v8hid / infinite-zoom-automatic1111-webui

infinite zoom effect extension for AUTOMATIC1111's webui - stable diffusion

Infinite Zoom extension for Stable Diffusion WebUI.

This is an extension for the AUTOMATIC1111's (and Vladmandic´s) webui that allows users to create infinite zoom effect videos using stable diffusion outpainting method.

How to install?

Click to expand

1. Open Stable Diffusion WebUI.

2. Go to the Extensions tab > Install from URL.

3. Enter https://github.com/v8hid/infinite-zoom-automatic1111-webui.git for the URL and leave the second field empty and wait for it to be installed.

4. Go to the Installed tab and press Apply, wait for installation, and restart.

5. Wait for the Stable Diffusion WebUI to restart and now you can try the Infinite Zoom extension.

How to use?

Click to expand

1. Click on the Infinite Zoom tab

2. Modify the parameters as you wish and click Generate video, the video will appear as soon as it generates

To learn more about the parameters, please refer to our WIKI.

Effective Friendly Tips for Optimal Outcomes

Click to expand

• You're only as good as your model, so level up with an Inpainting model for killer results.

• Heads up: Setting Mask Blur parameter above 0 will give you results that look like they've been hit by the ugly stick.

• Just between us - don't forget to uncheck Apply color correction to img2img results to match original colors in the Stable Diffusion tab of the WebUI settings. You don't want your results looking like a bad Instagram filter.

Examples

Click to expand

infinite_zoom_1681356213.mp4

infinite_zoom_1681313291.mp4

2341234.mp4

infinite_zoom_1681315670.mp4

How it works?

Click to expand

To start, let's break down the workflow of the extension into three main steps:

• Step 1: Choose an image to start with The program either generates an initial image using the first prompt you provide or you can upload your own image in the custom initial image field. This initial image will be the basis for the outpainting process.

• Step 2: Generate outpaint steps Once you have your initial image, the program will start generating outpaint steps. The number of outpaint steps is determined by the Total Outpaint Steps input. In each outpaint step, the program makes the initial image smaller in the center of the canvas and generates a new image in the empty space that is created. This process is repeated for each outpaint step until the desired number is reached.

• Step 3: Create a gradual zoom effect After all outpaint steps have been generated, the program creates an interpolation between each outpaint step to create a gradual zoom effect. The number of frames created between each outpaint step is determined by the Zoom Speed parameter and the Frames per second parameter.

Number of frames for each outpaint step = Zoom Speed $\times$ Frames per second

Length of each outpaint step in second = Number of frames $\div$ Frames per second

Google Colab version

It works on free colab plan

Contributing

Contributions are welcome! Please follow these guidelines:

1. Fork the repository.
2. Make your changes and commit them.
3. Make sure to submit the pull request to the develop repository.

infinite-zoom-automatic1111-webui's Issues

[Feature] Sampler Selection Field

Users can now choose their desired sampler from the main settings page with our new Sampler Selection Field.
p.s: now it uses Euler A

[BUG]

Describe the bug
A clear and concise description of what the bug is.

To Reproduce
Steps to reproduce the behavior:

1. Enter these inputs '....'
2. Click on '....'

Expected behavior
A clear and concise description of what you expected to happen.

Screenshots of error
If applicable, add screenshots to help explain your problem. Or just dump the error.

Desktop (please complete the following information):

• OS: [e.g. Windows]
• Version [e.g. 22]

Additional context
Add any other context about the problem here.

ffmpy.FFExecutableNotFoundError: Executable 'ffprobe' not found

I am getting the error above after I run the generate button but the video still appears in the output.

Steps to reproduce:
Use default setting

Things I tried:

1. Did a pip install ffmpeg in cmd inside my %USERPROFILE% environment
2. Did a pip install ffprobe inside the venv environment in automatic111
3. Downloaded the 7zip full build of ffmpeg from https://www.gyan.dev/ffmpeg/builds/ and then moving the ffmpeg, ffprobe and ffplay exe files into the venv folder

I am able to see the version of ffmpeg when I do ffmpeg -version in cmd so I am not sure what the problem is exactly. Hoping that someone has the solution to this.

Here is a snippet of the error:
Outpaint step: 1 / 2
100%|██████████████████████████████████████████████████████████████████████████████████| 50/50 [00:34<00:00, 1.44it/s]
Outpaint step: 2 / 2
100%|██████████████████████████████████████████████████████████████████████████████████| 50/50 [00:34<00:00, 1.44it/s]
Traceback (most recent call last):
File "C:\Users\nicky\AppData\Local\Programs\Python\Python310\lib\site-packages\ffmpy.py", line 93, in run
self.process = subprocess.Popen(
File "C:\Users\nicky\AppData\Local\Programs\Python\Python310\lib\subprocess.py", line 971, in init
self._execute_child(args, executable, preexec_fn, close_fds,
File "C:\Users\nicky\AppData\Local\Programs\Python\Python310\lib\subprocess.py", line 1440, in _execute_child
hp, ht, pid, tid = _winapi.CreateProcess(executable, args,
FileNotFoundError: [WinError 2] The system cannot find the file specified

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\Users\nicky\AppData\Local\Programs\Python\Python310\lib\site-packages\gradio\routes.py", line 394, in run_predict
output = await app.get_blocks().process_api(
File "C:\Users\nicky\AppData\Local\Programs\Python\Python310\lib\site-packages\gradio\blocks.py", line 1078, in process_api
data = self.postprocess_data(fn_index, result["prediction"], state)
File "C:\Users\nicky\AppData\Local\Programs\Python\Python310\lib\site-packages\gradio\blocks.py", line 1012, in postprocess_data
prediction_value = block.postprocess(prediction_value)
File "C:\Users\nicky\AppData\Local\Programs\Python\Python310\lib\site-packages\gradio\components.py", line 1979, in postprocess
and not processing_utils.video_is_playable(y)
File "C:\Users\nicky\AppData\Local\Programs\Python\Python310\lib\site-packages\gradio\processing_utils.py", line 783, in video_is_playable
output = probe.run(stderr=subprocess.PIPE, stdout=subprocess.PIPE)
File "C:\Users\nicky\AppData\Local\Programs\Python\Python310\lib\site-packages\ffmpy.py", line 98, in run
raise FFExecutableNotFoundError(
ffmpy.FFExecutableNotFoundError: Executable 'ffprobe' not found

Can no longer retrieve Zoom In videos that have an initial image

I can make Zoom In videos that have no initial image, but when I included an initial image, I got an error message. However, I WAS still able to retrieve the Zoom In video with initial image in Outputs>>img2img-images>>infinite-zooms, so I was good with it. But now I can't. The resulting Zoom In video with initial image only has the first frame. I have the pictures that make this Zoom In video in img2img-images folder in the today's date folder. If you can point me to something to can put these images together for the Zoom In video for the time being I'll be happy.

