{ "id": "9d4580e0-21d4-41fe-bc0b-0bc85129157c", "revision": 0, "last_node_id": 134, "last_link_id": 166, "nodes": [ { "id": 2, "type": "Fast Groups Bypasser (rgthree)", "pos": [ 3896.8669915591663, 1928.6478233214218 ], "size": [ 290, 60 ], "flags": { "pinned": true }, "order": 0, "mode": 0, "inputs": [], "outputs": [ { "name": "OPT_CONNECTION", "type": "*", "links": null } ], "title": "Global Overrides", "properties": { "matchColors": "", "matchTitle": "Global", "showNav": true, "showAllGraphs": true, "sort": "position", "customSortAlphabet": "", "toggleRestriction": "default" }, "color": "#322", "bgcolor": "#533" }, { "id": 3, "type": "MarkdownNote", "pos": [ 3436.8669915591663, 1928.6478233214218 ], "size": [ 430, 630 ], "flags": { "pinned": true }, "order": 1, "mode": 0, "inputs": [], "outputs": [], "title": "Missing Custom Nodes? See below for the link/URL", "properties": {}, "widgets_values": [ "# ⚠️ Custom nodes I use with this workflow\n---\n#### [rgthree-comfy](https://github.com/rgthree/rgthree-comfy)\n* https://github.com/rgthree/rgthree-comfy\n\n#### [ComfyUI-Custom-Scripts](https://github.com/pythongosssss/ComfyUI-Custom-Scripts)\n* https://github.com/pythongosssss/ComfyUI-Custom-Scripts\n\n#### [ComfyUI-KJNodes](https://github.com/kijai/ComfyUI-KJNodes)\n* https://github.com/kijai/ComfyUI-KJNodes\n\n#### [ComfyUI_UltimateSDUpscale](https://github.com/ssitu/ComfyUI_UltimateSDUpscale)\n* https://github.com/ssitu/ComfyUI_UltimateSDUpscale\n\n#### [ComfyUI-Inspire-Pack](https://github.com/ltdrdata/ComfyUI-Inspire-Pack)\n* https://github.com/ltdrdata/ComfyUI-Inspire-Pack\n\n#### [ComfyUI-Impact-Pack](https://github.com/ltdrdata/ComfyUI-Impact-Pack)\n* https://github.com/ltdrdata/ComfyUI-Impact-Pack\n\n#### [ComfyUI-Impact-Subpack](https://github.com/ltdrdata/ComfyUI-Impact-Subpack)\n* https://github.com/ltdrdata/ComfyUI-Impact-Subpack\n\n#### [ComfyMath](https://github.com/evanspearman/ComfyMath)\n* https://github.com/evanspearman/ComfyMath\n\n#### [ComfyUI-Image-Saver](https://github.com/alexopus/ComfyUI-Image-Saver)\n* https://github.com/alexopus/ComfyUI-Image-Saver\n\n#### [comfyui-gps-supplements](https://github.com/Goshe-nite/comfyui-gps-supplements)\n* https://github.com/Goshe-nite/comfyui-gps-supplements\n\n#### [ComfyUI-Easy-Color-Corrector](https://github.com/regiellis/ComfyUI-EasyColorCorrector)\n* https://github.com/regiellis/ComfyUI-EasyColorCorrector" ], "widgets_values_named": { "text": "# ⚠️ Custom nodes I use with this workflow\n---\n#### [rgthree-comfy](https://github.com/rgthree/rgthree-comfy)\n* https://github.com/rgthree/rgthree-comfy\n\n#### [ComfyUI-Custom-Scripts](https://github.com/pythongosssss/ComfyUI-Custom-Scripts)\n* https://github.com/pythongosssss/ComfyUI-Custom-Scripts\n\n#### [ComfyUI-KJNodes](https://github.com/kijai/ComfyUI-KJNodes)\n* https://github.com/kijai/ComfyUI-KJNodes\n\n#### [ComfyUI_UltimateSDUpscale](https://github.com/ssitu/ComfyUI_UltimateSDUpscale)\n* https://github.com/ssitu/ComfyUI_UltimateSDUpscale\n\n#### [ComfyUI-Inspire-Pack](https://github.com/ltdrdata/ComfyUI-Inspire-Pack)\n* https://github.com/ltdrdata/ComfyUI-Inspire-Pack\n\n#### [ComfyUI-Impact-Pack](https://github.com/ltdrdata/ComfyUI-Impact-Pack)\n* https://github.com/ltdrdata/ComfyUI-Impact-Pack\n\n#### [ComfyUI-Impact-Subpack](https://github.com/ltdrdata/ComfyUI-Impact-Subpack)\n* https://github.com/ltdrdata/ComfyUI-Impact-Subpack\n\n#### [ComfyMath](https://github.com/evanspearman/ComfyMath)\n* https://github.com/evanspearman/ComfyMath\n\n#### [ComfyUI-Image-Saver](https://github.com/alexopus/ComfyUI-Image-Saver)\n* https://github.com/alexopus/ComfyUI-Image-Saver\n\n#### [comfyui-gps-supplements](https://github.com/Goshe-nite/comfyui-gps-supplements)\n* https://github.com/Goshe-nite/comfyui-gps-supplements\n\n#### [ComfyUI-Easy-Color-Corrector](https://github.com/regiellis/ComfyUI-EasyColorCorrector)\n* https://github.com/regiellis/ComfyUI-EasyColorCorrector" }, "color": "#432", "bgcolor": "#653" }, { "id": 5, "type": "UNet loader with Name (Image Saver)", "pos": [ 4216.866991559166, 1928.6478233214218 ], "size": [ 330, 110 ], "flags": { "pinned": true }, "order": 2, "mode": 0, "inputs": [], "outputs": [ { "name": "model", "type": "MODEL", "links": [ 26 ] }, { "name": "filename", "type": "STRING", "links": [ 56 ] } ], "properties": { "cnr_id": "comfyui-image-saver", "ver": "1.21.0", "Node name for S&R": "UNet loader with Name (Image Saver)", "aux_id": "alexopus/ComfyUI-Image-Saver" }, "widgets_values": [ "Krea2_Turbo\\cyberChimera_v10Int8.safetensors", "default" ], "widgets_values_named": { "unet_name": "Krea2_Turbo\\cyberChimera_v10Int8.safetensors", "weight_dtype": "default" }, "color": "#323", "bgcolor": "#535" }, { "id": 6, "type": "CLIPLoader", "pos": [ 4216.866991559166, 2088.647823321422 ], "size": [ 330, 110 ], "flags": { "pinned": true }, "order": 3, "mode": 0, "inputs": [], "outputs": [ { "name": "CLIP", "type": "CLIP", "links": [ 50 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.17.0", "Node name for S&R": "CLIPLoader" }, "widgets_values": [ "qwen3vl_4b_fp8_scaled.safetensors", "krea2", "default" ], "widgets_values_named": { "clip_name": "qwen3vl_4b_fp8_scaled.safetensors", "type": "krea2", "device": "default" }, "color": "#432", "bgcolor": "#653" }, { "id": 9, "type": "Fast Groups Bypasser (rgthree)", "pos": [ 3896.8669915591663, 2038.6478233214218 ], "size": [ 290, 90 ], "flags": { "pinned": true }, "order": 4, "mode": 0, "inputs": [], "outputs": [ { "name": "OPT_CONNECTION", "type": "*", "links": null } ], "title": "Model Loader", "properties": { "matchColors": "", "matchTitle": "Loader", "showNav": true, "showAllGraphs": true, "sort": "position", "customSortAlphabet": "", "toggleRestriction": "default" }, "color": "#323", "bgcolor": "#535" }, { "id": 10, "type": "Fast Groups Bypasser (rgthree)", "pos": [ 3896.8669915591663, 2178.647823321422 ], "size": [ 290, 110 ], "flags": { "pinned": true }, "order": 5, "mode": 0, "inputs": [], "outputs": [ { "name": "OPT_CONNECTION", "type": "*", "links": null } ], "title": "Pre-USDU Upscale", "properties": { "matchColors": "brown", "matchTitle": "", "showNav": true, "showAllGraphs": true, "sort": "position", "customSortAlphabet": "", "toggleRestriction": "default" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 11, "type": "Bookmark (rgthree)", "pos": [ 6326.866991559166, 1798.6478233214218 ], "size": [ 210, 70 ], "flags": { "collapsed": true, "pinned": true }, "order": 6, "mode": 0, "inputs": [], "outputs": [], "title": "Initial Image", "properties": {}, "widgets_values": [ "2", 1 ], "widgets_values_named": { "shortcut_key": "2", "zoom": 1 }, "color": "#323", "bgcolor": "#535" }, { "id": 12, "type": "MarkdownNote", "pos": [ 6376.866991559166, 1928.6478233214218 ], "size": [ 250, 430 ], "flags": { "pinned": true }, "order": 7, "mode": 0, "inputs": [], "outputs": [], "properties": {}, "widgets_values": [ "# ⚠️ Wildcard Stability Guide\n---\n\n### 🎲 Why is my prompt still changing?