opt

.github/FUNDING.yml

@@ -1 +1 @@
-ko_fi: haoming
+ko_fi: haoming

CHANGELOG.md

@@ -1,3 +1,7 @@
+### v2.2.4 - 2024 Aug.28
+- Optimization *(`internal`)*
+- Improve Color **Accuracy** ~~Slightly~~
+
 ### v2.2.3 - 2024 Aug.27
 - Lib *(`internal`)*
 

README.md

@@ -10,10 +10,10 @@ allowing you to adjust the brightness, contrast, and color of the generations.
 After installing this Extension, you will see a new section in both **txt2img** and **img2img** tabs.
 Refer to the parameters and sample images below and play around with the values.
 
-**Note:** Since this modifies the underlying latent noise, the composition may change drastically.
+> **Note:** Since this modifies the underlying latent noise, the composition may change drastically
 
 #### Parameters
-- **Enable:** Turn on/off this Extension
+- **Enable:** Turn on / off this Extension
 - **Alt:** Modify an alternative Tensor instead, causing the effects to be significantly stronger
 - **Brightness:** Adjust the overall brightness of the image
 - **Contrast:** Adjust the overall contrast of the image

javascript/vec_cc.js

@@ -1,7 +1,11 @@
 class VectorscopeCC {
 
-    static dot = { 'txt': null, 'img': null };
+    static dot = { 'txt': undefined, 'img': undefined };
 
+    /**
+     * @param {number} r @param {number} g @param {number} b
+     * @param {string} mode "txt" | "img"
+     */
     static updateCursor(r, g, b, mode) {
         const mag = Math.abs(r) + Math.abs(g) + Math.abs(b);
         var condX, condY;
@@ -18,6 +22,11 @@ class VectorscopeCC {
         this.dot[mode].style.top = `calc(50% + ${condY - 12}px)`;
     }
 
+    /**
+     * @param {HTMLImageElement} wheel
+     * @param {HTMLInputElement[]} sliders
+     * @param {HTMLImageElement} dot
+     */
     static registerPicker(wheel, sliders, dot) {
         ['mousemove', 'click'].forEach((event) => {
             wheel.addEventListener(event, (e) => {
@@ -35,20 +44,7 @@ class VectorscopeCC {
                 const x = ((e.clientX - rect.left) - 100.0) / 25;
                 const y = ((e.clientY - rect.top) - 100.0) / 25;
 
-                const zeta = Math.atan(y / x);
+                var r = -0.077 * (4.33 * x + 7.5 * y);
-                var degree = 0;
-
-                if (x >= 0) {
-                    if (y >= 0)
-                        degree = zeta * 180 / Math.PI;
-                    else
-                        degree = 360 + zeta * 180 / Math.PI;
-                }
-                else if (x < 0) {
-                    degree = 180 + zeta * 180 / Math.PI;
-                }
-
-                var r = -(0.00077 * (433 * x * degree + 750 * y * degree) / degree);
                 var g = y / 0.866 + r;
                 var b = x + 0.5 * r + 0.5 * g;
 

lib_cc/callback.py

@@ -1,5 +1,5 @@
 from modules.sd_samplers_kdiffusion import KDiffusionSampler
-from modules import script_callbacks, devices
+from modules.script_callbacks import on_script_unloaded
 from functools import wraps
 from random import random
 import torch
@@ -45,19 +45,19 @@ class NoiseMethods:
         """
 
         noise = NoiseMethods.zeros(latent) if use_zero else NoiseMethods.ones(latent)
-        batchSize, c, w, h = noise.shape
+        b, c, w, h = noise.shape
 
-        device = devices.get_optimal_device()
+        device = latent.device
         upsampler = torch.nn.Upsample(size=(w, h), mode="bilinear").to(device)
 
-        for b in range(batchSize):
+        for batch in range(b):
             for i in range(iterations):
                 r = random() * 2 + 2
 
                 wn = max(1, int(w / (r**i)))
                 hn = max(1, int(h / (r**i)))
 
-                noise[b] += (
+                noise[batch] += (
                     upsampler(torch.randn(1, c, hn, wn).to(device)) * discount**i
                 )[0]
 
@@ -67,10 +67,10 @@ class NoiseMethods:
         return noise / noise.std()
 
