Lut fixes

New Prompts
Python 3.12.8 Test

LUT/0-none.cube

@@ -0,0 +1,517 @@
+# Charles Fettinger 3D LUT from 8x8 PNG
+TITLE "Converted 8x8x8 LUT"
+LUT_3D_SIZE 8
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+0.823529 0.952941 1.000000
+0.952941 0.952941 1.000000

LUT/gist_heat.cube

@@ -0,0 +1,258 @@
+TITLE "Colormap gist_heat"
+LUT_1D_SIZE 256
+0.0000000 0.0000000 0.0000000
+0.0058824 0.0000000 0.0000000
+0.0117647 0.0000000 0.0000000
+0.0176471 0.0000000 0.0000000
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README.md

@@ -4,7 +4,7 @@ emoji: 🌖
 colorFrom: yellow
 colorTo: purple
 sdk: gradio
-python_version: 3.10.13
+python_version: 3.12.8
 sdk_version: 5.22.0
 app_file: app.py
 pinned: false

app.py

@@ -702,40 +702,8 @@ with gr.Blocks(css_paths="style_20250314.css", title=title, theme='Surn/beeuty',
                 format="PNG"
             )
 
-        with gr.Column(scale=0):
-            with gr.Accordion("Sketch Pad", open = False):
-                with gr.Row():
-                    sketch_image = gr.Sketchpad(
-                        label="Sketch Image",
-                        type="filepath",
-                        #invert_colors=True,
-                        #sources=['upload','canvas'],
-                        #tool=['editor','select','color-sketch'],
-                        placeholder="Draw a sketch or upload an image. Currently broken in gradio 5.17.1",
-                        interactive=True,
-                        elem_classes="centered solid imgcontainer",
-                        key="imgSketch",
-                        image_mode="RGBA",
-                        format="PNG",
-                        brush=gr.Brush()
-                    )
-                with gr.Row():
-                    with gr.Column(scale=1):
-                        sketch_replace_input_image_button = gr.Button(
-                            "Replace Input Image with sketch",
-                            elem_id="sketch_replace_input_image_button",
-                            elem_classes="solid"
-                        )
-                    with gr.Column(scale=2):
-                        alpha_composite_slider = gr.Slider(0,100,50,0.5, label="Alpha Composite Sketch to Input Image", elem_id="alpha_composite_slider")
-                    
+        with gr.Column(scale=1):
             with gr.Accordion("Image Filters", open = False):
-                with gr.Row():
-                    with gr.Column():
-                        composite_color = gr.ColorPicker(label="Color", value="#ede9ac44")
-                        composite_opacity = gr.Slider(label="Opacity %", minimum=0, maximum=100, value=50, interactive=True)
-                with gr.Row():
-                    composite_button = gr.Button("Composite", elem_classes="solid")
                 with gr.Row():
                     with gr.Column():
                         lut_filename = gr.Textbox(
@@ -748,37 +716,69 @@ with gr.Blocks(css_paths="style_20250314.css", title=title, theme='Surn/beeuty',
                             file_count="single",
                             file_types=[".cube"],
                             type="filepath",
-                            label="LUT cube File")
+                            label="LUT cube File",
+                            height=120)
+                with gr.Row():
+                    lut_intensity = gr.Slider(label="Filter Intensity", minimum=-200, maximum=200, value=100, info="0 none, negative inverts the filter", interactive=True)
+                    apply_lut_button = gr.Button("Apply Filter (LUT)", elem_classes="solid", elem_id="apply_lut_button")
                 with gr.Row():
                     lut_example_image = gr.Image(type="pil", label="Filter (LUT) Example Image", value=default_lut_example_img)
                 with gr.Row():
                     with gr.Column():
                         gr.Markdown("""
                         ### Included Filters (LUTs)
-                        There are several included Filters:
-
-                        Try them on the example image before applying to your Input Image.
+                        Try on Example Image then APPLY FILTER to Input Image.
+                        *-none.cube files are placebo controls
                         """, elem_id="lut_markdown")
                     with gr.Column():
                         gr.Examples(elem_id="lut_examples",
                             examples=[[f] for f in lut_files],
                             inputs=[lut_filename],
                             outputs=[lut_filename],
-                            label="Select a Filter (LUT) file. Populate the LUT File Name field",
-                            examples_per_page=15
+                            label="Select a Filter (LUT) file to populate the LUT File Name field",
+                            examples_per_page = 25,
                         )
                     
