features updates
unused code removed from outpainting mk2
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AUTOMATIC
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README.md
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README.md
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@ -11,44 +11,56 @@ Check the [custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-web
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- One click install and run script (but you still must install python and git)
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- Outpainting
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- Inpainting
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- Prompt matrix
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- Prompt
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- Stable Diffusion upscale
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- Attention
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- Loopback
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- X/Y plot
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- Attention, specify parts of text that the model should pay more attention to
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- a man in a ((txuedo)) - will pay more attentinoto tuxedo
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- a man in a (txuedo:1.21) - alternative syntax
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- Loopback, run img2img procvessing multiple times
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- X/Y plot, a way to draw a 2 dimensional plot of images with different parameters
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- Textual Inversion
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- have as many embeddings as you want and use any names you like for them
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- use multiple embeddings with different numbers of vectors per token
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- works with half precision floating point numbers
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- Extras tab with:
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- GFPGAN, neural network that fixes faces
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- CodeFormer, face restoration tool as an alternative to GFPGAN
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- RealESRGAN, neural network upscaler
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- ESRGAN, neural network with a lot of third party models
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- ESRGAN, neural network upscaler with a lot of third party models
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- SwinIR, neural network upscaler
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- LDSR, Latent diffusion super resolution upscaling
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- Resizing aspect ratio options
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- Sampling method selection
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- Interrupt processing at any time
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- 4GB video card support
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- Correct seeds for batches
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- 4GB video card support (also reports of 2GB working)
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- Correct seeds for batches
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- Prompt length validation
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- Generation parameters added as text to PNG
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- Tab to view an existing picture's generation parameters
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- get length of prompt in tokensas you type
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- get a warning after geenration if some text was truncated
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- Generation parameters
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- parameters you used to generate images are saved with that image
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- in PNG chunks for PNG, in EXIF for JPEG
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- can drag the image to PNG info tab to restore generation parameters and automatically copy them into UI
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- can be disabled in settings
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- Settings page
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- Running custom code from UI
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- Running arbitrary python code from UI (must run with commandline flag to enable)
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- Mouseover hints for most UI elements
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- Possible to change defaults/mix/max/step values for UI elements via text config
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- Random artist button
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- Tiling support: UI checkbox to create images that can be tiled like textures
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- Tiling support, a checkbox to create images that can be tiled like textures
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- Progress bar and live image generation preview
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- Negative prompt
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- Styles
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- Variations
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- Seed resizing
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- CLIP interrogator
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- Prompt Editing
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- Batch Processing
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- Negative prompt, an extra text field that allows you to list what you don't want to see in generated image
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- Styles, a way to save part of prompt and easily apply them via dropdown later
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- Variations, a way to generate same image but with tiny differences
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- Seed resizing, a way to generate same image but at slightly different resolution
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- CLIP interrogator, a button that tries to guess prompt from an image
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- Prompt Editing, a way to change prompt mid-generation, say to start making a watermelon and switch to anime girl midway
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- Batch Processing, process a group of files using img2img
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- Img2img Alternative
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- Highres Fix
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- LDSR Upscaling
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- Highres Fix, a convenience option to produce high resolution pictures in one click without usual distortions
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- Reloading checkpoints on the fly
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- Checkpoint Merger, a tab that allows you to merge two checkpoints into one
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- [Custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Scripts) with many extensions from community
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## Installation and Running
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Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for both [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended) and [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
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@ -11,46 +11,8 @@ from modules import images, processing, devices
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from modules.processing import Processed, process_images
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from modules.shared import opts, cmd_opts, state
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# https://github.com/parlance-zz/g-diffuser-bot
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def expand(x, dir, amount, power=0.75):
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is_left = dir == 3
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is_right = dir == 1
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is_up = dir == 0
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is_down = dir == 2
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if is_left or is_right:
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noise = np.zeros((x.shape[0], amount, 3), dtype=float)
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indexes = np.random.random((x.shape[0], amount)) ** power * (1 - np.arange(amount) / amount)
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if is_right:
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indexes = 1 - indexes
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indexes = (indexes * (x.shape[1] - 1)).astype(int)
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for row in range(x.shape[0]):
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if is_left:
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noise[row] = x[row][indexes[row]]
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else:
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noise[row] = np.flip(x[row][indexes[row]], axis=0)
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x = np.concatenate([noise, x] if is_left else [x, noise], axis=1)
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return x
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if is_up or is_down:
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noise = np.zeros((amount, x.shape[1], 3), dtype=float)
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indexes = np.random.random((x.shape[1], amount)) ** power * (1 - np.arange(amount) / amount)
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if is_down:
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indexes = 1 - indexes
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indexes = (indexes * x.shape[0] - 1).astype(int)
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for row in range(x.shape[1]):
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if is_up:
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noise[:, row] = x[:, row][indexes[row]]
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else:
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noise[:, row] = np.flip(x[:, row][indexes[row]], axis=0)
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x = np.concatenate([noise, x] if is_up else [x, noise], axis=0)
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return x
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# this function is taken from https://github.com/parlance-zz/g-diffuser-bot
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def get_matched_noise(_np_src_image, np_mask_rgb, noise_q=1, color_variation=0.05):
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# helper fft routines that keep ortho normalization and auto-shift before and after fft
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def _fft2(data):
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