 
-def RGB_2_CbCr(r: float, g: float, b: float) -> float:
+def RGB_2_CbCr(r: float, g: float, b: float) -> tuple[float, float]:
     """Convert RGB channels into YCbCr for SDXL"""
-    cb = -0.15 * r - 0.29 * g + 0.44 * b
+    cb = -0.17 * r - 0.33 * g + 0.5 * b
-    cr = 0.44 * r - 0.37 * g - 0.07 * b
+    cr = 0.5 * r - 0.41 * g - 0.08 * b
 
     return cb, cr
 
@@ -94,7 +94,8 @@ def cc_callback(self, d):
 
     mode = str(self.vec_cc["mode"])
     method = str(self.vec_cc["method"])
-    source = d[mode]
+    source: torch.Tensor = d[mode]
+    target: torch.Tensor = None
 
     if "Straight" in method:
         target = d[mode].detach().clone()
@@ -175,4 +176,4 @@ def restore_callback():
     KDiffusionSampler.callback_state = original_callback
 
 
-script_callbacks.on_script_unloaded(restore_callback)
+on_script_unloaded(restore_callback)

lib_cc/colorpicker.py

@@ -7,17 +7,17 @@ DOT = os.path.join(scripts.basedir(), "scripts", "dot.png")
 
 
 def create_colorpicker(is_img: bool):
-    m = "img" if is_img else "txt"
+    m: str = "img" if is_img else "txt"
 
     gr.Image(
-        WHEEL,
+        value=WHEEL,
         interactive=False,
         container=False,
         elem_id=f"cc-colorwheel-{m}",
     )
 
     gr.Image(
-        DOT,
+        value=DOT,
         interactive=False,
         container=False,
         elem_id=f"cc-temp-{m}",

lib_cc/style.py

@@ -11,7 +11,7 @@ EMPTY_STYLE = {"styles": {}, "deleted": {}}
 
 class StyleManager:
     def __init__(self):
-        self.STYLE_SHEET = None
+        self.STYLE_SHEET: dict = None
 
     def load_styles(self):
         if os.path.isfile(STYLE_FILE):
@@ -27,10 +27,10 @@ class StyleManager:
 
         return self.list_style()
 
-    def list_style(self):
+    def list_style(self) -> list[str]:
         return list(self.STYLE_SHEET["styles"].keys())
 
-    def get_style(self, style_name: str):
+    def get_style(self, style_name: str) -> tuple[bool | str | float]:
         style: dict = self.STYLE_SHEET["styles"].get(style_name, None)
 
         if not style:

lib_cc/xyz.py

@@ -13,6 +13,7 @@ def grid_reference():
 
 
 def xyz_support(cache: dict):
+
     def apply_field(field):
         def _(p, x, xs):
             cache.update({field: x})

scripts/cc.py

@@ -11,7 +11,7 @@ import gradio as gr
 import lib_cc
 
 
-VERSION = "v2.2.3"
+VERSION = "2.2.4"
 
 
 style_manager = StyleManager()
@@ -19,6 +19,7 @@ style_manager.load_styles()
 
 
 class VectorscopeCC(scripts.Script):
+
     def __init__(self):
         self.xyzCache = {}
         xyz_support(self.xyzCache)
@@ -30,11 +31,11 @@ class VectorscopeCC(scripts.Script):
         return scripts.AlwaysVisible
 
     def ui(self, is_img2img):
-        mode = "img" if is_img2img else "txt"
+        mode: str = "img" if is_img2img else "txt"
-        m = f'"{mode}"'
+        m: str = f'"{mode}"'
 
         with gr.Accordion(
-            f"Vectorscope CC {VERSION}", elem_id=f"vec-cc-{mode}", open=False
+            f"Vectorscope CC v{VERSION}", elem_id=f"vec-cc-{mode}", open=False
         ):
 
             with gr.Row():
@@ -151,13 +152,14 @@ class VectorscopeCC(scripts.Script):
                     label="Noise Settings",
                     value="Straight Abs.",
                 )
+
                 scaling = gr.Radio(
                     ["Flat", "Cos", "Sin", "1 - Cos", "1 - Sin"],
                     label="Scaling Settings",
                     value="Flat",
                 )
 
-            comps = (
+            comps: tuple[gr.components.Component] = (
                 latent,
                 bri,
                 con,
@@ -297,49 +299,40 @@ class VectorscopeCC(scripts.Script):
             enable = self.xyzCache["Enable"].lower().strip() == "true"
 
         if not enable:
-            if "Enable" not in self.xyzCache.keys():
+            if len(self.xyzCache) > 0:
-                if len(self.xyzCache) > 0:
+                if "Enable" not in self.xyzCache.keys():
                     print("\n[Vec.CC] x [X/Y/Z Plot] Extension is not Enabled!\n")
-
                 self.xyzCache.clear()
 
