Uber Comfy Nodes - Misc ComfyUI Nodes

Handy "scratch-itch" nodes I've built while working in ComfyUI. Install the repo via Comfy Manager (recommended), then restart ComfyUI. All nodes appear under Uber Comfy.

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Node list

| # | Display name | What it does | Typical use-case | |---|--------------|--------------|------------------| | 1 | ControlNet Selector | Dropdown of every ControlNet file; does not load the model. | Pick once, pass name downstream. | | 2 | Load Optional ControlNet Model | Core loader fork with an extra None option so a workflow can disable ControlNet on the fly. | On/off toggles without duplicate graphs. | | 3 | Diffusers Selector | Dropdown of every Diffusers-format model folder; zero weight loading. | Feed the chosen path to custom loaders or merge nodes. | | 4 | Save Image JPG No Meta | Saves JPG (set quality) without PNG metadata chunks. | Produce lightweight web images. | | 5 | Multi Input Variable Rewrite | Up to 26 optional inputs ({a}…{z}) replace placeholders inside a template string. | Dynamic prompts, filename templating. | | 6 | Text Regex Operations | Chain up to 20 regex find/replace operations, each with its own pattern, replacement, and multiline flag. | Complex multi-step text processing and caption cleanup. | | 7 | Video Segment Calculator | Given clip duration, FPS & index, returns frame count, skip offset, precise start/end times (optional overlap). | Slice long videos into equal segments. | | 8 | Model Similarity Node | Compares two Stable-Diffusion models (tested SD1.x and SDXL so far) MODEL sockets. Calculates cosine similarity across every self-attention layer in input, middle and output blocks. | Detect fine-tunes, merges, or genuine scratch-trained checkpoints. | | 9 | Model Weight Dumper | Dumps all weight keys from a MODEL socket with optional shape/dtype info and prefix filtering. | Inspect model architecture, debug custom loaders, compare layer structures. | | 10 | Runware Resolution Calculator | Analyzes input image (with optional mask) and selects optimal resolution from model-specific presets using aspect ratio matching and area utilization scoring. | Auto-select best generation resolution for Nano Banana 2 and similar models. | | 11 | Adaptive Image Scaler | Intelligent scaling with automatic ML upscaler engagement (>1.08× scale), progressive tile reduction on OOM, and synchronized alpha channel processing. | High-quality upscaling with fallback safety and dimension alignment. |

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Example – Model Similarity Node

[Checkpoint Loader] ─► base_model
[Checkpoint Loader] ─► target_model
                    ╰─► Model Similarity Node

Possible outputs:

Similarity:  0-5 %   → truly independent training
Similarity: 60-90 %  → fine-tune / weight-merge
Similarity: 95 %+    → almost identical weights

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Examples for Selected Nodes

Text Regex Operations

Input text: "
*Start* of line and some extra text $5.99."


num_operations: 3
Pattern 1: "^\*"          → Replacement 1: "-"            (convert bullet * at line start to dash -)
Pattern 2: "\*(.*?)\*"  → Replacement 2: ""            (remove asterisks around words)
Pattern 3: "\$(.+)"       → Replacement 3: "Price: \1"      (label prices starting with $)


use_multiline_1: true
use_multiline_2: false
use_multiline_3: false


Output: "-Start of line and some extra text Price: 5.99."

Multi Input Variable Rewrite

Input text: "Create {a} image of {b} in {c} style"
Input a: "a beautiful"
Input b: "mountains" 
Input c: "anime"
Output: "Create a beautiful image of mountains in anime style"

Video Segment Calculator

Duration: 45.0 seconds, FPS: 30.0, Index: 2
Output: frame_load_cap=1350, skip_first_frames=2700, start_time=90.0, end_time=135.0
(Use this to split a 2-minute video into 45-second chunks and process second 90-135 separately)

Load Optional ControlNet Model

Set ControlNet name to "None" to disable ControlNet loading in workflows without rebuilding.

Save Image JPG No Meta

Saves all images in the batch as JPG files with the specified quality without writing any metadata

Model Weight Dumper

[Checkpoint Loader] ─► MODEL ─► Model Weight Dumper

show_shapes: true
filter_prefix: "model.diffusion_model.input_blocks"

Output: Text list of all matching weight keys with shapes and dtypes
Example output line: "model.diffusion_model.input_blocks.0.0.weight → (320, 4, 3, 3) (torch.float16)"

Runware Resolution Calculator

Input: Full image (1920×1080), cropped image, mask highlighting subject area (400×600px ROI)
model_preset: "Nano Banana 2"

Process:
- Analyzes ROI aspect ratio (2:3 portrait)
- Tests fitting strategies (width-anchor, height-anchor, proportional)
- Scores resolutions by expansion efficiency and scale match

Output: width=896, height=1200 (optimal 2:3 portrait from preset)
Console: "✓ Selected: 896×1200 (expansion: 2.15x)"

Adaptive Image Scaler

Scenario 1: Small upscale (1024×1024 → 1152×1152, scale 1.125x)
interpolation: "lanczos"
upscale_model: (connected)
dimension_alignment: 64

Process: Engages ML upscaler (>1.08× threshold), tiles at 512px, adjusts to 1152×1152 (64px aligned)
Output: High-quality ML-upscaled image with alpha channel preserved via bicubic interpolation


Scenario 2: Large downscale (4096×4096 → 1024×1024, scale 0.25x)
interpolation: "area"
upscale_model: None

Process: Uses direct "area" interpolation (best for downscaling), bypasses ML model
Output: Clean downscaled image with all 4 channels preserved

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Open an issue or PR if you spot a missing utility—this repo will keep growing as new workflow gaps appear.