Having issue using 4x-Ultrasharp in postprocessing

I'm having an issue upscaling with 4x-Ultrasharp in postprocessing. This is the total progress after after batch 1 and then the error:
Batch 1/1
0% 0/50 [00:00<?, ?it/s]
2% 1/50 [00:00<00:07, 6.55it/s]
4% 2/50 [00:00<00:07, 6.64it/s]
6% 3/50 [00:00<00:07, 6.62it/s]
8% 4/50 [00:00<00:06, 6.68it/s]
10% 5/50 [00:00<00:06, 6.72it/s]
12% 6/50 [00:00<00:06, 6.72it/s]
14% 7/50 [00:01<00:06, 6.67it/s]
16% 8/50 [00:01<00:06, 6.70it/s]
18% 9/50 [00:01<00:06, 6.70it/s]
20% 10/50 [00:01<00:05, 6.70it/s]
22% 11/50 [00:01<00:05, 6.71it/s]
24% 12/50 [00:01<00:05, 6.72it/s]
26% 13/50 [00:01<00:05, 6.72it/s]
28% 14/50 [00:02<00:05, 6.70it/s]
30% 15/50 [00:02<00:05, 6.70it/s]
32% 16/50 [00:02<00:05, 6.71it/s]
34% 17/50 [00:02<00:04, 6.69it/s]
36% 18/50 [00:02<00:04, 6.68it/s]
38% 19/50 [00:02<00:04, 6.68it/s]
40% 20/50 [00:02<00:04, 6.67it/s]
42% 21/50 [00:03<00:04, 6.67it/s]
44% 22/50 [00:03<00:04, 6.65it/s]
46% 23/50 [00:03<00:04, 6.67it/s]
48% 24/50 [00:03<00:03, 6.69it/s]
50% 25/50 [00:03<00:03, 6.68it/s]
52% 26/50 [00:03<00:03, 6.68it/s]
54% 27/50 [00:04<00:03, 6.66it/s]
56% 28/50 [00:04<00:03, 6.69it/s]
58% 29/50 [00:04<00:03, 6.67it/s]
60% 30/50 [00:04<00:02, 6.67it/s]
62% 31/50 [00:04<00:02, 6.67it/s]
64% 32/50 [00:04<00:02, 6.69it/s]
66% 33/50 [00:04<00:02, 6.64it/s]
68% 34/50 [00:05<00:02, 6.64it/s]
70% 35/50 [00:05<00:02, 6.63it/s]
72% 36/50 [00:05<00:02, 6.67it/s]
74% 37/50 [00:05<00:01, 6.64it/s]
76% 38/50 [00:05<00:01, 6.64it/s]
78% 39/50 [00:05<00:01, 6.63it/s]
80% 40/50 [00:05<00:01, 6.65it/s]
82% 41/50 [00:06<00:01, 6.65it/s]
84% 42/50 [00:06<00:01, 6.59it/s]
86% 43/50 [00:06<00:01, 6.60it/s]
88% 44/50 [00:06<00:00, 6.54it/s]
90% 45/50 [00:06<00:00, 6.53it/s]
92% 46/50 [00:06<00:00, 6.42it/s]
94% 47/50 [00:07<00:00, 6.43it/s]
96% 48/50 [00:07<00:00, 6.54it/s]
98% 49/50 [00:07<00:00, 6.60it/s]
100% 50/50 [00:07<00:00, 6.65it/s]
Error completing request
Arguments: ([[0, ' ((Best quality)), ((masterpiece)),((realistic)),lord of the rings hobbit village, blue sky on top, scenic, masterpiece'], ['3', '((Best quality)), ((masterpiece)),((realistic)),lord of the rings lush green mountain forest with small river, blue sky on top, scenic, masterpiece'], ['6', '((Best quality)), ((masterpiece)),((realistic)),lord of the rings mountain valley in the alps, blue sky on top, scenic, masterpiece']], 'frames, borderline, text, character, duplicate, error, out of frame, watermark, low quality, ugly, deformed, blur bad-artist', 8, 7, 50, None, None, 30, 1, 0, 0, 1, 0, 2, False, 0, 2, 512, 512, 1, 'Euler a', True, '4x-UltraSharp', 2) {}
Traceback (most recent call last):
File "/content/stable-diffusion-webui/modules/call_queue.py", line 56, in f
res = list(func(*args, **kwargs))
File "/content/stable-diffusion-webui/modules/call_queue.py", line 37, in f
res = func(*args, **kwargs)
File "/content/stable-diffusion-webui/extensions/infinite-zoom-automatic1111-webui/scripts/infinite-zoom.py", line 242, in create_zoom
result = create_zoom_single(
File "/content/stable-diffusion-webui/extensions/infinite-zoom-automatic1111-webui/scripts/infinite-zoom.py", line 352, in create_zoom_single
do_upscaleImg(current_image, upscale_do, upscaler_name, upscale_by)
File "/content/stable-diffusion-webui/extensions/infinite-zoom-automatic1111-webui/scripts/infinite-zoom.py", line 102, in do_upscaleImg
ups.process(
File "/content/stable-diffusion-webui/scripts/postprocessing_upscale.py", line 94, in process
upscaled_image = self.upscale(pp.image, pp.info, upscaler1, upscale_mode, upscale_by, upscale_to_width, upscale_to_height, upscale_crop)
File "/content/stable-diffusion-webui/scripts/postprocessing_upscale.py", line 64, in upscale
image = upscaler.scaler.upscale(image, upscale_by, upscaler.data_path)
File "/content/stable-diffusion-webui/modules/upscaler.py", line 63, in upscale
img = self.do_upscale(img, selected_model)
File "/content/stable-diffusion-webui/modules/esrgan_model.py", line 154, in do_upscale
img = esrgan_upscale(model, img)
File "/content/stable-diffusion-webui/modules/esrgan_model.py", line 225, in esrgan_upscale
output = upscale_without_tiling(model, tile)
File "/content/stable-diffusion-webui/modules/esrgan_model.py", line 204, in upscale_without_tiling
output = model(img)
File "/usr/local/lib/python3.9/dist-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/content/stable-diffusion-webui/modules/esrgan_model_arch.py", line 62, in forward
return self.model(feat)
File "/usr/local/lib/python3.9/dist-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.9/dist-packages/torch/nn/modules/container.py", line 204, in forward
input = module(input)
File "/usr/local/lib/python3.9/dist-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/content/stable-diffusion-webui/extensions-builtin/Lora/lora.py", line 201, in lora_Conv2d_forward
return lora_forward(self, input, torch.nn.Conv2d_forward_before_lora(self, input))
File "/usr/local/lib/python3.9/dist-packages/torch/nn/modules/conv.py", line 463, in forward
return self._conv_forward(input, self.weight, self.bias)
File "/usr/local/lib/python3.9/dist-packages/torch/nn/modules/conv.py", line 459, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: Given groups=1, weight of size [64, 3, 3, 3], expected input[1, 4, 192, 192] to have 3 channels, but got 4 channels instead