             KDiffusionSampler.vec_cc = {"enable": False}
             return p
 
         if "Random" in self.xyzCache.keys():
+            print("[X/Y/Z Plot] x [Vec.CC] Randomize is Enabled.")
             if len(self.xyzCache) > 1:
-                print(
+                print("Some parameters will not apply!")
-                    "\n[X/Y/Z Plot] x [Vec.CC] Randomize is Enabled.\nSome settings will not apply!\n"
-                )
-            else:
-                print("\n[X/Y/Z Plot] x [Vec.CC] Randomize is Enabled.\n")
 
         cc_seed = int(seeds[0]) if doRN else None
 
-        for k, v in self.xyzCache.items():
+        if "Alt" in self.xyzCache.keys():
-            match k:
+            latent = self.xyzCache["Alt"].lower().strip() == "true"
-                case "Alt":
+
-                    latent = self.xyzCache["Alt"].lower().strip() == "true"
+        if "DoHR" in self.xyzCache.keys():
-                case "Brightness":
+            doHR = self.xyzCache["DoHR"].lower().strip() == "true"
-                    bri = float(v)
+
-                case "Contrast":
+        if "Random" in self.xyzCache.keys():
-                    con = float(v)
+            cc_seed = int(self.xyzCache["Random"])
-                case "Saturation":
+
-                    sat = float(v)
+        bri = float(self.xyzCache.get("Brightness", bri))
-                case "R":
+        con = float(self.xyzCache.get("Contrast", con))
-                    r = float(v)
+        sat = float(self.xyzCache.get("Saturation", sat))
-                case "G":
+
-                    g = float(v)
+        r = float(self.xyzCache.get("R", r))
-                case "B":
+        g = float(self.xyzCache.get("G", g))
-                    b = float(v)
+        b = float(self.xyzCache.get("B", b))
-                case "DoHR":
+
-                    doHR = self.xyzCache["DoHR"].lower().strip() == "true"
+        method = str(self.xyzCache.get("Method", method))
-                case "Method":
+        scaling = str(self.xyzCache.get("Scaling", scaling))
-                    method = str(v)
-                case "Scaling":
-                    scaling = str(v)
-                case "Random":
-                    cc_seed = int(v)
 
         self.xyzCache.clear()
 
@@ -347,11 +340,7 @@ class VectorscopeCC(scripts.Script):
             KDiffusionSampler.vec_cc = {"enable": False}
             return p
 
-        steps: int = p.steps
+        steps: int = getattr(p, "firstpass_steps", None) or p.steps
-        # is img2img & do full steps
-        if not hasattr(p, "enable_hr") and not shared.opts.img2img_fix_steps:
-            if getattr(p, "denoising_strength", 1.0) < 1.0:
-                steps = int(steps * getattr(p, "denoising_strength", 1.0) + 1.0)
 
         if cc_seed:
             seed(cc_seed)
@@ -373,19 +362,24 @@ class VectorscopeCC(scripts.Script):
             print(f"B:\t\t{b}\n")
 
         if getattr(shared.opts, "cc_metadata", True):
-            p.extra_generation_params["Vec CC Enabled"] = enable
+            p.extra_generation_params.update(
-            p.extra_generation_params["Vec CC Alt"] = latent
+                {
-            p.extra_generation_params["Vec CC Brightness"] = bri
+                    "Vec CC Enabled": enable,
-            p.extra_generation_params["Vec CC Contrast"] = con
+                    "Vec CC Alt": latent,
-            p.extra_generation_params["Vec CC Saturation"] = sat
+                    "Vec CC Brightness": bri,
-            p.extra_generation_params["Vec CC R"] = r
+                    "Vec CC Contrast": con,
-            p.extra_generation_params["Vec CC G"] = g
+                    "Vec CC Saturation": sat,
-            p.extra_generation_params["Vec CC B"] = b
+                    "Vec CC R": r,
-            p.extra_generation_params["Vec CC Noise"] = method
+                    "Vec CC G": g,
-            p.extra_generation_params["Vec CC Proc HrF"] = doHR
+                    "Vec CC B": b,
-            p.extra_generation_params["Vec CC Proc Ade"] = doAD
+                    "Vec CC Noise": method,
-            p.extra_generation_params["Vec CC Scaling"] = scaling
+                    "Vec CC Proc HrF": doHR,
-            p.extra_generation_params["Vec CC Version"] = VERSION
+                    "Vec CC Proc Ade": doAD,
+                    "Vec CC Seed Randomize": doRN,
+                    "Vec CC Scaling": scaling,
+                    "Vec CC Version": VERSION,
+                }
+            )
 
         bri /= steps
         con /= steps
@@ -394,7 +388,7 @@ class VectorscopeCC(scripts.Script):
         g /= steps
         b /= steps
 