\nSetting the **Global Seed** to \"Fixed\" only locks the sampler noise; it **does not** stop the Wildcard node from repopulating new strings. To lock in a specific wildcard result, you must interact directly with the **ImpactWildcardProcessor**.\n\n### 🛠️ How to Lock your Prompt\n1. **Set Mode to `reproduce`:** This is the only way to freeze the current wildcard selection.\n2. **The \"Auto-Reset\" Trap:** Be aware that this node may automatically switch back to `populate` after a retry or a fresh generation. \n3. **User Input vs. Output:** Setting the seed to \"Fixed\" only stabilizes your *input* text—it does **not** stabilize the final *output* string generated by the wildcard logic.\n\n---\n\n> **Pro-Tip:** If you've found a \"Golden Prompt\" via wildcards, copy the text from the lower box of the Wildcard node and paste it into the positive prompt instead to avoid the hassle of the wildcard switching back to 'populate' and then bypass the Wildcards group." ], "widgets_values_named": { "text": "# ⚠️ Wildcard Stability Guide\n---\n\n### 🎲 Why is my prompt still changing?\nSetting the **Global Seed** to \"Fixed\" only locks the sampler noise; it **does not** stop the Wildcard node from repopulating new strings. To lock in a specific wildcard result, you must interact directly with the **ImpactWildcardProcessor**.\n\n### 🛠️ How to Lock your Prompt\n1. **Set Mode to `reproduce`:** This is the only way to freeze the current wildcard selection.\n2. **The \"Auto-Reset\" Trap:** Be aware that this node may automatically switch back to `populate` after a retry or a fresh generation. \n3. **User Input vs. Output:** Setting the seed to \"Fixed\" only stabilizes your *input* text—it does **not** stabilize the final *output* string generated by the wildcard logic.\n\n---\n\n> **Pro-Tip:** If you've found a \"Golden Prompt\" via wildcards, copy the text from the lower box of the Wildcard node and paste it into the positive prompt instead to avoid the hassle of the wildcard switching back to 'populate' and then bypass the Wildcards group." }, "color": "#323", "bgcolor": "#535" }, { "id": 13, "type": "SDXL Empty Latent Image (rgthree)", "pos": [ 6376.866991559166, 2438.647823321422 ], "size": [ 250, 150 ], "flags": { "pinned": true }, "order": 8, "mode": 0, "inputs": [], "outputs": [ { "name": "LATENT", "type": "LATENT", "links": [ 28 ] }, { "name": "CLIP_WIDTH", "type": "INT", "links": [] }, { "name": "CLIP_HEIGHT", "type": "INT", "links": [] } ], "title": "SDXL Preset Latent Size", "properties": { "cnr_id": "rgthree-comfy", "ver": "1.0.2605082257", "Node name for S&R": "SDXL Empty Latent Image (rgthree)" }, "widgets_values": [ " 832 x 1216 (portrait)", 1, 1 ], "widgets_values_named": { "dimensions": " 832 x 1216 (portrait)", "clip_scale": 1, "batch_size": 1 }, "color": "#233", "bgcolor": "#355" }, { "id": 14, "type": "VAELoader", "pos": [ 4216.866991559166, 2248.647823321422 ], "size": [ 330, 70 ], "flags": { "pinned": true }, "order": 9, "mode": 0, "inputs": [], "outputs": [ { "name": "VAE", "type": "VAE", "links": [ 53 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.16.4", "Node name for S&R": "VAELoader" }, "widgets_values": [ "qwen_image_vae.safetensors" ], "widgets_values_named": { "vae_name": "qwen_image_vae.safetensors" }, "color": "#322", "bgcolor": "#533" }, { "id": 15, "type": "Fast Groups Bypasser (rgthree)", "pos": [ 6116.866991559166, 2418.647823321422 ], "size": [ 230, 60 ], "flags": { "pinned": true }, "order": 10, "mode": 0, "inputs": [], "outputs": [ { "name": "OPT_CONNECTION", "type": "*", "links": null } ], "title": "Wildcards", "properties": { "matchColors": "", "matchTitle": "Wildcard", "showNav": true, "showAllGraphs": true, "sort": "position", "customSortAlphabet": "", "toggleRestriction": "default" }, "color": "#223", "bgcolor": "#335" }, { "id": 16, "type": "CLIPTextEncode", "pos": [ 5676.866991559166, 2408.647823321422 ], "size": [ 240, 90 ], "flags": { "pinned": true }, "order": 74, "mode": 0, "inputs": [ { "name": "clip", "type": "CLIP", "link": 4 }, { "name": "text", "type": "STRING", "widget": { "name": "text" }, "link": 5 } ], "outputs": [ { "label": "positive", "name": "CONDITIONING", "type": "CONDITIONING", "links": [ 6, 8, 79, 103, 122, 141 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.16.4", "Node name for S&R": "CLIPTextEncode" }, "widgets_values": [ "" ], "widgets_values_named": { "text": "" }, "color": "#232", "bgcolor": "#353" }, { "id": 17, "type": "Fast Groups Bypasser (rgthree)", "pos": [ 6056.866991559166, 2528.647823321422 ], "size": [ 290, 60 ], "flags": { "pinned": true }, "order": 11, "mode": 0, "inputs": [], "outputs": [ { "name": "OPT_CONNECTION", "type": "*", "links": null } ], "title": "Custom Latent Size", "properties": { "matchColors": "", "matchTitle": "Latent", "showNav": true, "showAllGraphs": true, "sort": "position", "customSortAlphabet": "", "toggleRestriction": "default" }, "color": "#233", "bgcolor": "#355" }, { "id": 18, "type": "Checkpoint Loader with Name (Image Saver)", "pos": [ 4216.866991559166, 2408.647823321422 ], "size": [ 330, 120 ], "flags": { "pinned": true }, "order": 12, "mode": 4, "inputs": [], "outputs": [ { "name": "MODEL", "type": "MODEL", "links": [ 25 ] }, { "name": "CLIP", "type": "CLIP", "links": [ 49 ] }, { "name": "VAE", "type": "VAE", "links": [ 52 ] }, { "name": "model_name", "type": "STRING", "links": [ 55 ] } ], "title": "Checkpoint Loader (Image Saver)", "properties": { "cnr_id": "comfyui-image-saver", "ver": "1.24.0", "Node name for S&R": "Checkpoint Loader with Name (Image Saver)" }, "widgets_values": [ "waisnackmixCollection_wsmAnimaBeta.safetensors" ], "widgets_values_named": { "ckpt_name": "waisnackmixCollection_wsmAnimaBeta.safetensors" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 19, "type": "MarkdownNote", "pos": [ 4576.866991559166, 2258.647823321422 ], "size": [ 350, 260 ], "flags": { "pinned": true }, "order": 13, "mode": 0, "inputs": [], "outputs": [], "title": "Power Lora Loader (ChatGPT)", "properties": {}, "widgets_values": [ "## 🧠 Power Lora Loader\n\nThe **Power Lora Loader** is an advanced node from **rgthree’s ComfyUI extensions** that improves on the default Lora loader with extra tools for browsing, previewing, and managing Loras. It’s particularly useful if you work with models downloaded from **Civitai** or keep a large collection of Loras with metadata.