Traceback (most recent call last):
File "/usr/local/lib/python3.9/dist-packages/gradio/routes.py", line 337, in run_predict
output = await app.get_blocks().process_api(
File "/usr/local/lib/python3.9/dist-packages/gradio/blocks.py", line 1018, in process_api
data = self.postprocess_data(fn_index, result["prediction"], state)
File "/usr/local/lib/python3.9/dist-packages/gradio/blocks.py", line 935, in postprocess_data
if predictions[i] is components._Keywords.FINISHED_ITERATING:
IndexError: tuple index out of range

I use a colab. I don't know if that has anything to do with it. I have already created other infinite zoom videos, so this the next thing I am testing.

Speed of zoom-in or out

Hi, thanks for extension!

Is it possible to add another slider that controls the zoom speed?

I want to make a video with this effect, but at a much slower speed...

[Feature] Offer infinite pan in addition to zoom

Would be great to have a constantly scrolling scene

Error executing callback ui_tabs_callback

Don't see tab after starting

Log:

Error executing callback ui_tabs_callback for D:\Soft\StableD\extensions\infinite-zoom-automatic1111-webui\scripts\infinite-zoom.py
Traceback (most recent call last):
File "D:\Soft\StableD\modules\script_callbacks.py", line 93, in ui_tabs_callback
res += c.callback() or []
File "D:\Soft\StableD\extensions\infinite-zoom-automatic1111-webui\scripts\infinite-zoom.py", line 433, in on_ui_tabs
importPrompts_button = gr.UploadButton(
AttributeError: module 'gradio' has no attribute 'UploadButton'

'NoneType' object has no attribute 'alwayson_scripts'

Error completing request
Arguments: ([[0, 'Jungle with lush green trees and clear blue sky'], ['3', 'Jungle with tall brown trees and orange sunset sky'], ['5', 'Jungle with sparse trees and dark stormy sky'], ['10', 'Jungle with yellow autumn trees and purple twilight sky']], 'frames, borderline, text, character, duplicate, error, out of frame, watermark, low quality, ugly, deformed, blur bad-artist', 14, 7, 50, None, None, 30, 0, 0, 0, 1, 0, 2, False, 0, 1, 512, 512, 1, 'Euler a', False, 'None', 1) {}
Traceback (most recent call last):
File "E:\tools\stable\novelai-webui-aki-v3A\modules\call_queue.py", line 56, in f
res = list(func(*args, **kwargs))
File "E:\tools\stable\novelai-webui-aki-v3A\modules\call_queue.py", line 37, in f
res = func(*args, **kwargs)
File "E:\tools\stable\novelai-webui-aki-v3A\extensions\infinite-zoom-automatic1111-webui\scripts\infinite-zoom.py", line 242, in create_zoom
result = create_zoom_single(
File "E:\tools\stable\novelai-webui-aki-v3A\extensions\infinite-zoom-automatic1111-webui\scripts\infinite-zoom.py", line 330, in create_zoom_single
processed = renderTxt2Img(
File "E:\tools\stable\novelai-webui-aki-v3A\extensions\infinite-zoom-automatic1111-webui\scripts\infinite-zoom.py", line 132, in renderTxt2Img
processed = process_images(p)
File "E:\tools\stable\novelai-webui-aki-v3A\modules\processing.py", line 503, in process_images
res = process_images_inner(p)
File "E:\tools\stable\novelai-webui-aki-v3A\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 39, in processing_process_images_hijack
cn_is_batch, batches, output_dir, input_file_names = get_cn_batches(p)
File "E:\tools\stable\novelai-webui-aki-v3A\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 184, in get_cn_batches
units = external_code.get_all_units_in_processing(p)
File "E:\tools\stable\novelai-webui-aki-v3A\extensions\sd-webui-controlnet\scripts\external_code.py", line 104, in get_all_units_in_processing
return get_all_units(p.scripts, p.script_args)
File "E:\tools\stable\novelai-webui-aki-v3A\extensions\sd-webui-controlnet\scripts\external_code.py", line 113, in get_all_units
cn_script = find_cn_script(script_runner)
File "E:\tools\stable\novelai-webui-aki-v3A\extensions\sd-webui-controlnet\scripts\external_code.py", line 280, in find_cn_script
for script in script_runner.alwayson_scripts:
AttributeError: 'NoneType' object has no attribute 'alwayson_scripts'

Traceback (most recent call last):
File "E:\tools\stable\novelai-webui-aki-v3A\py310\lib\site-packages\gradio\blocks.py", line 987, in postprocess_data
if predictions[i] is components._Keywords.FINISHED_ITERATING:
IndexError: tuple index out of range

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "E:\tools\stable\novelai-webui-aki-v3A\py310\lib\site-packages\gradio\routes.py", line 394, in run_predict
output = await app.get_blocks().process_api(
File "E:\tools\stable\novelai-webui-aki-v3A\py310\lib\site-packages\gradio\blocks.py", line 1078, in process_api
data = self.postprocess_data(fn_index, result["prediction"], state)
File "E:\tools\stable\novelai-webui-aki-v3A\py310\lib\site-packages\gradio\blocks.py", line 991, in postprocess_data
raise ValueError(
ValueError: Number of output components does not match number of values returned from from function f

todo: add Settings, slider for out size, use custom outpath

Assigning to me. to avoid races or concurrent implementations

Corrupted Json structure

I see some warrning in the log as showing below:

Infinite Zoom: Corrupted Json structure: {
    "prompts":{
       ...

I try removing the extention and installing again and I still get the same warrning

cant install extension

Launching Web UI with arguments: --disable-safe-unpickle --xformers
Error loading script: infinite-zoom.py
Traceback (most recent call last):
File "C:\Users\RTX01\stable-diffusion-webui\modules\scripts.py", line 205, in load_scripts
module = script_loading.load_module(scriptfile.path)
File "C:\Users\RTX01\stable-diffusion-webui\modules\script_loading.py", line 13, in load_module
exec(compiled, module.dict)
File "C:\Users\RTX01\stable-diffusion-webui\extensions\infinite-zoom-automatic1111-webui\scripts\infinite-zoom.py", line 23, in
from scripts import postprocessing_upscale
ImportError: cannot import name 'postprocessing_upscale' from 'scripts' (unknown location)

prompts and settings for one example

It would be nice to get a sense of how to get good results and what models do a good job.