-                with gr.Row():
-                    apply_lut_button = gr.Button("Apply Filter (LUT)", elem_classes="solid", elem_id="apply_lut_button")
-                    
                 lut_file.change(get_filename, inputs=[lut_file], outputs=[lut_filename])
-                lut_filename.change(show_lut, inputs=[lut_filename, input_image], outputs=[lut_example_image])
+                lut_filename.change(show_lut, inputs=[lut_filename, input_image, lut_intensity], outputs=[lut_example_image], scroll_to_output=True)
+                lut_intensity.change(show_lut, inputs=[lut_filename, input_image, lut_intensity], outputs=[lut_example_image])
                 apply_lut_button.click(
-                    lambda lut_filename, input_image: gr.Warning("Please upload an Input Image to get started.") if input_image is None else apply_lut_to_image_path(lut_filename, input_image)[0], 
-                    inputs=[lut_filename, input_image], 
+                    lambda lut_filename, input_image, lut_intensity: gr.Warning("Please upload an Input Image to get started.") if input_image is None else apply_lut_to_image_path(lut_filename, input_image, lut_intensity)[1], 
+                    inputs=[lut_filename, input_image, lut_intensity], 
                     outputs=[input_image], 
                     scroll_to_output=True
                 )
+            with gr.Accordion("Color Composite", open = False):
+                with gr.Row():
+                    composite_color = gr.ColorPicker(label="Color", value="#ede9ac44")
+                    composite_opacity = gr.Slider(label="Opacity %", minimum=0, maximum=100, value=50, interactive=True)
+                with gr.Row():
+                    composite_button = gr.Button("Composite", elem_classes="solid")
+            with gr.Accordion("Sketch Pad", open = False):
+                with gr.Row():
+                    sketch_image = gr.Sketchpad(
+                        label="Sketch Image",
+                        type="filepath",
+                        #invert_colors=True,
+                        #sources=['upload','canvas'],
+                        #tool=['editor','select','color-sketch'],
+                        placeholder="Draw a sketch or upload an image. Currently broken in gradio 5.17.1",
+                        interactive=True,
+                        elem_classes="centered solid imgcontainer",
+                        key="imgSketch",
+                        image_mode="RGBA",
+                        format="PNG",
+                        brush=gr.Brush()
+                    )
+                with gr.Row():
+                    with gr.Column(scale=1):
+                        sketch_replace_input_image_button = gr.Button(
+                            "Replace Input Image with sketch",
+                            elem_id="sketch_replace_input_image_button",
+                            elem_classes="solid"
+                        )
+                    with gr.Column(scale=2):
+                        alpha_composite_slider = gr.Slider(0,100,50,0.5, label="Alpha Composite Sketch to Input Image", elem_id="alpha_composite_slider")
     with gr.Row():
         with gr.Accordion("Generative AI", open = True ):
             with gr.Column():
@@ -817,7 +817,7 @@ with gr.Blocks(css_paths="style_20250314.css", title=title, theme='Surn/beeuty',
             with gr.Row():
                 with gr.Column(scale=1):
                     generate_button = gr.Button("Generate From Map Options, Input Image and LoRa Style", variant="primary", elem_id="gen_btn")
-                    with gr.Accordion("LoRA Styles*", open=False):
+                    with gr.Accordion("Image Styles*", open=False):
                         selected_info = gr.Markdown("")
                         lora_gallery = gr.Gallery(
                             [(item["image"], item["title"]) for item in loras],

modules/constants.py

@@ -65,6 +65,7 @@ TARGET_SIZE = (2688,1536)
 #os.makedirs(TMP_DIR, exist_ok=True)
 
