Initial commit

.gitattributes

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+# Auto detect text files and perform LF normalization
+* text=auto

.gitignore

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+# Byte-compiled / optimized / DLL files
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+*.py[cod]
+*$py.class
+
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+#.idea/

LICENSE

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+MIT License
+
+Copyright (c) 2025 Budi Hartono
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+# comfyui-aspect-ratio-presets
+Custom ComfyUI nodes for generating empty latent tensors with preset and axis-based aspect ratios.

aspect_ratio_nodes.py

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+# aspect_ratio_nodes.py
+
+import numpy as np
+import modules.scripts as scripts
+from modules import shared
+from modules.ui import create_node, create_node_callbacks
+from presets import PRESETS
+
+def _validate_dim(v):
+    if v <= 0:
+        raise ValueError("Dimension must be > 0")
+    if v % 8 != 0:
+        raise ValueError("Dimension must be divisible by 8")
+
+class EmptyLatentAspectPreset(scripts.Script):
+    title = "Empty Latent (Aspect Ratio Preset)"
+    ui_category = "ComfyUI Aspect Ratio Preset"
+
+    def ui(self):
+        self.resolution = self.ui.dropdown(
+            label="Resolution Preset",
+            choices=[f"{m} {w}×{h} ({lbl})" for m, lbl, w, h in PRESETS],
+            default=0,
+            tooltip="Choose a predefined resolution + aspect ratio"
+        )
+        self.batch_size = self.ui.int_field(
+            label="Batch Size",
+            default=1,
+            minimum=1,
+            tooltip="How many blank latents to produce"
+        )
+
+    def run(self, p):
+        model, lbl, W, H = PRESETS[self.resolution]
+        _validate_dim(W); _validate_dim(H)
+        B = self.batch_size
+        C = shared.sd_model.cond_stage_model.latent_channels  # usually 4
+        shape = (B, C, H // 8, W // 8)
+        return np.zeros(shape, dtype=np.float32)
+
+
+class EmptyLatentAspectByAxis(scripts.Script):
+    title = "Empty Latent (Aspect Ratio by Axis)"
+    ui_category = "ComfyUI Aspect Ratio Preset"
+
+    ASPECT_CHOICES = [
+        ("1:1 Square", (1,1)),
+        ("3:2 Landscape", (3,2)),
+        ("2:3 Portrait", (2,3)),
+        ("4:3 Landscape", (4,3)),
+        ("3:4 Portrait", (3,4)),
+        ("16:9 Landscape", (16,9)),
+        ("9:16 Portrait", (9,16)),
+        ("5:4 Landscape", (5,4)),
+        ("4:5 Portrait", (4,5)),
+        ("21:9 Widescreen", (21,9)),
+        ("9:21 Portrait", (9,21)),
+        ("7:5 Landscape", (7,5)),
+        ("5:7 Portrait", (5,7)),
+    ]
+
+    def ui(self):
+        self.primary = self.ui.int_field(
+            label="Primary Dimension",
+            default=512,
+            tooltip="Your value for the chosen Reference Axis"
+        )
+        self.axis = self.ui.dropdown(
+            label="Reference Axis",
+            choices=["Width","Height"],
+            default="Width",
+            tooltip="Which side does the Primary Dimension refer to?"
+        )
+        self.aspect = self.ui.dropdown(
+            label="Aspect Ratio",
+            choices=[lbl for lbl,_ in self.ASPECT_CHOICES],
+            default=0,
+            tooltip="Select X:Y ratio and orientation"
+        )
+        self.batch_size = self.ui.int_field(
+            label="Batch Size",
+            default=1,
+            minimum=1,
+            tooltip="How many blank latents to produce"
+        )
+
+    def run(self, p):
+        val = self.primary
+        _validate_dim(val)
+        w_ratio, h_ratio = self.ASPECT_CHOICES[self.aspect][1]
+
+        if self.axis == "Width":
+            W = val
+            H = round(val * (h_ratio / w_ratio))
+        else:
+            H = val
+            W = round(val * (w_ratio / h_ratio))
+
+        _validate_dim(W); _validate_dim(H)
+
+        B = self.batch_size
+        C = shared.sd_model.cond_stage_model.latent_channels
+        shape = (B, C, H // 8, W // 8)
+        return np.zeros(shape, dtype=np.float32)

presets.py

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+# presets.py
+
+PRESETS = [
+    # model, label, w, h
+    ("SD 1.5",  "1:1 Square",    512, 512),
+    ("SD 1.5",  "3:2 Landscape", 768, 512),
+    ("SD 1.5",  "4:3 Landscape", 768, 576),
+    ("SD 1.5",  "16:9 Landscape",912, 512),
+    ("SD 1.5",  "2:3 Portrait",  512, 768),
+    ("SD 1.5",  "3:4 Portrait",  576, 768),
+    ("SD 1.5",  "9:16 Portrait", 512, 912),
+    ("SDXL",    "1:1 Square",    1024,1024),
+    ("SDXL",    "3:2 Landscape", 1152,768),
+    ("SDXL",    "4:3 Landscape", 1152,864),
+    ("SDXL",    "16:9 Landscape",1360,768),
+    ("SDXL",    "2:3 Portrait",  768,1152),
+    ("SDXL",    "3:4 Portrait",  864,1152),
+    ("SDXL",    "9:16 Portrait", 768,1360),
+    ("Flux/HiD","3:2 Landscape", 1216,832),
+    ("Flux/HiD","2:3 Portrait",  832,1216),
+    ("Flux/HiD","1:1 Square",    1408,1408),
+    ("Flux/HiD","4:3 Landscape", 1664,1216),
+    ("Flux/HiD","16:9 Landscape",1920,1088),
+    ("Flux/HiD","9:21 Portrait", 960,2176),
+    ("HiDream", "1:1 Square",    1280,1280),
+    ("HiDream", "1:1 Square",    1536,1536),
+]

requirements.txt

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+numpy