Store and Load prompts to/from file

to avoid rewriting prompts, have a
*save button

• load button
• and save that generation info next to the video like "infinite-zoom-1231556.txt"

Format: dont know, what the gradio table is able to read/write

Executable 'ffprobe' not found - FFPROBE PATH not set

I have the same problem and found some manual workaround; if not solution.
My setup is Windows, SD is latest version (22bcc or so)

ffrpobe is still not found.
I "pip install ffprobe", did not help.
The pyffprobe is only a wrapper for some ffprope.exe, which has to be

• available on disk
• and in ENV:PATH

So, I downloaded from github latest ffmpeg release (https://github.com/BtbN/FFmpeg-Builds/releases) and
upacked somewhere.
Now, you need to extend the PATH variable in the context where you SD-Webui is started; either manually
set PATH=%PATH%;C:\Users\YOU\Downloads\ffmpeg-master-latest-win64-gpl\bin

Pros put that in their web-user.bat...

@v8hid You could solve that more elegant by provide a Settings-property "PathToFFMPEG" and set OS.Path accordingly

Originally posted by @GeorgLegato in #3 (comment)

How to set duration? and fix boxes and frames showing?

How to set duration?

I try adding extra prompts and add 0, 75, 125 etc.. but it gets ignored and same exact duration stay no matter how many prompt i add.

The other question is why am I getting boxes without smooth inpaint? I am using offical SD 1.5 inpainting model.

sample below:
https://user-images.githubusercontent.com/4099839/232152364-b41ac254-a29a-4bdc-a14a-6f4c1b2f614a.mp4

2nd sample:
https://user-images.githubusercontent.com/4099839/232153736-97fe50d8-d037-4844-9500-819f73f0037d.mp4

Addition of watermark

Is it possible to add a field with settings to overlay a transparent png-file like a watermark? With the ability to adjust the position (centre, top corner, diagonal)? Instead of editing in video editors.

[BUG]ValueError: An event handler (f) didn't receive enough output values (needed: 5, received: 4)

Describe the bug
when i create a vieo is error;

Traceback (most recent call last):
  File "/Users/cgd/cgd/ai/stable-diffusion-webui/venv/lib/python3.10/site-packages/gradio/routes.py", line 408, in run_predict
    output = await app.get_blocks().process_api(
  File "/Users/cgd/cgd/ai/stable-diffusion-webui/venv/lib/python3.10/site-packages/gradio/blocks.py", line 1318, in process_api
    data = self.postprocess_data(fn_index, result["prediction"], state)
  File "/Users/cgd/cgd/ai/stable-diffusion-webui/venv/lib/python3.10/site-packages/gradio/blocks.py", line 1221, in postprocess_data
    self.validate_outputs(fn_index, predictions)  # type: ignore
  File "/Users/cgd/cgd/ai/stable-diffusion-webui/venv/lib/python3.10/site-packages/gradio/blocks.py", line 1196, in validate_outputs
    raise ValueError(
ValueError: An event handler (f) didn't receive enough output values (needed: 5, received: 4)

To Reproduce
Steps to reproduce the behavior:

Expected behavior

Screenshots of error

Desktop (please complete the following information):

Additional context

Video-Gallery points to tmp-folder

From Vlad1111

ValueError: File cannot be fetched: C:/Users/ME/AppData/Local/Temp/58e814e546d2366335af49716872cea2e9c0407c/infinite_zoom_1682344331.mp4. All files must
contained within the Gradio python app working directory, or be a temp file created by the Gradio python app.

Current element
<video src="http://localhost:7860/file=C:\Users\ME\AppData\Local\Temp\58e814e546d2366335af49716872cea2e9c0407c\infinite_zoom_1682344331.mp4" preload="auto" class="svelte-1vnmhm4" style="opacity: 1; transition: all 0.2s ease 0s; position: relative;"><track kind="captions"><iframe style="display: block; position: absolute; top: 0; left: 0; width: 100%; height: 100%; overflow: hidden; border: 0; opacity: 0; pointer-events: none; z-index: -1;" aria-hidden="true" tabindex="-1" src="about:blank"></iframe></video>

Solution:
a) add the path to video srs
b) use data url (I know firefox has problems reading such)

[Feature] Can it loop?

Is it possible to also have last image same as first image making an infinite loop?

Infinite Zoom's ValueError Issue

If you encounter a ValueError while using Infinite Zoom to generate, as shown in the screenshot, it could be due to insufficient VRAM. You can solve this issue by following these steps: add --xformers --medvram after COMMANDLINE_ARGS= in your Launch.bat file：

set COMMANDLINE_ARGS= --xformers --medvram

By doing this, you will reduce the VRAM usage, allowing the generation process to proceed smoothly. However, it may take longer than before.

This may seem like a minor issue, but once it occurs, it can cause the entire Stable Diffusion process to become paralyzed until you restart it. Therefore, if you don't have a large amount of VRAM, you can use the aforementioned method to reduce its usage during generation.

ValueError: All images in a movie should have same size

Traceback (most recent call last):
File "/usr/local/lib/python3.9/dist-packages/gradio/routes.py", line 394, in run_predict
output = await app.get_blocks().process_api(
File "/usr/local/lib/python3.9/dist-packages/gradio/blocks.py", line 1075, in process_api
result = await self.call_function(
File "/usr/local/lib/python3.9/dist-packages/gradio/blocks.py", line 884, in call_function
prediction = await anyio.to_thread.run_sync(
File "/usr/local/lib/python3.9/dist-packages/anyio/to_thread.py", line 31, in run_sync
return await get_asynclib().run_sync_in_worker_thread(
File "/usr/local/lib/python3.9/dist-packages/anyio/_backends/_asyncio.py", line 937, in run_sync_in_worker_thread
return await future
File "/usr/local/lib/python3.9/dist-packages/anyio/_backends/_asyncio.py", line 867, in run
result = context.run(func, *args)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/infinite-zoom-automatic1111-webui/scripts/infinite-zoom.py", line 154, in create_zoom
result = create_zoom_single(
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/infinite-zoom-automatic1111-webui/scripts/infinite-zoom.py", line 357, in create_zoom_single
write_video(
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/infinite-zoom-automatic1111-webui/iz_helpers/video.py", line 35, in write_video
writer.append_data(np_frame)
File "/usr/local/lib/python3.9/dist-packages/imageio/core/format.py", line 590, in append_data
return self._append_data(im, total_meta)
File "/usr/local/lib/python3.9/dist-packages/imageio/plugins/ffmpeg.py", line 591, in _append_data
raise ValueError("All images in a movie should have same size")
ValueError: All images in a movie should have same size

feature request

1 - Can we have frame size or aspect ratio? so we can have it 1:1 or 16:9 etc..