 PROMPTS = {
+    "Mecha Wasteland Arena":"Top-down view of a Mecha battlefield map. post-industrial wasteland. Crumbling structures, volcanic ridges, scrapyards, and ash plains. Features elevated overwatch positions and tight brawling areas. Colors: red, gray, orange, white, brown. Partial edge hexes are black.",
     "BorderBlack": "Top-down view, from above. of a hexagon-based alien map with black borders. Features rivers, mountains, volcanoes, and snow at top and bottom. Colors: light blue, green, tan, brown. No reflections or shadows. Partial hexes on edges are black.",
     "Earth": "Top-down view of a world map with rivers, mountains, volcanoes, and snow at top and bottom. Colors: light blue, green, tan, brown. No reflections or shadows. Partial edge hexes are black. from above.",
     "Beeuty": "Top-down view of a table map with honeycomb_shapes, lakes, dense forests, magical flora, and hex_grids. Map for tabletop gaming with clarity and strategic elements. Colors: yellow, green, purple, brown. Partial hexes on edges are black. Viewed from above.",
@@ -73,10 +74,13 @@ PROMPTS = {
     "Alien World": "Top-down view of an alien world map built from hexagon pieces. Includes rivers, mountains, volcanoes, and snowy areas. Colors: light blue, green, tan, brown. Partial edge hexes are black. Overhead view.",
     "Mystic Forest": "Top-down view of a mystic forest map with lakes, dense forests, magical flora, and hex grids. Designed for clarity in tabletop gaming. Colors: light blue, green, purple, brown. Partial hexes on edges are black.",
     "Medieval Battlefield": "Top-down view of a medieval battlefield map featuring lakes, forests, and magic fauna. Emphasizes clarity and strategy for tabletop games. Colors: teal, dark green, violet, brown. Partial edge hexes are black. Viewed from above.",
+    "Dungeon Interior":"Top-down view of a dungeon interior map for tabletop gaming, Features stone walls, corridors, rooms with doors, traps, and treasure chests. Emphasizes clarity for strategic gameplay. Colors: gray, brown, dark blue. Partial edge hexes are black. Viewed from above",
+    "Desert Wasteland":"Top-down view of a desert wasteland map for tabletop gaming, Includes sand dunes, rocky canyons, oases with water and palm trees, and ancient ruins. Designed for clarity and strategy. Colors: yellow, tan, brown, blue, green. Partial edge hexes are black. Viewed from above.",
     "Prompt": None  # Indicates that the prompt should be taken from prompt_textbox
 }
 
 NEGATIVE_PROMPTS = {
+    "Mecha Wasteland Arena": "humans, old_buildings, water, bright colors, text, logos, shadows, Earth geography, isometric",
     "BorderBlack": "humans, modern_buildings, vehicles, text, logos, reflections, shadows, realistic map of the Earth, isometric",
     "Earth": "humans, modern_buildings, vehicles, text, logos, reflections, shadows, missing map of the Earth, isometric",
     "Beeuty": "humans, modern_buildings, vehicles, text, logos, reflections, shadows, map of the Earth, isometric",
@@ -85,6 +89,8 @@ NEGATIVE_PROMPTS = {
     "Alien World": "Earth, humans, modern_buildings, vehicles, text, logos, reflections, shadows, realistic map of the Earth, isometric",
     "Mystic Forest": "humans, modern_buildings, vehicles, text, logos, reflections, shadows, realistic map of the Earth, isometric",
     "Medieval Battlefield": "humans, modern_buildings, vehicles, text, logos, reflections, shadows, realistic map of the Earth, isometric",
+    "Dungeon Interior":"humans, modern_buildings, vehicles, text, logos, reflections, shadows, outdoor elements, realistic map of the Earth, isometric",
+    "Desert Wasteland":"humans, modern_buildings, vehicles, text, logos, reflections, shadows, lush forests, large bodies of water, snow, realistic map of the Earth, isometric",
     "Prompt": None  # Indicates that the negative prompt should be taken from negative_prompt_textbox
 }
 

modules/image_utils.py

@@ -609,7 +609,25 @@ def read_3d_lut(path_lut: Union[str, os.PathLike], num_channels: int = 3) -> Ima
     lut_table = [row2val(row) for row in lut_raw if is_3dlut_row(row.split(" "))]
     return ImageFilter.Color3DLUT(size, lut_table, num_channels)
 