-        mode = "x" if latent else "denoised"
+        mode: str = "x" if latent else "denoised"
 
         KDiffusionSampler.vec_cc = {
             "enable": True,

scripts/cc_hdr.py

@@ -7,16 +7,15 @@ import cv2 as cv
 
 
 # https://docs.opencv.org/4.8.0/d2/df0/tutorial_py_hdr.html
-def merge_HDR(imgs: list, path: str, depth: str, fmt: str, gamma: float):
+def merge_HDR(imgs: list, path: str, depth: str, fmt: str, gamma: float) -> np.ndarray:
     import datetime
     import math
     import os
 
     output_folder = os.path.join(path, "hdr")
-    if not os.path.exists(output_folder):
+    os.makedirs(output_folder, exist_ok=True)
-        os.makedirs(output_folder)
 
-    imgs_np = [np.array(img, dtype=np.uint8) for img in imgs]
+    imgs_np = [np.asarray(img).astype(np.uint8) for img in imgs]
 
     merge = cv.createMergeMertens()
     hdr = merge.process(imgs_np)
@@ -39,8 +38,11 @@ def merge_HDR(imgs: list, path: str, depth: str, fmt: str, gamma: float):
         rgb,
     )
 
+    return ldr
+
 
 class VectorHDR(scripts.Script):
+
     def title(self):
         return "High Dynamic Range"
 
@@ -49,14 +51,14 @@ class VectorHDR(scripts.Script):
 
     def ui(self, is_img2img):
         with gr.Row():
-            count = gr.Slider(label="Brackets", minimum=3, maximum=9, step=2, value=7)
+            count = gr.Slider(label="Brackets", minimum=3, maximum=9, step=2, value=5)
             gap = gr.Slider(
-                label="Gaps", minimum=0.50, maximum=2.50, step=0.25, value=1.50
+                label="Gaps", minimum=0.50, maximum=2.50, step=0.25, value=1.25
             )
 
         with gr.Accordion(
             "Merge Options",
-            elem_id="vec-hdr-" + ("img" if is_img2img else "txt"),
+            elem_id=f'vec-hdr-{"img" if is_img2img else "txt"}',
             open=False,
         ):
             auto = gr.Checkbox(label="Automatically Merge", value=True)
@@ -85,16 +87,7 @@ class VectorHDR(scripts.Script):
         center = count // 2
 
         p.seed = get_fixed_seed(p.seed)
-        p.scripts.script("vectorscope cc").xyzCache.update(
+        p.scripts.script("vectorscope cc").xyzCache.update({"Enable": "False"})
-            {
-                "Enable": "True",
-                "Alt": "True",
-                "Brightness": 0,
-                "DoHR": "False",
-                "Method": "Ones",
-                "Scaling": "1 - Cos",
-            }
-        )
 
         baseline = process_images(p)
         pc = copy(p)
@@ -109,7 +102,14 @@ class VectorHDR(scripts.Script):
                 continue
 
             pc.scripts.script("vectorscope cc").xyzCache.update(
-                {"Brightness": brackets[it]}
+                {
+                    "Enable": "True",
+                    "Alt": "True",
+                    "Brightness": brackets[it],
+                    "DoHR": "False",
+                    "Method": "Ones",
+                    "Scaling": "1 - Cos",
+                }
             )
 
             proc = process_images(pc)
@@ -117,13 +117,12 @@ class VectorHDR(scripts.Script):
 
         if not auto:
             baseline.images = imgs
-            return baseline
-
         else:
-            merge_HDR(imgs, p.outpath_samples, depth, fmt, gamma)
+            baseline.images = [merge_HDR(imgs, p.outpath_samples, depth, fmt, gamma)]
-            return baseline
+
+        return baseline
 
 
-def brightness_brackets(count, gap):
+def brightness_brackets(count: int, gap: int) -> list[int]:
     half = count // 2
     return [gap * (i - half) for i in range(count)]