\n\n---\n\n## ⚙️ Basic Functionality\n- **Loads LoRAs** (Low-Rank Adapters) into a model pipeline, just like the normal `LoraLoader` node.\n- Lets you **stack multiple LoRAs**, reorder them, and control their individual strengths.\n- Supports **drag-and-drop loading** from the ComfyUI file browser.\n\n---\n\n## 🖱️ Right-Click Menu Features\nRight-click on any loaded LoRA inside the node to open its context menu.\n\n### 🔍 “Show Info”\n- **Fetch info from civitai** from the LoRA’s embedded info or directly from its `model.json` or `civitai.info` file (if available).\n- Shows:\n - Model Name\n - Version\n - Author\n - Trained Base Model\n - Civitai URL\n - Description (short)\n - Suggested Trigger Words\n- If the `.safetensors` file has embedded metadata (Civitai automatically includes it), Power Lora Loader reads it locally — **no internet needed**.\n\n---\n\n## 🏷️ Trigger Word Tools\n\n### 🧩 “Trained Words”\nIf the lora has any trigger words/trained words. They will be listed after fetching the info from civitai.\n- There will be a listing of all known **trigger phrases** or **keywords** associated with that LoRA.\n- You can **click on a trigger** to copy it directly to your clipboard.\n- Useful for pasting into your prompt, prompt node, or **Markdown Note node**.\n \n> 💡 You can also **Ctrl+Click** or **Shift+Click** multiple trigger words to copy them together, separated by commas.\n\n---\n\n## 🖼️ Image Previews\nAfter fetching the info from civitai, it will also display sample images toward the bottom of the popup window.\n\nIf the LoRA has **multiple preview images**, you can cycle through them (small arrows appear when more than one image is found).\n\n---\n\n## 📦 Multi-LoRA Controls\n- Add multiple LoRAs to the same node with the ➕ button.\n- Adjust **strength (weight)** sliders per LoRA.\n- Reorder LoRAs with drag handles.\n- Toggle individual LoRAs on/off with checkboxes.\n\n---\n" ], "widgets_values_named": { "text": "## 🧠 Power Lora Loader\n\nThe **Power Lora Loader** is an advanced node from **rgthree’s ComfyUI extensions** that improves on the default Lora loader with extra tools for browsing, previewing, and managing Loras. It’s particularly useful if you work with models downloaded from **Civitai** or keep a large collection of Loras with metadata.\n\n---\n\n## ⚙️ Basic Functionality\n- **Loads LoRAs** (Low-Rank Adapters) into a model pipeline, just like the normal `LoraLoader` node.\n- Lets you **stack multiple LoRAs**, reorder them, and control their individual strengths.\n- Supports **drag-and-drop loading** from the ComfyUI file browser.\n\n---\n\n## 🖱️ Right-Click Menu Features\nRight-click on any loaded LoRA inside the node to open its context menu.\n\n### 🔍 “Show Info”\n- **Fetch info from civitai** from the LoRA’s embedded info or directly from its `model.json` or `civitai.info` file (if available).\n- Shows:\n - Model Name\n - Version\n - Author\n - Trained Base Model\n - Civitai URL\n - Description (short)\n - Suggested Trigger Words\n- If the `.safetensors` file has embedded metadata (Civitai automatically includes it), Power Lora Loader reads it locally — **no internet needed**.\n\n---\n\n## 🏷️ Trigger Word Tools\n\n### 🧩 “Trained Words”\nIf the lora has any trigger words/trained words. They will be listed after fetching the info from civitai.\n- There will be a listing of all known **trigger phrases** or **keywords** associated with that LoRA.\n- You can **click on a trigger** to copy it directly to your clipboard.\n- Useful for pasting into your prompt, prompt node, or **Markdown Note node**.\n \n> 💡 You can also **Ctrl+Click** or **Shift+Click** multiple trigger words to copy them together, separated by commas.\n\n---\n\n## 🖼️ Image Previews\nAfter fetching the info from civitai, it will also display sample images toward the bottom of the popup window.\n\nIf the LoRA has **multiple preview images**, you can cycle through them (small arrows appear when more than one image is found).\n\n---\n\n## 📦 Multi-LoRA Controls\n- Add multiple LoRAs to the same node with the ➕ button.\n- Adjust **strength (weight)** sliders per LoRA.\n- Reorder LoRAs with drag handles.\n- Toggle individual LoRAs on/off with checkboxes.\n\n---\n" }, "color": "#223", "bgcolor": "#335" }, { "id": 20, "type": "Fast Groups Bypasser (rgthree)", "pos": [ 3896.8669915591663, 2338.647823321422 ], "size": [ 290, 60 ], "flags": { "pinned": true }, "order": 14, "mode": 0, "inputs": [], "outputs": [ { "name": "OPT_CONNECTION", "type": "*", "links": null } ], "title": "USDU", "properties": { "matchColors": "green", "matchTitle": "", "showNav": true, "showAllGraphs": true, "sort": "position", "customSortAlphabet": "", "toggleRestriction": "default" }, "color": "#232", "bgcolor": "#353" }, { "id": 21, "type": "Fast Groups Bypasser (rgthree)", "pos": [ 3896.8669915591663, 2448.647823321422 ], "size": [ 290, 110 ], "flags": { "pinned": true }, "order": 15, "mode": 0, "inputs": [], "outputs": [ { "name": "OPT_CONNECTION", "type": "*", "links": null } ], "title": "Detailers", "properties": { "matchColors": "", "matchTitle": "Detailer", "showNav": true, "showAllGraphs": true, "sort": "position", "customSortAlphabet": "", "toggleRestriction": "default" }, "color": "#222", "bgcolor": "#000" }, { "id": 22, "type": "ConditioningZeroOut", "pos": [ 