-def apply_1d_lut(image, lut_file):
+def apply_1d_lut(image, lut_file, intensity: int = 100, lut_scale: float = 1.0, lut_offset: float = 0.0):
+    """
+    Apply a 1D LUT to an image with intensity, scale, and offset control.
+    
+    Args:
+        image: PIL Image object.
+        lut_file: Path to the 1D LUT file.
+        intensity: Integer from -200 to 200 controlling LUT strength (default 100).
+        lut_scale: Float to scale LUT colors (default 1.0).
+        lut_offset: Float to offset LUT colors (default 0.0).
+    
+    Returns:
+        PIL Image object with the adjusted LUT applied.
+    """
+    import numpy as np
+    
+    # Compute blending factor
+    alpha = intensity / 100.0  # Ranges from -2.0 to 2.0
+    
     # Read the 1D LUT
     with open(lut_file) as f:
         lines = f.read().splitlines()
@@ -619,20 +637,58 @@ def apply_1d_lut(image, lut_file):
             values = [float(v) for v in line.split()]
             table.append(tuple(values))
     
+    # Adjust LUT table with scale and offset
+    adjusted_table = [
+        tuple(np.clip(val * lut_scale + lut_offset, 0, 1) for val in color)
+        for color in table
+    ]
+    
+    # If intensity is negative, use inverted LUT
+    if alpha < 0:
+        adjusted_table = [(1 - r, 1 - g, 1 - b) for r, g, b in adjusted_table]
+        alpha = -alpha  # Use positive alpha for blending
+    
     # Convert image to grayscale
     if image.mode != 'L':
         image = image.convert('L')
     img_array = np.array(image) / 255.0  # Normalize to [0, 1]
     
     # Map grayscale values to colors
-    lut_size = len(table)
+    lut_size = len(adjusted_table)
     indices = (img_array * (lut_size - 1)).astype(int)
-    colors = np.array(table)[indices]
+    colors = np.array(adjusted_table)[indices]  # LUT-mapped colors, shape (H, W, 3)
+    
+    # Create original colors (grayscale replicated across RGB)
+    original_colors = np.repeat(img_array[:, :, np.newaxis], 3, axis=2)  # Shape (H, W, 3)
+    
+    # Blend original and LUT-mapped colors
+    blended_colors = original_colors * (1 - alpha) + colors * alpha
+    blended_colors = np.clip(blended_colors, 0, 1)  # Ensure values stay in [0, 1]
     
     # Create RGB image
-    rgb_image = Image.fromarray((colors * 255).astype(np.uint8), mode='RGB')
+    rgb_image = Image.fromarray((blended_colors * 255).astype(np.uint8), mode='RGB')
     return rgb_image
 
+def invert_lut(original_lut: ImageFilter.Color3DLUT) -> ImageFilter.Color3DLUT:
+    """
+    Create an inverted LUT by reversing the order of entries to simulate a 180-degree rotation.
+
+    Args:
+        original_lut: The original Color3DLUT object.
+
+    Returns:
+        A new Color3DLUT object with inverted entries.
+    """
+    # Extract the table and size from the original LUT
+    size = original_lut.size[0]  # Assuming cubic LUT
+    table = original_lut.table
+    
+    # Reverse the table to simulate a 180-degree rotation
+    inverted_table = table[::-1]
+    
+    # Create and return the inverted LUT with the same number of channels
+    return ImageFilter.Color3DLUT(size, inverted_table, original_lut.channels)
+
 def apply_3d_lut(img: Image, lut_path: str = "", lut: ImageFilter.Color3DLUT = None) -> Image:
     """
     Apply a LUT to an image and return a PIL Image with the LUT applied.
@@ -656,39 +712,143 @@ def apply_3d_lut(img: Image, lut_path: str = "", lut: ImageFilter.Color3DLUT = N
         lut = read_3d_lut(lut_path)
     return img.filter(lut)
 
