Claude
7e60424416
Features: - Actual image resizing using torch bilinear interpolation - Optional cropping to preserve aspect ratio when rounding causes deviations - Configurable crop position (center, top, bottom, left, right) - Resized image now output first, followed by original passthrough - Input validation with detailed error messages - Comprehensive tooltips on all inputs and outputs - Reorganized UI with logical grouping of parameters - Enhanced description with usage tips - Max value constraints added to prevent unreasonable inputs Technical improvements: - Use torch.nn.functional.interpolate for high-quality resizing - Smart crop algorithm that resizes first then crops to preserve quality - Proper tensor shape handling [batch, height, width, channels] - Aspect ratio deviation warnings when crop is disabled - min/max bounds on all numeric inputs Breaking changes: - Output order changed: resized_image is now first output - Output names simplified (width/height instead of constrained_width/constrained_height) - execute() signature expanded with crop parameters Bump version to 2.1.0
16 lines
584 B
TOML
16 lines
584 B
TOML
[project]
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name = "constrainresolution"
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description = "Given min/max resolution constraints, this automatically suggests optimal dimensions while preserving aspect ratio. Ideal for Image to Image (I2I) and Image to Video (I2V) workflows!"
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version = "2.1.0"
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license = {file = "LICENSE"}
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dependencies = ["numpy", "comfy_api"]
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[project.urls]
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Repository = "https://github.com/EnragedAntelope/ComfyUI-ConstrainResolution"
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# Used by Comfy Registry https://comfyregistry.org
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[tool.comfy]
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PublisherId = "enragedantelope"
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DisplayName = "ComfyUI-ConstrainResolution"
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Icon = ""
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