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infinite-zoom-automatic1111-webui
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added Prefix,Suffix, Toolltips, Accordions for sectionizing groups

pull/59/head
GeorgLegato 2023-04-26 05:49:16 +02:00
parent 3a481c06ee
commit 1c44b0b41c
8 changed files with 191 additions and 113 deletions
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7
iz_helpers/helpers.py
View File

@ -100,8 +100,10 @@ def putPrompts(files):
data = readJsonPrompt(file_contents,False)
return [
gr.Textbox.update(data["commonPromptPrefix"]),
gr.DataFrame.update(data["prompts"]),
gr.Textbox.update(data["negPrompt"]),
gr.Textbox.update(data["commonPromptSuffix"]),
gr.Textbox.update(data["negPrompt"])
]
except Exception:
@ -112,12 +114,13 @@ def putPrompts(files):
# error only be shown with raise, so ui gets broken.
#asyncio.run(showGradioErrorAsync("Loading your prompts failed. It seems to be invalid. Your prompt table has been preserved.",5))
return [gr.DataFrame.update(), gr.Textbox.update()]
return [gr.Textbox.update(), gr.DataFrame.update(), gr.Textbox.update(),gr.Textbox.update()]
def clearPrompts():
return [
gr.DataFrame.update(value=[[0, "Infinite Zoom. Start over"]]),
gr.Textbox.update(""),
gr.Textbox.update(""),
gr.Textbox.update("")
]

8
iz_helpers/prompt_util.py
View File

@ -68,4 +68,10 @@ def readJsonPrompt(txt, returnFailPrompt=False):
return invalid_prompt
raise (f"Infinite Zoom: Corrupted Json structure: {txt[:24]} ...")
return validatePromptJson_throws(jpr)
try:
return validatePromptJson_throws(jpr)
except Exception:
if returnFailPrompt:
return invalid_prompt
pass

8
iz_helpers/promptschema.json
View File

@ -47,13 +47,17 @@
"negPrompt": {
"type": "string"
},
"commonPrompt": {
"commonPromptPrefix": {
"type": "string"
},
"commonPromptSuffix": {
"type": "string"
}
},
"required": [
"prompts",
"negPrompt",
"commonPrompt"
"commonPromptPrefix",
"commonPromptSuffix"
]
}

13
iz_helpers/run.py
View File

@ -16,8 +16,9 @@ from .video import write_video
def create_zoom(
common_prompt,
common_prompt_pre,
prompts_array,
common_prompt_suf,
negative_prompt,
num_outpainting_steps,
guidance_scale,
@ -47,8 +48,9 @@ def create_zoom(
for i in range(batchcount):
print(f"Batch {i+1}/{batchcount}")
result = create_zoom_single(
common_prompt,
common_prompt_pre,
prompts_array,
common_prompt_suf,
negative_prompt,
num_outpainting_steps,
guidance_scale,
@ -78,8 +80,9 @@ def create_zoom(
def create_zoom_single(
common_prompt,
common_prompt_pre,
prompts_array,
common_prompt_suf,
negative_prompt,
num_outpainting_steps,
guidance_scale,
@ -144,7 +147,7 @@ def create_zoom_single(
pr = prompts[min(k for k in prompts.keys() if k >= 0)]
processed, newseed = renderTxt2Img(
f"{common_prompt}\n{pr}" if common_prompt else pr,
f"{common_prompt_pre}\n{pr}\n{common_prompt_suf}".strip(),
negative_prompt,
sampler,
num_inference_steps,
@ -209,7 +212,7 @@ def create_zoom_single(
else:
pr = prompts[max(k for k in prompts.keys() if k <= i)]
processed, newseed = renderImg2Img(
f"{common_prompt}\n{pr}" if common_prompt else pr,
f"{common_prompt_pre}\n{pr}\n{common_prompt_suf}".strip(),
negative_prompt,
sampler,
num_inference_steps,

10
iz_helpers/static_variables.py
View File

@ -4,19 +4,20 @@ import modules.sd_samplers
default_prompt = """
{
"commonPromptPrefix":"<lora:epiNoiseoffset_v2:0.6> ",
"prompts":{
"headers":["outpaint steps","prompt","img"],
"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"]
]
},
"negPrompt":"frames, border, edges, borderline, text, character, duplicate, error, out of frame, watermark, low quality, ugly, deformed, blur bad-artist",
"commonPrompt":"style by Alex Horley Wenjun Lin greg rutkowski Ruan Jia (Wayne Barlowe:1.2), <lora:epiNoiseoffset_v2:0.6> "
"commonPromptSuffix":"style by Alex Horley Wenjun Lin greg rutkowski Ruan Jia (Wayne Barlowe:1.2)",
"negPrompt":"frames, border, edges, borderline, text, character, duplicate, error, out of frame, watermark, low quality, ugly, deformed, blur, bad-artist"
}
"""
empty_prompt = (
'{"prompts":{"data":[],"headers":["outpaint steps","prompt"]},"negPrompt":"", commonPrompt:""}'
'{"prompts":{"data":[],"headers":["outpaint steps","prompt"]},"negPrompt":"", commonPromptPrefix:"", commonPromptSuffix}'
)
invalid_prompt = {
@ -25,7 +26,8 @@ invalid_prompt = {
"headers": ["outpaint steps", "prompt"],
},
"negPrompt": "Invalid prompt-json",
"commonPrompt": "Invalid prompt"
"commonPromptPrefix": "Invalid prompt",
"commonPromptSuffix": "Invalid prompt"
}
available_samplers = [