-def apply_lut(image, lut_filename: str) -> Image:
+def apply_lut_simple(image, lut_filename: str, intensity: int = 100) -> Image:
     """
-    Apply a LUT to an image and return the result.
+    Apply a LUT to an image with intensity control.
+    
     Args:
-        image (str or PIL.Image.Image): The image to apply the LUT to.
-        lut_filename (str): The path to the LUT file.
+        image: PIL Image object or path to image file.
+        lut_filename: Path to the LUT file.
+        intensity: Integer from -200 to 200 controlling LUT strength (default 100).
+    
     Returns:
-        PIL.Image.Image: The image with the LUT applied.
+        PIL Image object with the adjusted LUT applied.
     """
+    import numpy as np
+    
+    # Handle image input as string
     if isinstance(image, str):
         image = open_image(image)
+    
     if lut_filename is not None:
-        if (get_lut_type(lut_filename) == "3D"):
-            lut = read_3d_lut(lut_filename)
-            image =  apply_3d_lut(image, lut=lut)
+        lut_type = get_lut_type(lut_filename)
+        if lut_type == "3D":
+            # Read the original 3D LUT
+            original_lut = read_3d_lut(lut_filename)
+            
+            # Apply the original LUT to the image
+            lutted_image = image.filter(original_lut)
+            
+            # Compute blending factor
+            alpha = intensity / 100.0  # Ranges from -2.0 to 2.0
+            
+            # Handle special cases
+            if alpha == 0:
+                return image
+            elif alpha == 1:
+                return lutted_image
+            else:
+                # Convert images to NumPy arrays for blending
+                img_array = np.array(image).astype(float) / 255.0
+                lutted_array = np.array(lutted_image).astype(float) / 255.0
+                blended_array = img_array * (1 - alpha) + lutted_array * alpha
+                blended_array = np.clip(blended_array, 0, 1)
+                blended_image = Image.fromarray((blended_array * 255).astype(np.uint8))
+                return blended_image
         else:
-            image = apply_1d_lut(image, lut_filename)
+            # Apply 1D LUT with intensity (already correct)
+            image = apply_1d_lut(image, lut_filename, intensity)
+    
     return image
 
-def show_lut(lut_filename: str, lut_example_image: Image = default_lut_example_img) -> Image:
+def apply_lut(image, lut_filename: str, intensity: int = 100, lut_scale: float = 1.0, lut_offset: float = 0.0) -> Image:
+    """
+    Apply a LUT to an image with intensity, scale, and offset adjustments.
+
+    Args:
+        image: PIL Image object or path to image file.
+        lut_filename: Path to the LUT file (.cube for 3D LUT or text file for 1D LUT).
+        intensity: Integer from -200 to 200 controlling LUT strength (default 100).
+        lut_scale: Float to scale LUT colors (default 1.0).
+        lut_offset: Float to offset LUT colors (default 0.0).
+
+    Returns:
+        PIL Image object with the adjusted LUT applied.
+    """
+
+    
+    # Handle image input as string
+    if isinstance(image, str):
+        image = Image.open(image).convert('RGB')
+
+    if lut_filename is None:
+        return image
+
+    lut_type = get_lut_type(lut_filename)
+
+    if lut_type == "3D":
+        # Read the original 3D LUT
+        # Read the original 3D LUT using the external function
+        original_lut = read_3d_lut(lut_filename)
+
+        # Create the inverted LUT
+        inverted_lut = invert_lut(original_lut)
+
+        # Define a function to adjust LUT entries with scale and offset
+        def adjust_entry(r, g, b):
+            r = np.clip(r * lut_scale + lut_offset, 0, 1)
+            g = np.clip(g * lut_scale + lut_offset, 0, 1)
+            b = np.clip(b * lut_scale + lut_offset, 0, 1)
+            return (r, g, b)
+
+        # Apply scale and offset adjustments to both LUTs
+        adjusted_original_lut = original_lut.transform(adjust_entry)
+        adjusted_inverted_lut = inverted_lut.transform(adjust_entry)
+
+        # Compute blending factor from intensity
+        alpha = intensity / 100.0  # Ranges from -2.0 to 2.0
+
+        # Select the appropriate LUT based on intensity
+        if alpha >= 0:
+            lut_to_use = adjusted_original_lut
+        else:
+            lut_to_use = adjusted_inverted_lut
+            alpha = -alpha  # Use positive alpha for blending with inverted LUT
+
+        # Apply the selected LUT to the image
+        lutted_image = image.filter(lut_to_use)
+
+        # Convert images to NumPy arrays for blending
+        original_array = np.array(image, dtype=np.float32) / 255.0
+        lutted_array = np.array(lutted_image, dtype=np.float32) / 255.0
+
+        # Blend the original and LUT-applied images
+        blended_array = original_array * (1 - alpha) + lutted_array * alpha
+        blended_array = np.clip(blended_array, 0, 1)
+
+        # Convert back to PIL Image
+        final_image = Image.fromarray((blended_array * 255).astype(np.uint8))
+        return final_image
+
+    else:  # 1D LUT
+        # Delegate to the modified apply_1d_lut function
+        return apply_1d_lut(image, lut_filename, intensity, lut_scale, lut_offset)
+
+
+def show_lut(lut_filename: str, lut_example_image: Image = default_lut_example_img, intensity: int = 100) -> Image:
     if lut_example_image is None:
         lut_example_image = default_lut_example_img
 
