0.0.1
PhotoLab
ComfyUI node that applies effects to generated images like JPG compression, color grading, film grain, vignette, blur, and optional lighting matching with a reference image.
Features:
- JPG Compression Artifacts: Simulate digital compression degradation with adjustable quality and multiple passes
- Film Grain: Add realistic film grain noise with controllable strength
- Vignette: Apply darkening around image edges
- Color Grading: Choose from presets (None, Warm, Cool, Faded, Sepia) with adjustable strength
- Saturation Control: Adjust color saturation from grayscale to boosted
- Blur Effects: Multiple blur types including Gaussian, Box, Motion (horizontal/vertical), Radial, Lens, and Soft Focus
- Lighting Matching: Match lighting and shadows from a reference image using advanced algorithms (Histogram L-channel, Reinhard Transfer, Full LAB Histogram)
Effects:
- quality: JPG compression quality (0-100, lower = more artifacts)
- passes: Number of compression passes (1-10, more = more degradation)
- grain_strength: Strength of grain effect (0-100, 0 = disabled)
- vignette_strength: Strength of vignette effect (0-100, 0 = disabled)
- color_grade: Color grading preset ("None", "Warm", "Cool", "Faded", "Sepia")
- color_grade_strength: Strength of color grade effect (0-100)
- saturation: Color saturation (0-200, 100 = original)
- blur_type: Type of blur ("None", "Gaussian", "Box", "Motion Horizontal", "Motion Vertical", "Radial", "Lens", "Soft Focus")
- blur_strength: Strength of blur effect (0-100, 0 = disabled)
- lighting_match_mode: Algorithm for lighting transfer ("Disabled", "Histogram (L-channel)", "Reinhard Transfer", "Full LAB Histogram")
- lighting_match_strength: Blend strength for lighting match (0.0-1.0)
Optional Parameters:
- reference_image: Reference image tensor [B, H, W, C] for lighting matching (only used when lighting_match_mode is not "Disabled")
- Reset to Defaults Resets all parameters to their defults
Credit to: https://github.com/brucew4yn3rp/ComfyUI_VintageEffect.git
Languages
Python
80.2%
JavaScript
19.8%