204
iz_helpers/ui.py
View File

@ -28,6 +28,15 @@ def on_ui_tabs():
with gr.Row():
with gr.Column(scale=1, variant="panel"):
with gr.Tab("Main"):
batchcount_slider = gr.Slider(
minimum=1,
maximum=25,
value=shared.opts.data.get("infzoom_batchcount", 1),
step=1,
label="Batch Count",
)
main_outpaint_steps = gr.Slider(
minimum=2,
maximum=100,
@ -41,111 +50,111 @@ def on_ui_tabs():
pr = shared.opts.data.get("infzoom_defPrompt", default_prompt)
jpr = readJsonPrompt(pr, True)
main_common_prompt = gr.Textbox(
value=jpr["commonPrompt"], label="Common Prompt"
)
with gr.Accordion(label="Prompt Section"):
main_common_prompt_pre = gr.Textbox(
value=jpr["commonPromptPrefix"], label="Common Prompt Prefix"
)
main_prompts = gr.Dataframe(
type="array",
headers=["outpaint step", "prompt"],
datatype=["number", "str"],
row_count=1,
col_count=(2, "fixed"),
value=jpr["prompts"],
wrap=True,
)
main_prompts = gr.Dataframe(
type="array",
headers=["outpaint step", "prompt"],
datatype=["number", "str"],
row_count=1,
col_count=(2, "fixed"),
value=jpr["prompts"],
wrap=True,
)
main_negative_prompt = gr.Textbox(
value=jpr["negPrompt"], label="Negative Prompt"
)
main_common_prompt_suf = gr.Textbox(
value=jpr["commonPromptSuffix"], label="Common Prompt Suffix"
)
# these button will be moved using JS unde the dataframe view as small ones
exportPrompts_button = gr.Button(
value="Export prompts",
variant="secondary",
elem_classes="sm infzoom_tab_butt",
elem_id="infzoom_exP_butt",
)
importPrompts_button = gr.UploadButton(
label="Import prompts",
variant="secondary",
elem_classes="sm infzoom_tab_butt",
elem_id="infzoom_imP_butt",
)
exportPrompts_button.click(
None,
_js="exportPrompts",
inputs=[main_prompts, main_negative_prompt],
outputs=None
)
importPrompts_button.upload(
fn=putPrompts,
outputs=[main_prompts, main_negative_prompt],
inputs=[importPrompts_button],
)
main_negative_prompt = gr.Textbox(
value=jpr["negPrompt"], label="Negative Prompt"
)
clearPrompts_button = gr.Button(
value="Clear prompts",
variant="secondary",
elem_classes="sm infzoom_tab_butt",
elem_id="infzoom_clP_butt",
)
clearPrompts_button.click(
fn=clearPrompts,
inputs=[],
outputs=[main_prompts, main_negative_prompt, main_common_prompt],
)
with gr.Row():
seed = gr.Number(
label="Seed", value=-1, precision=0, interactive=True
# these button will be moved using JS unde the dataframe view as small ones
exportPrompts_button = gr.Button(
value="Export prompts",
variant="secondary",
elem_classes="sm infzoom_tab_butt",
elem_id="infzoom_exP_butt",
)
main_sampler = gr.Dropdown(
label="Sampler",
choices=available_samplers,
value="Euler a",
type="value",
importPrompts_button = gr.UploadButton(
label="Import prompts",
variant="secondary",
elem_classes="sm infzoom_tab_butt",
elem_id="infzoom_imP_butt",
)
with gr.Row():
main_width = gr.Slider(
minimum=16,
maximum=2048,
value=shared.opts.data.get("infzoom_outsizeW", 512),
step=16,
label="Output Width",
exportPrompts_button.click(
None,
_js="exportPrompts",
inputs=[main_common_prompt_pre, main_prompts, main_common_prompt_suf, main_negative_prompt],
outputs=None
)
main_height = gr.Slider(
minimum=16,
maximum=2048,
value=shared.opts.data.get("infzoom_outsizeH", 512),
step=16,
label="Output Height",
importPrompts_button.upload(
fn=putPrompts,
outputs=[main_common_prompt_pre, main_prompts,main_common_prompt_suf , main_negative_prompt],
inputs=[importPrompts_button],
)
with gr.Row():
main_guidance_scale = gr.Slider(
minimum=0.1,
maximum=15,
step=0.1,
value=7,
label="Guidance Scale",
)
sampling_step = gr.Slider(
minimum=1,
maximum=100,
step=1,
value=50,
label="Sampling Steps for each outpaint",
)
with gr.Row():
init_image = gr.Image(type="pil", label="custom initial image")
exit_image = gr.Image(type="pil", label="custom exit image")
batchcount_slider = gr.Slider(
minimum=1,
maximum=25,
value=shared.opts.data.get("infzoom_batchcount", 1),
step=1,
label="Batch Count",
)
clearPrompts_button = gr.Button(
value="Clear prompts",
variant="secondary",
elem_classes="sm infzoom_tab_butt",
elem_id="infzoom_clP_butt",
)
clearPrompts_button.click(
fn=clearPrompts,
inputs=[],
outputs=[main_prompts, main_negative_prompt, main_common_prompt_pre, main_common_prompt_suf],
)
with gr.Accordion("Render settings"):
with gr.Row():
seed = gr.Number(
label="Seed", value=-1, precision=0, interactive=True
)
main_sampler = gr.Dropdown(
label="Sampler",
choices=available_samplers,
value="Euler a",
type="value",
)
with gr.Row():
main_width = gr.Slider(
minimum=16,
maximum=2048,
value=shared.opts.data.get("infzoom_outsizeW", 512),
step=16,
label="Output Width",
)
main_height = gr.Slider(
minimum=16,
maximum=2048,
value=shared.opts.data.get("infzoom_outsizeH", 512),
step=16,
label="Output Height",
)
with gr.Row():
main_guidance_scale = gr.Slider(
minimum=0.1,
maximum=15,
step=0.1,
value=7,
label="Guidance Scale",
)
sampling_step = gr.Slider(
minimum=1,
maximum=100,
step=1,
value=50,
label="Sampling Steps for each outpaint",
)
with gr.Row():
init_image = gr.Image(type="pil", label="Custom initial image")
exit_image = gr.Image(type="pil", label="Custom exit image")
with gr.Tab("Video"):
video_frame_rate = gr.Slider(
label="Frames per second",
@ -233,8 +242,9 @@ Our best experience and trade-off is the R-ERSGAn4x upscaler.
generate_btn.click(
fn=wrap_gradio_gpu_call(create_zoom, extra_outputs=[None, "", ""]),
inputs=[
main_common_prompt,
main_common_prompt_pre,
main_prompts,
main_common_prompt_suf,
main_negative_prompt,
main_outpaint_steps,
main_guidance_scale,