5680, 2550 ], "size": [ 240, 30 ], "flags": {}, "order": 77, "mode": 0, "inputs": [ { "name": "conditioning", "type": "CONDITIONING", "link": 6 } ], "outputs": [ { "name": "CONDITIONING", "type": "CONDITIONING", "links": [ 9, 80, 104, 123, 142 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.33.0", "Node name for S&R": "ConditioningZeroOut" }, "color": "#322", "bgcolor": "#533" }, { "id": 23, "type": "GlobalSeed //Inspire", "pos": [ 6656.866991559166, 1928.6478233214218 ], "size": [ 290, 130 ], "flags": { "collapsed": false, "pinned": true }, "order": 16, "mode": 0, "inputs": [], "outputs": [], "properties": { "cnr_id": "comfyui-inspire-pack", "ver": "d23db9aa544de9a6d4c609cb7005fa9e0d42031d", "Node name for S&R": "GlobalSeed //Inspire", "aux_id": "ltdrdata/ComfyUI-Inspire-Pack" }, "widgets_values": [ 3733834349, true, "increment for each node", 3733834348 ], "widgets_values_named": { "value": 3733834349, "mode": true, "action": "increment for each node", "last_seed": 3733834348 }, "color": "#322", "bgcolor": "#533" }, { "id": 24, "type": "CFGGuider", "pos": [ 6656.866991559166, 2378.647823321422 ], "size": [ 290, 100 ], "flags": { "pinned": true }, "order": 79, "mode": 0, "inputs": [ { "name": "model", "type": "MODEL", "link": 7 }, { "name": "positive", "type": "CONDITIONING", "link": 8 }, { "name": "negative", "type": "CONDITIONING", "link": 9 } ], "outputs": [ { "name": "GUIDER", "type": "GUIDER", "links": [ 20 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.28.0", "Node name for S&R": "CFGGuider" }, "widgets_values": [ 1 ], "widgets_values_named": { "cfg": 1 }, "color": "#323", "bgcolor": "#535" }, { "id": 25, "type": "RandomNoise", "pos": [ 6656.866991559166, 2528.647823321422 ], "size": [ 290, 90 ], "flags": { "pinned": true }, "order": 17, "mode": 0, "inputs": [], "outputs": [ { "name": "NOISE", "type": "NOISE", "links": [ 19 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.16.4", "Node name for S&R": "RandomNoise" }, "widgets_values": [ 3733834350, "randomize" ], "widgets_values_named": { "noise_seed": 3733834350, "control_after_generate": "randomize" }, "color": "#322", "bgcolor": "#533" }, { "id": 26, "type": "KSamplerSelect", "pos": [ 6656.866991559166, 2108.647823321422 ], "size": [ 290, 60 ], "flags": { "pinned": true }, "order": 18, "mode": 0, "inputs": [], "outputs": [ { "name": "SAMPLER", "type": "SAMPLER", "links": [ 21 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.16.4", "Node name for S&R": "KSamplerSelect" }, "widgets_values": [ "euler" ], "widgets_values_named": { "sampler_name": "euler" }, "color": "#223", "bgcolor": "#335" }, { "id": 27, "type": "Lora Prompt Concatenation", "pos": [ 4576.866991559166, 2578.647823321422 ], "size": [ 350, 50 ], "flags": { "pinned": true }, "order": 68, "mode": 0, "inputs": [ { "name": "lora_loader", "type": "*", "link": 10 }, { "name": "positive", "type": "STRING", "link": 11 } ], "outputs": [ { "name": "positive", "type": "STRING", "links": [ 161 ] } ], "properties": { "aux_id": "Goshe-nite/comfyui-gps-supplements", "ver": "7c7ac90471cf0b71a9be5bf4e99cdda2b732f741", "Node name for S&R": "Lora Prompt Concatenation" }, "color": "#223", "bgcolor": "#335" }, { "id": 28, "type": "BasicScheduler", "pos": [ 6656.866991559166, 2218.647823321422 ], "size": [ 290, 110 ], "flags": { "pinned": true }, "order": 69, "mode": 0, "inputs": [ { "name": "model", "type": "MODEL", "link": 12 } ], "outputs": [ { "name": "SIGMAS", "type": "SIGMAS", "links": [ 22 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.17.0", "Node name for S&R": "BasicScheduler" }, "widgets_values": [ "normal", 8, 1 ], "widgets_values_named": { "scheduler": "normal", "steps": 8, "denoise": 1 }, "color": "#323", "bgcolor": "#535" }, { "id": 29, "type": "MarkdownNote", "pos": [ 6656.866991559166, 2668.647823321422 ], "size": [ 290, 150 ], "flags": { "pinned": true }, "order": 19, "mode": 0, "inputs": [], "outputs": [], "title": "Fixed Seed Value", "properties": {}, "widgets_values": [ "## If you want the seed to actually be at a fixed value, make sure to bypass the Global Seed node.\n---\n### Personally, I leave this set to *fixed* here and on the USDU node and just toggle off *Global Seed* as needed." ], "widgets_values_named": { "text": "## If you want the seed to actually be at a fixed value, make sure to bypass the Global Seed node.\n---\n### Personally, I leave this set to *fixed* here and on the USDU node and just toggle off *Global Seed* as needed." }, "color": "#322", "bgcolor": "#533" }, { "id": 30, "type": "PreviewImage", "pos": [ 7366.866991559166, 1928.6478233214218 ], "size": [ 410, 630 ], "flags": { "pinned": true }, "order": 82, "mode": 0, "inputs": [ { "name": "images", "type": "IMAGE", "link": 13 } ], "outputs": [ { "name": "images", "type": "IMAGE", "links": null } ], "title": "initial Image Result", "properties": { "cnr_id": "comfy-core", "ver": "0.16.4", "Node name for S&R": "PreviewImage" }, "widgets_values": [], "widgets_values_named": {}, "color": "#323", "bgcolor": "#535" }, { "id": 31, "type": "EmptyLatentImage", "pos": [ 6376.866991559166, 2678.647823321422 ], "size": [ 250, 110 ], "flags": { "pinned": true }, "order": 75, "mode": 4, "inputs": [ { "name": "width", "type": "INT", "widget": { "name": "width" }, "link": 14 }, { "name": "height", "type": "INT", "widget": { "name": "height" }, "link": 15 } ], "outputs": [ { "label": "to Latent Switch", "name": "LATENT", "type": "LATENT", "links": [ 27 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.17.0", "Node name for S&R": "EmptyLatentImage" }, "widgets_values": [ 1248, 1824, 1 ], "widgets_values_named": { "width": 1248, "height": 1824, "batch_size": 1 }, "color": "#323", "bgcolor": "#535" }, { "id": 32, "type": "CM_IntToNumber", "pos": [ 6056.866991559166, 2878.647823321422 ], "size": [ 290, 60 ], "flags": { "pinned": true }, "order": 57, "mode": 0, "inputs": [ { "label": "width", "name": "a", "type": "INT", "widget": { "name": "a" }, "link": 16 } ], "outputs": [ { "label": "width", "name": "NUMBER", "type": "NUMBER", "links": [ 42 ] } ], "title": "Width - INT to Number", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_IntToNumber" }, "widgets_values": [ 0 ], "widgets_values_named": { "a": 0 }, "color": "#232", "bgcolor": "#353" }, { "id": 33, "type": "CM_SDXLResolution", "pos": [ 6056.866991559166, 2638.647823321422 ], "size": [ 290, 80 ], "flags": { "pinned": true }, "order": 20, "mode": 0, "inputs": [], "outputs": [ { "name": "width", "type": "INT", "links": [ 16 ] }, { "name": "height", "type": "INT", "links": [ 41 ] } ], "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_SDXLResolution" }, "widgets_values": [ "832x1216" ], "widgets_values_named": { "resolution": "832x1216" }, "color": "#232", "bgcolor": "#353" }, { "id": 34, "type": "CM_FloatToNumber", "pos": [ 6056.866991559166, 2768.647823321422 ], "size": [ 290, 60 ], "flags": { "pinned": true }, "order": 21, "mode": 0, "inputs": [ { "label": "scale_factor", "name": "a", "type": "FLOAT", "widget": { "name": "a" }, "link": null } ], "outputs": [ { "label": "scale_factor", "name": "NUMBER", "type": "NUMBER", "links": [ 43, 45 ] } ], "title": "Upscale SDXL Resolution by", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_FloatToNumber" }, "widgets_values": [ 1.5 ], "widgets_values_named": { "a": 1.5 }, "color": "#232", "bgcolor": "#353" }, { "id": 35, "type": "CM_NumberToInt", "pos": [ 6376.866991559166, 2838.647823321422 ], "size": [ 250, 30 ], "flags": { "pinned": true }, "order": 66, "mode": 4, "inputs": [ { "label": "width", "name": "a", "type": "NUMBER", "link": 17 } ], "outputs": [ { "label": "width", "name": "INT", "type": "INT", "links": [ 14 ] } ], "title": "Upscaled Width - Num to INT", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_NumberToInt" }, "color": "#323", "bgcolor": "#535" }, { "id": 36, "type": "CM_NumberToInt", "pos": [ 6376.866991559166, 2918.647823321422 ], "size": [ 250, 30 ], "flags": { "pinned": true }, "order": 67, "mode": 4, "inputs": [ { "label": "height", "name": "a", "type": "NUMBER", "link": 18 } ], "outputs": [ { "label": "height", "name": "INT", "type": "INT", "links": [ 15 ] } ], "title": "Upscaled Height - Num to INT", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_NumberToInt" }, "color": "#323", "bgcolor": "#535" }, { "id": 37, "type": "SamplerCustomAdvanced", "pos": [ 6976.866991559166, 1928.6478233214218 ], "size": [ 360, 630 ], "flags": { "collapsed": false, "pinned": true }, "order": 80, "mode": 0, "inputs": [ { "name": "noise", "type": "NOISE", "link": 19 }, { "name": "guider", "type": "GUIDER", "link": 20 }, { "name": "sampler", "type": "SAMPLER", "link": 21 }, { "name": "sigmas", "type": "SIGMAS", "link": 22 }, { "name": "latent_image", "type": "LATENT", "link": 23 } ], "outputs": [ { "name": "output", "type": "LATENT", "links": [ 29 ] }, { "name": "denoised_output", "type": "LATENT", "links": [] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.16.4", "Node name for S&R": "SamplerCustomAdvanced" }, "color": "#323", "bgcolor": "#535" }, { "id": 38, "type": "Reroute", "pos": [ 6956.866991559166, 2878.647823321422 ], "size": [ 82, 26 ], "flags": { "pinned": true }, "order": 59, "mode": 0, "inputs": [ { "name": "", "type": "*", "link": 24 } ], "outputs": [ { "name": "MODEL", "type": "MODEL", "links": [ 1, 70, 96, 114, 134 ] } ], "properties": { "showOutputText": true, "horizontal": false }, "color": "#323", "bgcolor": "#535" }, { "id": 39, "type": "Any Switch (rgthree)", "pos": [ 6656.866991559166, 2878.647823321422 ], "size": [ 270, 110 ], "flags": { "pinned": true }, "order": 53, "mode": 0, "inputs": [ { "dir": 3, "name": "any_01", "type": "MODEL", "link": 25 }, { "dir": 3, "name": "any_02", "type": "MODEL", "link": 26 }, { "dir": 3, "name": "any_03", "type": "MODEL", "link": null }, { "dir": 3, "name": "any_04", "type": "MODEL", "link": null }, { "dir": 3, "name": "any_05", "type": "MODEL", "link": null } ], "outputs": [ { "dir": 4, "label": "MODEL", "name": "*", "shape": 3, "type": "MODEL", "links": [ 24 ] } ], "properties": { "cnr_id": "rgthree-comfy", "ver": "1.0.2607232129" }, "color": "#323", "bgcolor": "#535" }, { "id": 40, "type": "Any Switch (rgthree)", "pos": [ 6976.866991559166, 2608.647823321422 ], "size": [ 240, 110 ], "flags": { "pinned": true }, "order": 78, "mode": 0, "inputs": [ { "dir": 3, "label": "Custom Latent Size", "name": "any_01", "type": "LATENT", "link": 27 }, { "dir": 3, "label": "SDXL Preset Latent", "name": "any_02", "type": "LATENT", "link": 28 }, { "dir": 3, "label": "any_03", "name": "any_03", "type": "LATENT", "link": null }, { "dir": 3, "name": "any_04", "type": "LATENT", "link": null }, { "dir": 3, "name": "any_05", "type": "LATENT", "link": null } ], "outputs": [ { "dir": 4, "label": "LATENT", "name": "*", "shape": 3, "type": "LATENT", "links": [ 23 ] } ], "title": "Automatic Latent Switch", "properties": { "cnr_id": "rgthree-comfy", "ver": "1.0.2604070017" }, "color": "#323", "bgcolor": "#535" }, { "id": 41, "type": "Fast Groups Bypasser (rgthree)", "pos": [ 3896.8669915591663, 2608.647823321422 ], "size": [ 290, 90 ], "flags": { "pinned": true }, "order": 22, "mode": 0, "inputs": [], "outputs": [ { "name": "OPT_CONNECTION", "type": "*", "links": null } ], "title": "End of Workflow", "properties": { "matchColors": "yellow", "matchTitle": "", "showNav": true, "showAllGraphs": true, "sort": "position", "customSortAlphabet": "", "toggleRestriction": "default" }, "color": "#432", "bgcolor": "#653" }, { "id": 42, "type": "VAEDecode", "pos": [ 7246.866991559166, 2608.647823321422 ], "size": [ 220, 50 ], "flags": { "pinned": true }, "order": 81, "mode": 0, "inputs": [ { "name": "samples", "type": "LATENT", "link": 29 }, { "name": "vae", "type": "VAE", "link": 30 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 13, 68, 145 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.16.4", "Node name for S&R": "VAEDecode" }, "color": "#323", "bgcolor": "#535" }, { "id": 43, "type": "ImageUpscaleWithModel", "pos": [ 7806.866991559166, 2178.647823321422 ], "size": [ 270, 50 ], "flags": { "pinned": true }, "order": 84, "mode": 4, "inputs": [ { "name": "upscale_model", "type": "UPSCALE_MODEL", "link": 31 }, { "name": "image", "type": "IMAGE", "link": 32 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 46 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.19.0", "Node name for S&R": "ImageUpscaleWithModel" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 