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@ -1,3 +1,6 @@
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### v2.4.0 - 2025 Dec.30
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- Implement Randomize for **Noise** and **Scaling**
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### v2.3.2 - 2024 Nov.06
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- Linting *(`internal`)*
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@ -232,7 +232,8 @@ Hires upscale: 1.5, Hires steps: 12, Hires upscaler: 2xNomosUni_esrgan_multijpg
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> The following settings are in the **Vectorscope CC** section under the **Stable Diffusion** category of the **Settings** tab
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- Append the parameters to the infotext
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- Disable `do_not_save_to_config` to use the Webui **Defaults** functionality
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- Disable `do_not_save_to_config` to use the Webui's **Defaults** feature
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- Also randomize the **Noise** and **Scaling** settings
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- Set the `minimum` and `maximum` range for each parameter
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## Roadmap
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@ -331,7 +332,7 @@ In the **Script** `Dropdown` at the bottom, there is now a new **`High Dynamic R
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- **(Recommended)** Use a deterministic sampler and high enough steps. `Euler` *(**not** `Euler a`)* works well in my experience
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#### Options
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- **Brackets:** The numer of images to generate
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- **Brackets:** The number of images to generate
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- **Gaps:** The brightness difference between each image
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- **Automatically Merge:** When enabled, this will merge the images using an `OpenCV` algorithm and save to the `HDR` folder in the `outputs` folder
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- Disable this if you want to merge them yourself using better external program
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@ -1,4 +1,5 @@
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from modules.shared import opts
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import gradio as gr
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import random
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@ -47,3 +48,41 @@ def init():
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getattr(opts, "cc_color_max", 4.0),
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0.0,
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)
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def rand_method(*, orig=None):
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if not opts.cc_rand_method:
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return gr.update() if orig is None else orig
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v = random.choice(
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(
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"Straight",
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"Straight Abs.",
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"Cross",
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"Cross Abs.",
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"Ones",
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"N.Random",
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"U.Random",
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"Multi-Res",
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"Multi-Res Abs.",
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)
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)
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return gr.update(value=v) if orig is None else v
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def rand_scaling(*, orig=None):
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if not opts.cc_rand_scaling:
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return gr.update() if orig is None else orig
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v = random.choice(
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(
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"Flat",
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"Cos",
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"Sin",
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"1 - Cos",
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"1 - Sin",
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)
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)
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return gr.update(value=v) if orig is None else v
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@ -27,11 +27,31 @@ def settings():
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category_id="sd",
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onchange=reset_ui_config,
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)
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.info("uncheck this option if you wish to use the built-in Defaults function")
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.info("disable this option if you wish to use the built-in Defaults feature")
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.info("enable again if the extension is not working correctly after an update")
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.needs_reload_ui(),
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)
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opts.add_option(
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"cc_rand_method",
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OptionInfo(
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False,
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"Randomize the Noise Settings as well",
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section=section,
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category_id="sd",
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),
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)
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opts.add_option(
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"cc_rand_scaling",
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OptionInfo(
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False,
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"Randomize the Scaling Settings as well",
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section=section,
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category_id="sd",
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),
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)
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for lbl, minVal, maxVal in [
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("Brightness", (-5.0, 0.0), (0.0, 5.0)),
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("Contrast", (-5.0, 0.0), (0.0, 5.0)),
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@ -2,6 +2,7 @@ from modules.sd_samplers_kdiffusion import KDiffusionSampler
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from modules.shared import opts
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from modules import scripts
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from lib_cc.const import rand_method, rand_scaling
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from lib_cc.colorpicker import create_colorpicker
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from lib_cc.callback import hook_callbacks
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from lib_cc.style import StyleManager
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@ -12,7 +13,7 @@ from random import seed
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import gradio as gr
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VERSION = "2.3.2"
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VERSION = "2.4.0"
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style_manager = StyleManager()
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@ -242,6 +243,8 @@ class VectorscopeCC(scripts.Script):
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gr.update(value=const.Color.rand()),
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gr.update(value=const.Color.rand()),
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gr.update(value=const.Color.rand()),
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rand_method(),
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rand_scaling(),
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]
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reset_btn.click(
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@ -256,7 +259,7 @@ class VectorscopeCC(scripts.Script):
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random_btn.click(
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fn=on_random,
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outputs=[bri, con, sat, r, g, b],
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outputs=[bri, con, sat, r, g, b, method, scaling],
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show_progress="hidden",
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).then(
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fn=None,
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@ -360,13 +363,23 @@ class VectorscopeCC(scripts.Script):
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g = const.Color.rand()
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b = const.Color.rand()
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print(f"\n[Seed: {cc_seed}]")
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print(f"\n\n[Seed: {cc_seed}]")
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print(f"> Brightness: {bri}")
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print(f"> Contrast: {con}")
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print(f"> Saturation: {sat}")
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print(f"> R: {r}")
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print(f"> G: {g}")
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print(f"> B: {b}\n")
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print(f"> B: {b}")
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if getattr(opts, "cc_rand_method", False):
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method = rand_method(orig=method)
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print(f"> Noise: {method}")
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if getattr(opts, "cc_rand_scaling", False):
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scaling = rand_method(orig=scaling)
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print(f"> Scaling: {scaling}")
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print("\n")
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if getattr(opts, "cc_metadata", True):
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p.extra_generation_params.update(
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