2 - Can we open up the duration Total Outpaint Steps over 100? something to be set by user
currently its maxed with 100.

Error

Loading weights [8db0e00911] from C:\Users\xxxx\Deep\stable-diffusion-webui\models\Stable-diffusion\Jelli.ckpt
Applying scaled dot product cross attention optimization.
Weights loaded in 9.4s (load weights from disk: 8.6s, apply weights to model: 0.2s, move model to device: 0.6s).
Error completing request
Arguments: ([['A psychedelic hyper-realistic photo of Jellili person in space, fractal-like patterns, a close up of Jelliperson eye, galaxy in space hyper futuristic, 8k resolution, hyper realistic', '']], 'frames, borderline, text, character, duplicate, error, out of frame, watermark, low quality, ugly, deformed, blur', 8, 7, 50, None, 30, 0, 0, 0, 1, 0, 2, False, 0) {}
Traceback (most recent call last):
File "C:\Users\xxxx\Deep\stable-diffusion-webui\modules\call_queue.py", line 56, in f
res = list(func(*args, **kwargs))
File "C:\Users\xxxx\Deep\stable-diffusion-webui\modules\call_queue.py", line 37, in f
res = func(*args, **kwargs)
File "C:\Users\xxxx\Deep\stable-diffusion-webui\extensions\infinite-zoom-automatic1111-webui\scripts\inifnite-zoom.py", line 132, in create_zoom
prompts[min(k for k in prompts.keys() if k >= 0)],
ValueError: min() arg is an empty sequence

Traceback (most recent call last):
File "C:\Users\xxxx\Deep\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 987, in postprocess_data
if predictions[i] is components._Keywords.FINISHED_ITERATING:
IndexError: tuple index out of range

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\Users\xxxx\Deep\stable-diffusion-webui\venv\lib\site-packages\gradio\routes.py", line 394, in run_predict
output = await app.get_blocks().process_api(
File "C:\Users\xxxx\Deep\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 1078, in process_api
data = self.postprocess_data(fn_index, result["prediction"], state)
File "C:\Users\xxxx\Deep\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 991, in postprocess_data
raise ValueError(
ValueError: Number of output components does not match number of values returned from from function f

What is purpose of the 1st prompt column actually?

I think it is not used in code and that intentionally, is it just a numbering?
@v8hid we could remove it, right?

on Upscale: Odd pixel width crashes ffmpeg

If upscale factor * output pixel-size => odd width => ffmpeg dies:

720 px width * 1.66 upscale => 1195.2 => 1195 crash

Inputs:

[swscaler @ 0000022737ce1000] Warning: data is not aligned! This can lead to a speed loss
[libx264 @ 0000022737c8d400] width not divisible by 2 (1195x849)
Error initializing output stream 0:0 -- Error while opening encoder for output stream #0:0 - maybe incorrect parameters such as bit_rate, rate, width or height
gradio call: OSError
╭───────────────────────────────────────────────────────────────────────── Traceback (most recent call last) ─────────────────────────────────────────────────────────────────────────╮│ S:\KI\Vladmandic1111\venv\lib\site-packages\imageio_ffmpeg_io.py:630 in write_frames ││ ││ 629 │ │ │ try: ││ ❱ 630 │ │ │ │ p.stdin.write(bb) ││ 631 │ │ │ except Exception as err: │╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯BrokenPipeError: [Errno 32] Broken pipe

During handling of the above exception, another exception occurred:

╭───────────────────────────────────────────────────────────────────────── Traceback (most recent call last) ─────────────────────────────────────────────────────────────────────────╮│ S:\KI\Vladmandic1111\modules\call_queue.py:61 in f ││ ││ 60 │ │ │ │ pr.enable() ││ ❱ 61 │ │ │ res = list(func(*args, **kwargs)) ││ 62 │ │ │ if shared.cmd_opts.profile: ││ ││ S:\KI\Vladmandic1111\modules\call_queue.py:39 in f ││ ││ 38 │ │ │ try: ││ ❱ 39 │ │ │ │ res = func(*args, **kwargs) ││ 40 │ │ │ finally: ││ ││ ... 4 frames hidden ... ││ ││ S:\KI\Vladmandic1111\venv\lib\site-packages\imageio\plugins\ffmpeg.py:600 in _append_data ││ ││ 599 │ │ │ # Write. Yes, we can send the data in as a numpy array ││ ❱ 600 │ │ │ self._write_gen.send(im) ││ 601 ││ ││ S:\KI\Vladmandic1111\venv\lib\site-packages\imageio_ffmpeg_io.py:637 in write_frames ││ ││ 636 │ │ │ │ ) ││ ❱ 637 │ │ │ │ raise IOError(msg) ││ 638 │╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯OSError: [Errno 32] Broken pipe

FFMPEG COMMAND:
S:\KI\Vladmandic1111\venv\lib\site-packages\imageio_ffmpeg\binaries\ffmpeg-win64-v4.2.2.exe -y -f rawvideo -vcodec rawvideo -s 1195x849 -pix_fmt rgb24 -r 30.00 -i - -an -vcodec
libx264 -pix_fmt yuv420p -v warning S:\KI\Vladmandic1111\infinite-zooms\infinite_zoom_1682034171.mp4

FFMPEG STDERR OUTPUT:

Traceback (most recent call last):
File "S:\KI\Vladmandic1111\venv\lib\site-packages\gradio\blocks.py", line 987, in postprocess_data
if predictions[i] is components._Keywords.FINISHED_ITERATING:
IndexError: tuple index out of range

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "S:\KI\Vladmandic1111\venv\lib\site-packages\gradio\routes.py", line 394, in run_predict
output = await app.get_blocks().process_api(
File "S:\KI\Vladmandic1111\venv\lib\site-packages\gradio\blocks.py", line 1078, in process_api
data = self.postprocess_data(fn_index, result["prediction"], state)
File "S:\KI\Vladmandic1111\venv\lib\site-packages\gradio\blocks.py", line 991, in postprocess_data
raise ValueError(
ValueError: Number of output components does not match number of values returned from from function f

360 Panorama

Any guide on how to generate 360 Panorama?

[BUG] Black and white, greyscale, output.