     if lut_filename is not None:
         try:
-            lut_example_image = apply_lut(lut_example_image, lut_filename)
+            lut_example_image = apply_lut(lut_example_image, lut_filename, intensity)
         except Exception as e:
             print(f"BAD LUT: Error applying LUT {str(e)}.")
     else:
         lut_example_image = open_image(default_lut_example_img)
     return lut_example_image
 
-def apply_1d_lut(image, lut_file):
+def apply_1d_lut_simple(image, lut_file):
     # Read the 1D LUT
     with open(lut_file) as f:
         lines = f.read().splitlines()
@@ -712,7 +872,7 @@ def apply_1d_lut(image, lut_file):
     rgb_image = Image.fromarray((colors * 255).astype(np.uint8), mode='RGB')
     return rgb_image
 
-def apply_lut_to_image_path(lut_filename: str, image_path: str) -> tuple[Image, str]:
+def apply_lut_to_image_path(lut_filename: str, image_path: str, intensity: int = 100 ) -> tuple[Image, str]:
     """
     Apply a LUT to an image and return the result.
     Supports ICO files by converting them to PNG with RGBA channels.
@@ -762,7 +922,7 @@ def apply_lut_to_image_path(lut_filename: str, image_path: str) -> tuple[Image,
     # Apply the LUT to the image
     if (lut_filename is not None and img is not None):
         try:
-            img_lut = apply_lut(img, lut_filename)
+            img_lut = apply_lut(img, lut_filename, intensity)
         except Exception as e:
             print(f"BAD LUT: Error applying LUT {str(e)}.")
         if img_lut is not None:
@@ -774,9 +934,6 @@ def apply_lut_to_image_path(lut_filename: str, image_path: str) -> tuple[Image,
     print(f"Image with LUT saved as {new_image_path}")
     return img, gr.update(value=str(new_image_path))
 