44, "type": "Bookmark (rgthree)", "pos": [ 7746.866991559166, 1798.6478233214218 ], "size": [ 210, 70 ], "flags": { "collapsed": true, "pinned": true }, "order": 23, "mode": 0, "inputs": [], "outputs": [], "title": "Upscale", "properties": {}, "widgets_values": [ "3", 1 ], "widgets_values_named": { "shortcut_key": "3", "zoom": 1 }, "color": "#232", "bgcolor": "#353" }, { "id": 45, "type": "CM_NumberToInt", "pos": [ 7806.866991559166, 2938.647823321422 ], "size": [ 270, 30 ], "flags": { "pinned": true }, "order": 89, "mode": 0, "inputs": [ { "label": "width", "name": "a", "type": "NUMBER", "link": 33 } ], "outputs": [ { "label": "width", "name": "INT", "type": "INT", "links": [ 47 ] } ], "title": "Upscaled Width - Num to INT", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_NumberToInt" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 46, "type": "CM_NumberToInt", "pos": [ 7806.866991559166, 3018.647823321422 ], "size": [ 270, 30 ], "flags": { "pinned": true }, "order": 90, "mode": 0, "inputs": [ { "label": "height", "name": "a", "type": "NUMBER", "link": 34 } ], "outputs": [ { "label": "height", "name": "INT", "type": "INT", "links": [ 48 ] } ], "title": "Upscaled Height - Num to INT", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_NumberToInt" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 47, "type": "CM_NumberBinaryOperation", "pos": [ 7806.866991559166, 2678.647823321422 ], "size": [ 270, 80 ], "flags": { "pinned": true }, "order": 87, "mode": 0, "inputs": [ { "label": "width", "name": "a", "type": "NUMBER", "link": 35 }, { "label": "scale_factor", "name": "b", "type": "NUMBER", "link": 36 } ], "outputs": [ { "label": "width", "name": "NUMBER", "type": "NUMBER", "links": [ 33 ] } ], "title": "Multiply Width - Number", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_NumberBinaryOperation" }, "widgets_values": [ "Mul" ], "widgets_values_named": { "op": "Mul" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 48, "type": "CM_NumberBinaryOperation", "pos": [ 7806.866991559166, 2808.647823321422 ], "size": [ 270, 80 ], "flags": { "pinned": true }, "order": 88, "mode": 0, "inputs": [ { "label": "height", "name": "a", "type": "NUMBER", "link": 37 }, { "label": "scale_factor", "name": "b", "type": "NUMBER", "link": 38 } ], "outputs": [ { "label": "height", "name": "NUMBER", "type": "NUMBER", "links": [ 34 ] } ], "title": "Multiply Height - Number", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_NumberBinaryOperation" }, "widgets_values": [ "Mul" ], "widgets_values_named": { "op": "Mul" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 49, "type": "CM_IntToNumber", "pos": [ 7806.866991559166, 2458.647823321422 ], "size": [ 270, 60 ], "flags": { "pinned": true }, "order": 85, "mode": 0, "inputs": [ { "label": "width", "name": "a", "type": "INT", "widget": { "name": "a" }, "link": 39 } ], "outputs": [ { "label": "width", "name": "NUMBER", "type": "NUMBER", "links": [ 35 ] } ], "title": "Width - INT to Number", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_IntToNumber" }, "widgets_values": [ 0 ], "widgets_values_named": { "a": 0 }, "color": "#332922", "bgcolor": "#593930" }, { "id": 50, "type": "CM_IntToNumber", "pos": [ 7806.866991559166, 2568.647823321422 ], "size": [ 270, 60 ], "flags": { "pinned": true }, "order": 86, "mode": 0, "inputs": [ { "label": "height", "name": "a", "type": "INT", "widget": { "name": "a" }, "link": 40 } ], "outputs": [ { "label": "height", "name": "NUMBER", "type": "NUMBER", "links": [ 37 ] } ], "title": "Height - INT to Number", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_IntToNumber" }, "widgets_values": [ 0 ], "widgets_values_named": { "a": 0 }, "color": "#332922", "bgcolor": "#593930" }, { "id": 51, "type": "CM_FloatToNumber", "pos": [ 7806.866991559166, 1928.6478233214218 ], "size": [ 270, 60 ], "flags": { "pinned": true }, "order": 24, "mode": 0, "inputs": [ { "label": "scale_factor", "name": "a", "type": "FLOAT", "widget": { "name": "a" }, "link": null } ], "outputs": [ { "label": "scale_factor", "name": "NUMBER", "type": "NUMBER", "links": [ 36, 38 ] } ], "title": "Upscale by", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_FloatToNumber" }, "widgets_values": [ 2 ], "widgets_values_named": { "a": 2 }, "color": "#332922", "bgcolor": "#593930" }, { "id": 52, "type": "CM_IntToNumber", "pos": [ 6056.866991559166, 2988.647823321422 ], "size": [ 290, 60 ], "flags": { "pinned": true }, "order": 58, "mode": 0, "inputs": [ { "label": "height", "name": "a", "type": "INT", "widget": { "name": "a" }, "link": 41 } ], "outputs": [ { "label": "height", "name": "NUMBER", "type": "NUMBER", "links": [ 44 ] } ], "title": "Height - INT to Number", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_IntToNumber" }, "widgets_values": [ 0 ], "widgets_values_named": { "a": 0 }, "color": "#232", "bgcolor": "#353" }, { "id": 53, "type": "CM_NumberBinaryOperation", "pos": [ 6056.866991559166, 3098.647823321422 ], "size": [ 290, 80 ], "flags": { "pinned": true }, "order": 63, "mode": 0, "inputs": [ { "label": "width", "name": "a", "type": "NUMBER", "link": 42 }, { "label": "scale_factor", "name": "b", "type": "NUMBER", "link": 43 } ], "outputs": [ { "label": "width", "name": "NUMBER", "type": "NUMBER", "links": [ 17 ] } ], "title": "Multiply Width - Number", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_NumberBinaryOperation" }, "widgets_values": [ "Mul" ], "widgets_values_named": { "op": "Mul" }, "color": "#232", "bgcolor": "#353" }, { "id": 54, "type": "CM_NumberBinaryOperation", "pos": [ 6056.866991559166, 3228.647823321422 ], "size": [ 290, 80 ], "flags": { "pinned": true }, "order": 64, "mode": 0, "inputs": [ { "label": "height", "name": "a", "type": "NUMBER", "link": 44 }, { "label": "scale_factor", "name": "b", "type": "NUMBER", "link": 45 } ], "outputs": [ { "label": "height", "name": "NUMBER", "type": "NUMBER", "links": [ 18 ] } ], "title": "Multiply Height - Number", "properties": { "cnr_id": "ComfyMath", "ver": "c01177221c31b8e5fbc062778fc8254aeb541638", "Node name for S&R": "CM_NumberBinaryOperation" }, "widgets_values": [ "Mul" ], "widgets_values_named": { "op": "Mul" }, "color": "#232", "bgcolor": "#353" }, { "id": 55, "type": "MarkdownNote", "pos": [ 6376.866991559166, 2998.647823321422 ], "size": [ 250, 210 ], "flags": { "pinned": true }, "order": 25, "mode": 0, "inputs": [], "outputs": [], "title": "Custom Latent Size", "properties": {}, "widgets_values": [ "#### You can manually pick your latent size on the *Empty Latent Image* node.