Describe the bug
Everything I generate using the extension after updating both SD and IZ comes out greyscale. The first generation is in colour but from then onwards they are all black and white for some reason. I've tried prompting against this and using various different options but I can't seem to get this to change.

To Reproduce
Steps to reproduce the behavior:

1. Enter these inputs 'default settings'
2. Click on 'generate'

Expected behavior
I expect it to return colour generations















Screenshots of error
If applicable, add screenshots to help explain your problem. Or just dump the error.

Desktop (please complete the following information):

• OS: Windows 10
• Version 22H2

Additional context
Add any other context about the problem here.

Create an interrupt/skip button

I added SendtoPanoramaViewer button, need higher resolution

The InfZoom Extension is nice to create panorama videos, when using a 360-panorama-LORA or just prompt "360 full panorama view"
My extension has a 360-panorama-viewer integrated and I added a sento-button, see screenshot.

360 Panoramas need much resolution. Is there an UI-setting planned to setup resolution? and or include an upscaler? nice if details could be added while upscaling.

https://github.com/GeorgLegato/sd-webui-panorama-viewer

install broke webui

After following the simple install steps, now:

error, not working

Describe the bug
Returns error, not working. It used to work before.

To Reproduce
Steps to reproduce the behavior:

1. Run Automatic1111
2. Infinite zoom tab, all initial settings. Click on 'Generate Video'...
3. returns error

Expected behavior
Should generate video.

Screenshots of error

Batch 1/1
  0%|                                                   | 0/50 [00:01<?, ?it/s]
Error completing request
Arguments: ([[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> ']], 'frames, borderline, text, character, duplicate, error, out of frame, watermark, low quality, ugly, deformed, blur  bad-artist', 8, 7, 50, None, None, 30, 0, 0, 0, 1, 0, 2, False, 0, 1, 512, 512, 1, 'Euler a', False, 'None', 1) {}
Traceback (most recent call last):
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\modules\call_queue.py", line 56, in f
    res = list(func(*args, **kwargs))
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\modules\call_queue.py", line 37, in f
    res = func(*args, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\extensions\infinite-zoom-automatic1111-webui\scripts\infinite-zoom.py", line 242, in create_zoom
    result = create_zoom_single(
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\extensions\infinite-zoom-automatic1111-webui\scripts\infinite-zoom.py", line 330, in create_zoom_single
    processed = renderTxt2Img(
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\extensions\infinite-zoom-automatic1111-webui\scripts\infinite-zoom.py", line 132, in renderTxt2Img
    processed = process_images(p)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\modules\processing.py", line 503, in process_images
    res = process_images_inner(p)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 42, in processing_process_images_hijack
    return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\modules\processing.py", line 653, in process_images_inner
    samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\modules\processing.py", line 869, in sample
    samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 358, in sample
    samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 234, in launch_sampling
    return func()
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 358, in <lambda>
    samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 145, in sample_euler_ancestral
    denoised = model(x, sigmas[i] * s_in, **extra_args)
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 126, in forward
    x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict([cond_in], image_cond_in))
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 167, in forward
    return self.get_v(input * c_in, self.sigma_to_t(sigma), **kwargs) * c_out + input * c_skip
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 177, in get_v
    return self.inner_model.apply_model(x, t, cond)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\modules\sd_hijack_utils.py", line 17, in <lambda>
    setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\modules\sd_hijack_utils.py", line 28, in __call__
    return self.__orig_func(*args, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858, in apply_model
    x_recon = self.model(x_noisy, t, **cond)
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1335, in forward
    out = self.diffusion_model(x, t, context=cc)
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 797, in forward
    h = module(h, emb, context)
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 84, in forward
    x = layer(x, context)
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 334, in forward
    x = block(x, context=context[i])
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 269, in forward
    return checkpoint(self._forward, (x, context), self.parameters(), self.checkpoint)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\util.py", line 121, in checkpoint
    return CheckpointFunction.apply(func, len(inputs), *args)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\util.py", line 136, in forward
    output_tensors = ctx.run_function(*ctx.input_tensors)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 273, in _forward
    x = self.attn2(self.norm2(x), context=context) + x
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\modules\sd_hijack_optimizations.py", line 332, in xformers_attention_forward
    k_in = self.to_k(context_k)
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\extensions-builtin\Lora\lora.py", line 305, in lora_Linear_forward
    lora_apply_weights(self)
  File "D:\Graphics\stable-diffusion-webui\stable-diffusion-webui\extensions-builtin\Lora\lora.py", line 273, in lora_apply_weights
    self.weight += lora_calc_updown(lora, module, self.weight)
RuntimeError: The size of tensor a (1024) must match the size of tensor b (768) at non-singleton dimension 1

Traceback (most recent call last):
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 987, in postprocess_data
    if predictions[i] is components._Keywords.FINISHED_ITERATING:
IndexError: tuple index out of range

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\gradio\routes.py", line 394, in run_predict
    output = await app.get_blocks().process_api(
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 1078, in process_api
    data = self.postprocess_data(fn_index, result["prediction"], state)
  File "d:\Graphics\stable-diffusion-webui\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 991, in postprocess_data
    raise ValueError(
ValueError: Number of output components does not match number of values returned from from function f

Desktop (please complete the following information):

• Windows
• 10

Additional context
I was able to use it before, seems something broke after updates.

High gpu usage when UI is open and processing?

Whenever I have chrome open and infinite zoom is processing GPU load specifically shoots up like crazy. However if I minify a1111 chrome window a lot of usage drops and processing is working as it should. I noticed this only happening with infinite zoom.

This is weird, I'm assuming some kind of UI reporting code is written in a blocking way?

[BUG] "ZIP" or "Save" button from sd-webui should export all frames from the gallery for further (re)use

Describe the bug
Make Save and ZIP button working

To Reproduce
create any movie
see you have frames in the gallery shown
click SAVE or ZIP
check console for error from webui-framework, we doe not set information properly needed to store Zip file

Expected behavior
Frame should be saved or zipped as output

Screenshots of error

Desktop (please complete the following information):

• OS: Windows
• Version 10

Automatic 1111 latest (1.1)

Weird Outpaint Issues

hi @v8hid,
thank you for working on this, the ui looks great!

I'm not sure if you were previously aware some others were also working on infinite zoom:
https://github.com/coolzilj/infinite-zoom
https://github.com/juanigsrz/sd-fractal-zoom

And there seems to be a problem with webui's outpainting itself, noted - https://github.com/coolzilj/infinite-zoom#known-issues

You may notice a distinct frame or seam around the image, although it's less noticeable in the original diffusers version.

