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| author | random_thoughtss <random_thoughtss@proton.me> | 2022-10-27 11:45:35 -0700 |
|---|---|---|
| committer | random_thoughtss <random_thoughtss@proton.me> | 2022-10-27 11:45:35 -0700 |
| commit | b68c7c437eda2840a304539dd2acd0b0894e920c (patch) | |
| tree | c35930f6063bd6b57bdf3f698b66fa0de5361ae6 | |
| parent | a38496c1deef12f56f74f8abce2034bef8bdaccb (diff) | |
Updated name and hover text.
| -rw-r--r-- | javascript/hints.js | 1 | ||||
| -rw-r--r-- | modules/shared.py | 2 |
2 files changed, 2 insertions, 1 deletions
diff --git a/javascript/hints.js b/javascript/hints.js index 6ddd6aec..623bc25c 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -75,6 +75,7 @@ titles = { "Create style": "Save current prompts as a style. If you add the token {prompt} to the text, the style use that as placeholder for your prompt when you use the style in the future.", "Checkpoint name": "Loads weights from checkpoint before making images. You can either use hash or a part of filename (as seen in settings) for checkpoint name. Recommended to use with Y axis for less switching.", + "Inpainting conditioning mask strength": "Only applies to inpainting models. Determines how strongly to mask off the original image for inpainting and img2img. 1.0 means fully masked, which is the default behaviour. 0.0 means a fully unmasked conditioning. Lower values will help preserve the overall composition of the image, but will struggle with large changes.", "vram": "Torch active: Peak amount of VRAM used by Torch during generation, excluding cached data.\nTorch reserved: Peak amount of VRAM allocated by Torch, including all active and cached data.\nSys VRAM: Peak amount of VRAM allocation across all applications / total GPU VRAM (peak utilization%).", diff --git a/modules/shared.py b/modules/shared.py index 9c2fa0d4..7c428d90 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -267,7 +267,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
"sd_hypernetwork": OptionInfo("None", "Hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
"sd_hypernetwork_strength": OptionInfo(1.0, "Hypernetwork strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.001}),
- "inpainting_mask_weight": OptionInfo(1.0, "Strength of img2img conditioning mask for inpainting models.", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
+ "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
"img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
"save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),
"img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."),
|