in prompt_images.keys() if k >= 0)] == "":
load_model_from_setting(
"infzoom_txt2img_model", progress, "Loading Model for txt2img: "
)
load_model_from_setting(
"infzoom_txt2img_model", progress, "Loading Model for txt2img: "
)
processed, current_seed = renderTxt2Img(
prompts[min(k for k in prompts.keys() if k >= 0)],
@ -156,13 +162,18 @@ def create_zoom_single(
current_seed,
width,
height,
)
current_image = processed.images[0]
)
current_image = processed.images[0]
else:
current_image = open_image(prompt_images[min(k for k in prompt_images.keys() if k >= 0)]).resize(
(width, height), resample=Image.LANCZOS
)
# apply available alpha mask
if prompt_alpha_mask_images[min(k for k in prompt_alpha_mask_images.keys() if k >= 0)] != "":
current_image = apply_alpha_mask(current_image, open_image(prompt_alpha_mask_images[min(k for k in prompt_alpha_mask_images.keys() if k >= 0)]))
mask_width = math.trunc(width / 4) # was initially 512px => 128px
mask_height = math.trunc(height / 4) # was initially 512px => 128px
@ -208,6 +219,8 @@ def create_zoom_single(
# inpainting step
current_image = current_image.convert("RGB")
paste_previous_image = prompt_image_is_keyframe[max(k for k in prompt_image_is_keyframe.keys() if k <= (i + 1))]
# Custom and specified images work like keyframes
if custom_exit_image and (i + 1) >= (num_outpainting_steps + extra_frames):
current_image = custom_exit_image.resize(
@ -218,31 +231,37 @@ def create_zoom_single(
if prompt_images[max(k for k in prompt_images.keys() if k <= (i + 1))] == "":
processed, current_seed = renderImg2Img(
prompts[max(k for k in prompts.keys() if k <= (i + 1))],
negative_prompt,
sampler,
num_inference_steps,
guidance_scale,
current_seed,
width,
height,
current_image,
mask_image,
inpainting_denoising_strength,
inpainting_mask_blur,
inpainting_fill_mode,
inpainting_full_res,
inpainting_padding,
)
current_image = processed.images[0]
negative_prompt,
sampler,
num_inference_steps,
guidance_scale,
current_seed,
width,
height,
current_image,
mask_image,
inpainting_denoising_strength,
inpainting_mask_blur,
inpainting_fill_mode,
inpainting_full_res,
inpainting_padding,
)
current_image = processed.images[0]
# only paste previous image when generating a new image
current_image.paste(prev_image, mask=prev_image)
#current_image.paste(prev_image, mask=prev_image)
paste_previous_image = True
else:
current_image = open_image(prompt_images[max(k for k in prompt_images.keys() if k <= (i + 1))]).resize(
(width, height), resample=Image.LANCZOS
)
# apply available alpha mask
if prompt_alpha_mask_images[max(k for k in prompt_alpha_mask_images.keys() if k <= (i + 1))] != "":
current_image = apply_alpha_mask(current_image, open_image(prompt_alpha_mask_images[max(k for k in prompt_alpha_mask_images.keys() if k <= (i + 1))]))
current_image.paste(prev_image, mask=prev_image)
# paste previous image on current image
if paste_previous_image:
current_image.paste(prev_image, mask=prev_image)
# interpolation steps between 2 inpainted images (=sequential zoom and crop)
for j in range(num_interpol_frames - 1):

12
iz_helpers/static_variables.py
View File

@ -5,12 +5,12 @@ import modules.sd_samplers
default_prompt = """
{
"prompts":{
"headers":["outpaint steps","prompt"],
"headers":["outpaint steps","prompt","image location","blend mask location", "is keyframe"],
"data":[
[0,"Huge spectacular Waterfall in a dense tropical forest,epic perspective,(vegetation overgrowth:1.3)(intricate, ornamentation:1.1),(baroque:1.1), fantasy, (realistic:1) digital painting , (magical,mystical:1.2) , (wide angle shot:1.4), (landscape composed:1.2)(medieval:1.1), divine,cinematic,(tropical forest:1.4),(river:1.3)mythology,india, volumetric lighting, Hindu ,epic, Alex Horley Wenjun Lin greg rutkowski Ruan Jia (Wayne Barlowe:1.2) <lora:epiNoiseoffset_v2:0.6> "]
[0,"Huge spectacular Waterfall in a dense tropical forest,epic perspective,(vegetation overgrowth:1.3)(intricate, ornamentation:1.1),(baroque:1.1), fantasy, (realistic:1) digital painting , (magical,mystical:1.2) , (wide angle shot:1.4), (landscape composed:1.2)(medieval:1.1), divine,cinematic,(tropical forest:1.4),(river:1.3)mythology,india, volumetric lighting, Hindu ,epic, Alex Horley Wenjun Lin greg rutkowski Ruan Jia (Wayne Barlowe:1.2) <lora:epiNoiseoffset_v2:0.6> ","C:\\path\\to\\image.png", "C:\\path\\to\\mask_image.png", false]
]
},
"negPrompt":"frames, borderline, text, character, duplicate, error, out of frame, watermark, low quality, ugly, deformed, blur bad-artist"
"negPrompt":"frames, borderline, text, character, duplicate, error, out of frame, watermark, low quality, ugly, deformed, blur bad-artist"
}
"""
available_samplers = [
@ -18,13 +18,13 @@ available_samplers = [
]
empty_prompt = (
'{"prompts":{"data":[],"headers":["outpaint steps","prompt"]},"negPrompt":""}'
'{"prompts":{"data":[],"headers":["outpaint steps","prompt","image location", "blend mask location", "is keyframe"]},"negPrompt":""}'
)
invalid_prompt = {
"prompts": {
"data": [[0, "Your prompt-json is invalid, please check Settings"]],
"headers": ["outpaint steps", "prompt"],
"data": [[0, "Your prompt-json is invalid, please check Settings","", "", False]],
"headers": ["outpaint steps", "prompt","image location","blend mask location", "is keyframe"],
},
"negPrompt": "Invalid prompt-json",
}

6
iz_helpers/ui.py
View File

@ -51,10 +51,10 @@ def on_ui_tabs():
main_prompts = gr.Dataframe(
type="array",
headers=["outpaint step", "prompt"],
datatype=["number", "str"],
headers=["outpaint step", "prompt", "image location", "blend mask", "is keyframe"],
datatype=["number", "str", "str", "str", "bool"],
row_count=1,
col_count=(2, "fixed"),
col_count=(5, "fixed"),
value=jpr["prompts"],
wrap=True,
)

2
iz_helpers/video.py
View File

@ -14,7 +14,7 @@ def write_video(file_path, frames, fps, reversed=True, start_frame_dupe_amount=1
frames = frames[::-1]
# Drop missformed frames
frames = [frame for frame in frames if frame.size == frames[0].size]
frames = [frame.convert("RGBA") for frame in frames if frame.size == frames[0].size]
# Create an imageio video writer, avoid block size of 512.
writer = imageio.get_writer(file_path, fps=fps, macro_block_size=None)