There are some experts in webui discussions posts who may know the reason, I don't.
Maybe we could see what @coolzilj thinks about this issue, and which extension is better to be maintained

Error Progress tracking requires queuing to be enabled

venv "stable-diffusion-webui\venv\Scripts\Python.exe"
Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug 1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Commit hash: 00dab8f10defbbda579a1bc89c8d4e972c58a20d
Installing requirements for Web UI
Installing requirements 1 for Infinite-Zoom

#######################################################################################################
Initializing Dreambooth
If submitting an issue on github, please provide the below text for debugging purposes:

Python revision: 3.10.6 (tags/v3.10.6:9c7b4bd, Aug 1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Dreambooth revision: 43ae9d55531004f1dedaea7ac2443e9b16739913
SD-WebUI revision: 00dab8f10defbbda579a1bc89c8d4e972c58a20d

Checking Dreambooth requirements...
[+] bitsandbytes version 0.35.0 installed.
[+] diffusers version 0.10.2 installed.
[+] transformers version 4.25.1 installed.
[+] xformers version 0.0.16rc425 installed.
[+] torch version 1.13.1+cu117 installed.
[+] torchvision version 0.14.1+cu117 installed.

#######################################################################################################

Launching Web UI with arguments: --xformers
[AddNet] Updating model hashes...
0it [00:00, ?it/s]
[AddNet] Updating model hashes...
0it [00:00, ?it/s]
SD-Webui API layer loaded
Loading weights [e6415c4892] from stable-diffusion-webui\models\Stable-diffusion\realisticVisionV20_v20.safetensors
Creating model from config: stable-diffusion-webui\configs\v1-inference.yaml
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.52 M params.
Applying xformers cross attention optimization.
Model loaded in 6.4s (create model: 0.5s, apply weights to model: 1.1s, apply half(): 1.3s, load VAE: 1.2s, move model to device: 0.9s, load textual inversion embeddings: 1.2s).
Traceback (most recent call last):
File "\stable-diffusion-webui\launch.py", line 361, in
start()
File "\stable-diffusion-webui\launch.py", line 356, in start
webui.webui()
File "\stable-diffusion-webui\webui.py", line 202, in webui
app, local_url, share_url = shared.demo.launch(
File "\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 1337, in launch
raise ValueError("Progress tracking requires queuing to be enabled.")
ValueError: Progress tracking requires queuing to be enabled.
Press any key to continue . . .

[Feature]How about adding an option to move the image horizontally and vertically in addition to zooming in and out?

Thank you for the wonderful work! Zooming in and zooming out works very well. How about adding an option to move the image horizontally and vertically in addition to zooming in and out?

[BUG] - Missing .dll files

Describe the bug
The program can't generate the video, I keep getting missing .ddl files, and when I download them I get new missing ones. No errors in console. I also added the path to the executables (ffmpeg.exe, ecc).

To Reproduce
Steps to reproduce the behavior:

1. Start generating the video.
2. I get the inpainted image, but not the video.

Screenshots of error
No errors in console, just missing files (there were other ones too, but I downloaded them...).

Desktop (please complete the following information):

• OS: Windows
• Version: 11

Additional context
I had this problem even before the main webui update, so I don't think is a torch 2.0.0 or something else error.

Error when generating

Error completing request1:05, 3.69s/it]
Arguments: ([[0, 'cyberpunk themed world'], ['', ''], ['', '']], 'frames, borderline, text, character, duplicate, error, out of frame, watermark, low quality, ugly, deformed, blur', 8, 7, 50, None, 30, 0, 0, 0, 1, 0, 2, False, 0, 1, 512) {}
Traceback (most recent call last):
File "/Users/xxxx/stable-diffusion-webui/modules/call_queue.py", line 56, in f
res = list(func(*args, **kwargs))
File "/Users/xxxx/stable-diffusion-webui/modules/call_queue.py", line 37, in f
res = func(*args, **kwargs)
File "/Users/xxxx/stable-diffusion-webui/extensions/infinite-zoom-automatic1111-webui/scripts/inifnite-zoom.py", line 227, in create_zoom
write_video(
File "/Users/xxxx/stable-diffusion-webui/extensions/infinite-zoom-automatic1111-webui/iz_helpers/video.py", line 35, in write_video
writer.append_data(np_frame)
File "/Users/xxxx/stable-diffusion-webui/venv/lib/python3.10/site-packages/imageio/core/format.py", line 590, in append_data
return self._append_data(im, total_meta)
File "/Users/xxxx/stable-diffusion-webui/venv/lib/python3.10/site-packages/imageio/plugins/ffmpeg.py", line 587, in _append_data
self._initialize()
File "/Users/xxxx/stable-diffusion-webui/venv/lib/python3.10/site-packages/imageio/plugins/ffmpeg.py", line 648, in _initialize
self._write_gen.send(None)
File "/Users/xxxx/stable-diffusion-webui/venv/lib/python3.10/site-packages/imageio_ffmpeg/_io.py", line 509, in write_frames
codec = get_first_available_h264_encoder()
File "/Users/xxxx/stable-diffusion-webui/venv/lib/python3.10/site-packages/imageio_ffmpeg/_io.py", line 125, in get_first_available_h264_encoder
compiled_encoders = get_compiled_h264_encoders()
File "/Users/xxxx/stable-diffusion-webui/venv/lib/python3.10/site-packages/imageio_ffmpeg/_io.py", line 59, in get_compiled_h264_encoders
cmd = [get_ffmpeg_exe(), "-hide_banner", "-encoders"]
File "/Users/xxxx/stable-diffusion-webui/venv/lib/python3.10/site-packages/imageio_ffmpeg/_utils.py", line 33, in get_ffmpeg_exe
raise RuntimeError(
RuntimeError: No ffmpeg exe could be found. Install ffmpeg on your system, or set the IMAGEIO_FFMPEG_EXE environment variable.

Traceback (most recent call last):
File "/Users/xxxx/stable-diffusion-webui/venv/lib/python3.10/site-packages/gradio/blocks.py", line 987, in postprocess_data
if predictions[i] is components._Keywords.FINISHED_ITERATING:
IndexError: tuple index out of range

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/Users/xxxx/stable-diffusion-webui/venv/lib/python3.10/site-packages/gradio/routes.py", line 394, in run_predict
output = await app.get_blocks().process_api(
File "/Users/xxxx/stable-diffusion-webui/venv/lib/python3.10/site-packages/gradio/blocks.py", line 1078, in process_api
data = self.postprocess_data(fn_index, result["prediction"], state)
File "/Users/xxxx/stable-diffusion-webui/venv/lib/python3.10/site-packages/gradio/blocks.py", line 991, in postprocess_data
raise ValueError(
ValueError: Number of output components does not match number of values returned from from function f

Upscaling acceleration

When I tried InfiniteZoom together with upscaling, I found that it upscales every each frame of the video, which is unnecessary in this case. It would be enough to upscale only the main generated frames and do the zooming on the upscaled ones. That would save a lot of time.