50
javascript/infinite-zoom-hints.js Normal file
View File

@ -0,0 +1,50 @@
// mouseover tooltips for various UI elements
infzoom_titles = {
"Batch Count":"How many separate videos to create",
"Total Outpaint Steps":"Each step generates frame for 1 second at your FPS, while cycling through your array of prompts",
"Common Prompt Prefix":"Prompt inserted before each step",
"Common Prompt Suffix":"Prompt inserted after each step",
"Negative Prompt":"What your model shall avoid",
"Export prompts": "Downloads a JSON file to save all prompts",
"Import prompts": "Restore Prompts table from a specific JSON file",
"Clear prompts": "Start over, remove all entries from prompt table, prefix, suffix, negative",
"Custom initial image":"An image at the end resp. begin of your movie, depending or ZoomIn or Out",
"Custom exit image":"An image at the end resp. begin of your movie, depending or ZoomIn or Out",
"Zoom Speed":"Varies additional frames per second",
}
onUiUpdate(function(){
gradioApp().querySelectorAll('span, button, select, p').forEach(function(span){
tooltip = infzoom_titles[span.textContent];
if(!tooltip){
tooltip = infzoom_titles[span.value];
}
if(!tooltip){
for (const c of span.classList) {
if (c in infzoom_titles) {
tooltip = infzoom_titles[c];
break;
}
}
}
if(tooltip){
span.title = tooltip;
}
})
gradioApp().querySelectorAll('select').forEach(function(select){
if (select.onchange != null) return;
select.onchange = function(){
select.title = infzoom_titles[select.value] || "";
}
})
})

4
javascript/infinite-zoom.js
View File

@ -1,7 +1,7 @@
// Function to download data to a file
function exportPrompts(cp,p, np, filename = "infinite-zoom-prompts.json") {
function exportPrompts(cppre,p, cpsuf,np, filename = "infinite-zoom-prompts.json") {
let J = { prompts: p, negPrompt: np, commonPrompt: cp }
let J = { prompts: p, negPrompt: np, commonPromptPrefix: cppre, commonPromptSuffix: cpsuf }
var file = new Blob([JSON.stringify(J)], { type: "text/csv" });
if (window.navigator.msSaveOrOpenBlob) // IE10+