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5.3 KiB
Python

import numpy as np
import torch
from PIL import Image, ImageDraw, ImageFont
def pil2tensor(image):
"""Convert PIL image to tensor in the correct format"""
return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
class SFQwenResolution:
"""
A node for selecting Qwen model resolutions with visual preview.
Class methods
-------------
INPUT_TYPES (dict):
Defines the resolution selection input.
Attributes
----------
RETURN_TYPES (`tuple`):
Returns width (INT), height (INT), resolution string (STRING), and preview image (IMAGE).
RETURN_NAMES (`tuple`):
Names for the outputs: width, height, resolution, preview.
FUNCTION (`str`):
Entry-point method name: "get_dimensions".
OUTPUT_NODE (`bool`):
True - this node outputs a preview image.
CATEGORY (`str`):
UI category: "ControlAltAI Nodes/Qwen".
get_dimensions(resolution) -> tuple:
Returns the width, height, resolution string, and preview image for the selected resolution.
"""
@classmethod
def INPUT_TYPES(cls):
"""
Return a dictionary which contains config for all input fields.
Returns: `dict`:
- Key "required": Contains required input fields config
- Value "resolution": A list selection of available resolutions
"""
return {
"required": {
"resolution": (
[
"1:1 (Square)",
"16:9 (Widescreen Landscape)",
"9:16 (Widescreen Portrait)",
"4:3 (Standard Landscape)",
"3:4 (Standard Portrait)",
"3:2 (Classic Landscape)",
"2:3 (Classic Portrait)",
],
{"default": "1:1 (Square)"},
),
}
}
RETURN_TYPES = ("INT", "INT", "STRING", "IMAGE")
RETURN_NAMES = ("width", "height", "resolution", "preview")
FUNCTION = "get_dimensions"
CATEGORY = "Stillfront/Utils"
OUTPUT_NODE = True
def create_preview_image(self, width, height, resolution):
# 1024x1024 preview size
preview_size = (1024, 1024)
image = Image.new("RGB", preview_size, (0, 0, 0)) # Black background
draw = ImageDraw.Draw(image)
# Draw grid with grey lines
grid_color = "#333333" # Dark grey for grid
grid_spacing = 50 # Adjusted grid spacing
for x in range(0, preview_size[0], grid_spacing):
draw.line([(x, 0), (x, preview_size[1])], fill=grid_color)
for y in range(0, preview_size[1], grid_spacing):
draw.line([(0, y), (preview_size[0], y)], fill=grid_color)
# Calculate preview box dimensions
preview_width = 800 # Increased size
preview_height = int(preview_width * (height / width))
# Adjust if height is too tall
if preview_height > 800: # Adjusted for larger preview
preview_height = 800
preview_width = int(preview_height * (width / height))
# Calculate center position
x_offset = (preview_size[0] - preview_width) // 2
y_offset = (preview_size[1] - preview_height) // 2
# Draw the aspect ratio box with thicker outline
draw.rectangle(
[
(x_offset, y_offset),
(x_offset + preview_width, y_offset + preview_height),
],
outline="red",
width=4, # Thicker outline
)
# Add text with larger font sizes
try:
# Draw text (centered)
text_y = y_offset + preview_height // 2
# Resolution text in red
draw.text(
(preview_size[0] // 2, text_y),
f"{width}x{height}",
fill="red",
anchor="mm",
font=ImageFont.truetype("arial.ttf", 48),
)
except:
# Fallback if font loading fails
draw.text(
(preview_size[0] // 2, text_y),
f"{width}x{height}",
fill="red",
anchor="mm",
)
# Convert to tensor using the helper function
return pil2tensor(image)
def get_dimensions(self, resolution):
# Map from aspect ratio to actual dimensions
resolution_map = {
"1:1 (Square)": (1328, 1328),
"16:9 (Widescreen Landscape)": (1664, 928),
"9:16 (Widescreen Portrait)": (928, 1664),
"4:3 (Standard Landscape)": (1472, 1104),
"3:4 (Standard Portrait)": (1104, 1472),
"3:2 (Classic Landscape)": (1584, 1056),
"2:3 (Classic Portrait)": (1056, 1584),
}
# Get dimensions from the map
width, height = resolution_map[resolution]
# Resolution as string
resolution_str = f"{width} x {height}"
# Generate preview image
preview = self.create_preview_image(width, height, resolution_str)
return width, height, resolution_str, preview
def gcd(a, b):
"""Calculate the Greatest Common Divisor of a and b."""
while b:
a, b = b, a % b
return a
NODE_CLASS_MAPPINGS = {
"SFQwenResolution": SFQwenResolution,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"SFQwenResolution": "SF Qwen Resolution",
}