-from PIL import Image
-import numpy as np
-
 def png_to_cube(input_png_path, output_cube_path, lut_size=17):
     # Example usage
     # png_to_cube(input_file, output_file, lut_size=17)
@@ -793,11 +950,11 @@ def png_to_cube(input_png_path, output_cube_path, lut_size=17):
     # Open the output .cube file
     with open(output_cube_path, "w") as f:
         # Write .cube header
-        f.write('# Generated by PNG to LUT converter\n')
+        f.write('# Charles Fettinger by PNG to LUT converter\n')
         f.write('TITLE "Converted LUT"\n')
         f.write(f'LUT_3D_SIZE {lut_size}\n')
         f.write('DOMAIN_MIN 0.0 0.0 0.0\n')
-        f.write('DOMAIN_MAX 1.0 1.0 1.0\n')        
+        f.write('DOMAIN_MAX 1.0 1.0 1.0\n')
         # Iterate over the 3D LUT grid (R, G, B)
         for b in range(lut_size):  # Blue channel
             for g in range(lut_size):  # Green channel
@@ -807,7 +964,7 @@ def png_to_cube(input_png_path, output_cube_path, lut_size=17):
                     # - X-axis (horizontal) = Red
                     # - Y-axis (vertical) = Green + Blue slices
                     x = r * step + step // 2  # Center of each Red step
-                    y = (g + b * lut_size) * step + step // 2  # Green + Blue offset                    
+                    y = (g + b * lut_size) * step + step // 2  # Green + Blue offset
                     # Ensure coordinates stay within bounds
                     x = min(x, 511)
                     y = min(y, 511)                    
@@ -833,7 +990,7 @@ def png_8x8_to_3d_cube(input_png_path, output_cube_path, lut_size=8):
     # Open the output .cube file
     with open(output_cube_path, "w") as f:
         # Write .cube header for 3D LUT
-        f.write('# Generated 3D LUT from 8x8 PNG\n')
+        f.write('# Charles Fettinger 3D LUT from 8x8 PNG\n')
         f.write('TITLE "Converted 8x8x8 LUT"\n')
         f.write(f'LUT_3D_SIZE {lut_size}\n')
         f.write('DOMAIN_MIN 0.0 0.0 0.0\n')
@@ -860,6 +1017,40 @@ def png_8x8_to_3d_cube(input_png_path, output_cube_path, lut_size=8):
                     f.write(f"{rgb[0]:.6f} {rgb[1]:.6f} {rgb[2]:.6f}\n")
     print(f"3D LUT conversion complete. Saved to {output_cube_path}")
 
+def png_8x8_to_3d_cube_inverted(input_png_path, output_cube_path, lut_size=8):
+    # Open the PNG file
+    img = Image.open(input_png_path)
+    if img.size != (512, 512):
+        raise ValueError("Input PNG must be 512x512 pixels.")
+    # Convert to RGB and normalize to 0-1 range
+    pixels = np.array(img.convert("RGB")) / 255.0
+    # Grid parameters
+    grid_size = 8
+    box_size = 512 // grid_size  # 64 pixels per box
+    step = box_size // lut_size  # 8 pixels per step
+    # Write the .cube file
+    with open(output_cube_path, "w") as f:
+        f.write('# Charles Fettinger 3D LUT from 8x8 PNG (inverted)\n')
+        f.write('TITLE "Converted 8x8x8 LUT (inverted)"\n')
+        f.write(f'LUT_3D_SIZE {lut_size}\n')
+        f.write('DOMAIN_MIN 0.0 0.0 0.0\n')
+        f.write('DOMAIN_MAX 1.0 1.0 1.0\n')
+        for b in range(lut_size):
+            for g in range(lut_size):
+                for r in range(lut_size):
+                    box_row = b
+                    box_col = g
+                    box_x = box_col * box_size
+                    box_y = box_row * box_size
+                    x = box_x + r * step + step // 2
+                    y = box_y + g * step + step // 2
+                    # Sample from the rotated position
+                    x_rev = 511 - x
+                    y_rev = 511 - y
+                    rgb = pixels[y_rev, x_rev]
+                    f.write(f"{rgb[0]:.6f} {rgb[1]:.6f} {rgb[2]:.6f}\n")
+    print(f"Inverted 3D LUT conversion complete. Saved to {output_cube_path}")
+
 ############################################# RGBA ###########################################################
 def convert_rgb_to_rgba_safe(image: Image) -> Image:
     """

requirements.txt

@@ -4,7 +4,7 @@ git+https://github.com/huggingface/accelerate.git
 safetensors
 sentencepiece
 git+https://github.com/huggingface/peft.git
-Pillow>=11.0.0
+Pillow>=11.1.0
 numpy
 tiktoken
 pycairo

style_20250314.css

@@ -20,7 +20,7 @@
     background-color: rgba(242, 218, 163, 0.62);
 }
 
-.dark .gradio-container.gradio-container-5-21.0 .contain .intro {
+.dark .gradio-container.gradio-container-5-22-0 .contain .intro {
     background-color: rgba(41, 18, 5, 0.38) !important;
 }