\n\n- If you want something larger than SDXL resolutions, but also don't want to do the math yourself you can connect the *width* and *height* outputs from the *Upscaled Width/Height - Num to INT* to the *width* and *height* inputs on the *Empty Latent Image* node.\n\n- Change the setting on the *Upscale SDXL Resolution* node to whatever you want and it will do the math for you. AFAIK it only works with .5 increments, but feel free to test it yourself." ], "widgets_values_named": { "text": "#### You can manually pick your latent size on the *Empty Latent Image* node.\n\n- If you want something larger than SDXL resolutions, but also don't want to do the math yourself you can connect the *width* and *height* outputs from the *Upscaled Width/Height - Num to INT* to the *width* and *height* inputs on the *Empty Latent Image* node.\n\n- Change the setting on the *Upscale SDXL Resolution* node to whatever you want and it will do the math for you. AFAIK it only works with .5 increments, but feel free to test it yourself." }, "color": "#232", "bgcolor": "#353" }, { "id": 56, "type": "ImageScale", "pos": [ 7806.866991559166, 2278.647823321422 ], "size": [ 270, 130 ], "flags": { "pinned": true }, "order": 91, "mode": 0, "inputs": [ { "name": "image", "type": "IMAGE", "link": 46 }, { "name": "width", "type": "INT", "widget": { "name": "width" }, "link": 47 }, { "name": "height", "type": "INT", "widget": { "name": "height" }, "link": 48 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 57, 75 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.19.0", "Node name for S&R": "ImageScale" }, "widgets_values": [ "lanczos", 1664, 2432, "disabled" ], "widgets_values_named": { "upscale_method": "lanczos", "width": 1664, "height": 2432, "crop": "disabled" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 57, "type": "UpscaleModelLoader", "pos": [ 7806.866991559166, 2068.647823321422 ], "size": [ 270, 60 ], "flags": { "pinned": true }, "order": 26, "mode": 4, "inputs": [], "outputs": [ { "name": "UPSCALE_MODEL", "type": "UPSCALE_MODEL", "links": [ 31 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.19.0", "Node name for S&R": "UpscaleModelLoader" }, "widgets_values": [ "4x-ClearRealityV1_Soft.pth" ], "widgets_values_named": { "model_name": "4x-ClearRealityV1_Soft.pth" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 58, "type": "Any Switch (rgthree)", "pos": [ 6656.866991559166, 3038.647823321422 ], "size": [ 270, 110 ], "flags": { "pinned": true }, "order": 54, "mode": 0, "inputs": [ { "dir": 3, "name": "any_01", "type": "CLIP", "link": 49 }, { "dir": 3, "name": "any_02", "type": "CLIP", "link": 50 }, { "dir": 3, "name": "any_03", "type": "CLIP", "link": null }, { "dir": 3, "name": "any_04", "type": "CLIP", "link": null }, { "dir": 3, "name": "any_05", "type": "CLIP", "link": null } ], "outputs": [ { "dir": 4, "label": "CLIP", "name": "*", "shape": 3, "type": "CLIP", "links": [ 51 ] } ], "properties": { "cnr_id": "rgthree-comfy", "ver": "1.0.2607232129" }, "color": "#432", "bgcolor": "#653" }, { "id": 59, "type": "Reroute", "pos": [ 6956.866991559166, 3038.647823321422 ], "size": [ 75, 26 ], "flags": { "pinned": true }, "order": 60, "mode": 0, "inputs": [ { "name": "", "type": "*", "link": 51 } ], "outputs": [ { "name": "CLIP", "type": "CLIP", "links": [ 2 ] } ], "properties": { "showOutputText": true, "horizontal": false }, "color": "#432", "bgcolor": "#653" }, { "id": 60, "type": "Any Switch (rgthree)", "pos": [ 6656.866991559166, 3198.647823321422 ], "size": [ 270, 110 ], "flags": { "pinned": true }, "order": 55, "mode": 0, "inputs": [ { "dir": 3, "name": "any_01", "type": "VAE", "link": 52 }, { "dir": 3, "name": "any_02", "type": "VAE", "link": 53 }, { "dir": 3, "name": "any_03", "type": "VAE", "link": null }, { "dir": 3, "name": "any_04", "type": "VAE", "link": null }, { "dir": 3, "name": "any_05", "type": "VAE", "link": null } ], "outputs": [ { "dir": 4, "label": "VAE", "name": "*", "shape": 3, "type": "VAE", "links": [ 54 ] } ], "properties": { "cnr_id": "rgthree-comfy", "ver": "1.0.2607232129" }, "color": "#322", "bgcolor": "#533" }, { "id": 61, "type": "Reroute", "pos": [ 6956.866991559166, 3198.647823321422 ], "size": [ 75, 26 ], "flags": { "pinned": true }, "order": 61, "mode": 0, "inputs": [ { "name": "", "type": "*", "link": 54 } ], "outputs": [ { "name": "VAE", "type": "VAE", "links": [ 30, 81, 102, 121, 140 ] } ], "properties": { "showOutputText": true, "horizontal": false }, "color": "#322", "bgcolor": "#533" }, { "id": 62, "type": "Any Switch (rgthree)", "pos": [ 6656.866991559166, 3358.647823321422 ], "size": [ 270, 110 ], "flags": { "pinned": true }, "order": 56, "mode": 0, "inputs": [ { "dir": 3, "name": "any_01", "type": "STRING", "link": 55 }, { "dir": 3, "name": "any_02", "type": "STRING", "link": 56 }, { "dir": 3, "name": "any_03", "type": "STRING", "link": null }, { "dir": 3, "name": "any_04", "type": "STRING", "link": null }, { "dir": 3, "name": "any_05", "type": "STRING", "link": null } ], "outputs": [ { "dir": 4, "label": "STRING", "name": "*", "shape": 3, "type": "STRING", "links": [ 69 ] } ], "properties": { "cnr_id": "rgthree-comfy", "ver": "1.0.2607232129" }, "color": "#222", "bgcolor": "#000" }, { "id": 63, "type": "VAELoader", "pos": [ 8106.866991559166, 2098.647823321422 ], "size": [ 300, 60 ], "flags": { "pinned": true }, "order": 27, "mode": 4, "inputs": [], "outputs": [ { "name": "VAE", "type": "VAE", "links": [ 59, 67 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.27.0", "Node name for S&R": "VAELoader", "models": [ { "name": "seedvr2_ema_vae_fp16.safetensors", "url": "https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/vae/seedvr2_ema_vae_fp16.safetensors", "directory": "vae" } ] }, "widgets_values": [ "seedvr2_ema_vae_fp16.safetensors" ], "widgets_values_named": { "vae_name": "seedvr2_ema_vae_fp16.safetensors" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 