The implementation seemed simple to me, so I wanted to take it on and code this feature directly. However, I found out that there is already the optimize_upscale branch by @GeorgLegato that does exactly this.

I want to ask, what does the future look like with this feature? If that branch isn't in the development, I'd be happy to take it on, I just find the modifications unnecessarily complicated. My idea is more simple:

1. after generating the images, upscale all of them.
2. skip/disable upscaling everywhere else

first click on generate fails

I think it needs to wait for model loading

Help[BUG]

Hi, I get following errors and don't know what to do:

Error loading script: infinite-zoom.py

File "D:\AI\stable-diffusion-webui-master\stable-diffusion-webui-master\scripts\infinite-zoom.py", line 2, in
from iz_helpers.ui import on_ui_tabs
ModuleNotFoundError: No module named 'iz_helpers'

Error loading script: infinite-zoom.py

File "D:\AI\stable-diffusion-webui-master\stable-diffusion-webui-master\extensions\infinite-zoom-automatic1111-webui\scripts\infinite-zoom.py", line 2, in
from iz_helpers.ui import on_ui_tabs
File "D:\AI\stable-diffusion-webui-master\stable-diffusion-webui-master\extensions\infinite-zoom-automatic1111-webui\iz_helpers\ui.py", line 2, in
from .run import create_zoom
File "D:\AI\stable-diffusion-webui-master\stable-diffusion-webui-master\extensions\infinite-zoom-automatic1111-webui\iz_helpers\run.py", line 6, in
from modules.paths_internal import script_path
ModuleNotFoundError: No module named 'modules.paths_internal'

[Feature] Enable setting a manual seed & seed behavior for next generation

Feature request: allow to control for the seed used.

Error message in console, but generation still works.

Hi, and thanks for the cool extension! I figured I'd let you know that I've been getting an error message in the console on every run regardless of settings, and it's been persisting through the recent updates. The error doesn't seem to actually hurt anything as far as I can tell, but I don't know hardly anything about Python so all I can see in the error message is that it looks like SD is trying to talk to my system Python, rather than my venv Python, but I have no idea really, sorry! In any case here's the error message copied from the console, it shows up after every generation when I use Infinite Zoom;

Exception in callback _ProactorBasePipeTransport._call_connection_lost(None)
handle: <Handle _ProactorBasePipeTransport._call_connection_lost(None)>
Traceback (most recent call last):
File "C:\Users\blast\AppData\Local\Programs\Python\Python310\lib\asyncio\events.py", line 80, in _run
self._context.run(self._callback, *self._args)
File "C:\Users\blast\AppData\Local\Programs\Python\Python310\lib\asyncio\proactor_events.py", line 165, in _call_connection_lost
self._sock.shutdown(socket.SHUT_RDWR)
ConnectionResetError: [WinError 10054] An existing connection was forcibly closed by the remote host

Edit: Forgot to add any relevant info, but if it helps I'm on the latest build of Auto's and I'm using the latest version of this extension as well. I've got a 2070 Super with 8 gigs, and if there's anything else that might help then please let me know, thanks!

Getting rid of the frame seam

One issue with outpainting an image without a mask_blur is that it can result in a noticeable frame around the edges of the image. While using an inpainting model can help to reduce this effect, there may still be instances where the frame is visible or there is a noticeable color shift.

However, using mask_blur presents another challenge - while it can help to create a smoother and more visually appealing outpainted image,

In practice, the use of mask_blur can cause some issues with the gradual zoom effect process. This is because the blur effect can slightly remove edges with a margin, leading to potential visual artifacts or inconsistencies in the zoom effect. which something like this:

The possible solution I came up with is to crop the initial image from the second generated image and replace the first frame with it. And repeat it for every iteration.

Automatic 1111 WebUI Extension is missing after latest update

As the title suggests, the Automatic 1111 WebUI Extension for Infinite Zoom is missing after I updated it. I used it yesterday for many hours. No problems. The update has caused some sort of issue. I still see Infinite Zoom in my extensions folder and it is active but the tab is nowhere to be found. I reinstalled Infinite Zoom and restarted "webui-user.bat". It did not make a difference. Any solutions or a way to rollback to the previous version?

• OS: Windows 10
• Version 22H2
• Automatic 1111 running in Google Chrome browser

Defaults prompts were broken after recent update.

Hi folks, sorry if I'm doing this wrong but I noticed that after a recent update my default prompts box was showing an error and telling me to check the settings. In the settings menu the default prompt was all on one long line and had some Loras and a bunch of other stuff in it, so I copied the example prompts from your Wiki page into the prompt boxes, exported them, and then copied them neatly into the settings menu as new defaults and sort of tidied it all up a bit. I closed everything and relaunched, and it works perfectly now.

I'm not sure if I'm the only one having this problem, but if anyone is interested here is how I setup the defaults in the settings menu, maybe it will help anyone else with the same problem. I wasn't sure about where to put the linebreaks so I just did it however, probably isn't quite proper but it works now :D I did lose the default negative somehow tho, sorry. Oh by the way, is there any way to add the number of steps to the default options menu, or have it exported with saved prompts? I tried sticking a "20" in there in a few different places but it didn't work lol.
Edit: When I pasted it into here it seems to have messed up the indents and stuff, no idea how to fix that sorry! Looks good while I'm editing and then gets flattened out when I'm done, gross lol

{"prompts":
{"data":
[
[0,"jungle with lush green trees and clear blue sky"],
["5","jungle with tall brown trees and orange sunset sky"],
["10","jungle with sparse trees and dark stormy sky"],
["15","jungle with yellow autumn trees and purple twilight sky"]
],
"headers":
["Steps","Prompts"]
},
"negPrompt":
"blur, blurry, split frame, drawing, painting, illustration, sketch, watermark, logo, monochrome"
}

Improving the prompt table

is super annoying. I am not sure if it's gradio, my system or what but if I try to copy/paste, type or whatever the prompt box gets cleared and I have to click several times. it just seems janky.

Can you just make it a standard text box?

[Feature] Progress bar

I can check progress from the command line, but the UI progress bar is not updated. Any chance this can be integrated?

[FEATURE] ControlNet txt2img inpainting method

There is a promising new outpainting method, see this whole thread here: Mikubill/sd-webui-controlnet#1464 (comment)

Maybe it can be incorporated? Works with non-inpainting models and doens't need a prompt.