64, "type": "SeedVR2Preprocess", "pos": [ 8106.866991559166, 2208.647823321422 ], "size": [ 300, 40 ], "flags": { "pinned": true }, "order": 92, "mode": 4, "inputs": [ { "name": "resized_images", "type": "IMAGE", "link": 57 } ], "outputs": [ { "name": "images", "type": "IMAGE", "links": [ 58 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.27.0", "Node name for S&R": "SeedVR2Preprocess" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 65, "type": "UNETLoader", "pos": [ 8106.866991559166, 1958.6478233214218 ], "size": [ 300, 90 ], "flags": { "pinned": true }, "order": 28, "mode": 4, "showAdvanced": false, "inputs": [], "outputs": [ { "name": "MODEL", "type": "MODEL", "links": [ 60, 62 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.27.0", "Node name for S&R": "UNETLoader", "models": [ { "name": "seedvr2_3b_int8_convrot.safetensors", "url": "https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/diffusion_models/seedvr2_3b_int8_convrot.safetensors", "directory": "diffusion_models" } ] }, "widgets_values": [ "seedvr2_3b_int8_convrot.safetensors", "default" ], "widgets_values_named": { "unet_name": "seedvr2_3b_int8_convrot.safetensors", "weight_dtype": "default" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 66, "type": "VAEEncodeTiled", "pos": [ 8106.866991559166, 2298.647823321422 ], "size": [ 300, 150 ], "flags": { "pinned": true }, "order": 93, "mode": 4, "showAdvanced": true, "inputs": [ { "name": "pixels", "type": "IMAGE", "link": 58 }, { "name": "vae", "type": "VAE", "link": 59 } ], "outputs": [ { "name": "LATENT", "type": "LATENT", "links": [ 61, 65 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.27.0", "Node name for S&R": "VAEEncodeTiled" }, "widgets_values": [ 512, 128, 4096, 8 ], "widgets_values_named": { "tile_size": 512, "overlap": 128, "temporal_size": 4096, "temporal_overlap": 8 }, "color": "#332922", "bgcolor": "#593930" }, { "id": 67, "type": "SeedVR2Conditioning", "pos": [ 8106.866991559166, 2498.647823321422 ], "size": [ 300, 50 ], "flags": { "pinned": true }, "order": 94, "mode": 4, "inputs": [ { "name": "model", "type": "MODEL", "link": 60 }, { "label": "latent", "name": "vae_conditioning", "type": "LATENT", "link": 61 } ], "outputs": [ { "name": "positive", "type": "CONDITIONING", "links": [ 63 ] }, { "name": "negative", "type": "CONDITIONING", "links": [ 64 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.27.0", "Node name for S&R": "SeedVR2Conditioning" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 68, "type": "KSampler", "pos": [ 8106.866991559166, 2598.647823321422 ], "size": [ 300, 270 ], "flags": { "pinned": true }, "order": 95, "mode": 4, "inputs": [ { "name": "model", "type": "MODEL", "link": 62 }, { "name": "positive", "type": "CONDITIONING", "link": 63 }, { "name": "negative", "type": "CONDITIONING", "link": 64 }, { "name": "latent_image", "type": "LATENT", "link": 65 } ], "outputs": [ { "name": "LATENT", "type": "LATENT", "links": [ 66 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.27.0", "Node name for S&R": "KSampler" }, "widgets_values": [ 3733834351, "randomize", 1, 1, "euler", "simple", 0.4 ], "widgets_values_named": { "seed": 3733834351, "control_after_generate": "randomize", "steps": 1, "cfg": 1, "sampler_name": "euler", "scheduler": "simple", "denoise": 0.4 }, "color": "#332922", "bgcolor": "#593930" }, { "id": 69, "type": "VAEDecodeTiled", "pos": [ 8106.866991559166, 2918.647823321422 ], "size": [ 300, 150 ], "flags": { "pinned": true }, "order": 96, "mode": 4, "showAdvanced": true, "inputs": [ { "name": "samples", "type": "LATENT", "link": 66 }, { "name": "vae", "type": "VAE", "link": 67 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 74 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.27.0", "Node name for S&R": "VAEDecodeTiled" }, "widgets_values": [ 512, 128, 4096, 8 ], "widgets_values_named": { "tile_size": 512, "overlap": 128, "temporal_size": 4096, "temporal_overlap": 8 }, "color": "#332922", "bgcolor": "#593930" }, { "id": 70, "type": "MarkdownNote", "pos": [ 7496.866991559166, 2608.647823321422 ], "size": [ 280, 190 ], "flags": { "pinned": true }, "order": 29, "mode": 0, "inputs": [], "outputs": [], "title": "Latent Output", "properties": {}, "widgets_values": [ "#### There are two latent outputs on the *SamplerCustomAdvanced* node.\n\n#### By default, it is set to use *denoised_output* instead of *output*.\n\n#### The difference between the two is that *denoised_output* is supposed to clean any leftover noise on the initial image before it is sent to be upscaled.\n\n#### Feel free to switch which output is connected to the VAE Decode node if you have the desire." ], "widgets_values_named": { "text": "#### There are two latent outputs on the *SamplerCustomAdvanced* node.\n\n#### By default, it is set to use *denoised_output* instead of *output*.\n\n#### The difference between the two is that *denoised_output* is supposed to clean any leftover noise on the initial image before it is sent to be upscaled.\n\n#### Feel free to switch which output is connected to the VAE Decode node if you have the desire." }, "color": "#323", "bgcolor": "#535" }, { "id": 71, "type": "Fast Groups Bypasser (rgthree)", "pos": [ 7496.866991559166, 2848.647823321422 ], "size": [ 280, 110 ], "flags": { "pinned": true }, "order": 30, "mode": 0, "inputs": [], "outputs": [ { "name": "OPT_CONNECTION", "type": "*", "links": null } ], "title": "Pre-USDU Upscale", "properties": { "matchColors": "brown", "matchTitle": "", "showNav": true, "showAllGraphs": true, "sort": "position", "customSortAlphabet": "", "toggleRestriction": "default" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 72, "type": "GetImageSizeAndCount", "pos": [ 7806.866991559166, 3128.647823321422 ], "size": [ 270, 90 ], "flags": { "pinned": true }, "order": 83, "mode": 0, "inputs": [ { "name": "image", "type": "IMAGE", "link": 68 } ], "outputs": [ { "name": "image", "type": "IMAGE", "links": [ 32, 73 ] }, { "label": "832 width", "name": "width", "type": "INT", "links": [ 39 ] }, { "label": "1216 height", "name": "height", "type": "INT", "links": [ 40 ] }, { "label": "1 count", "name": "count", "type": "INT", "links": [] } ], "properties": { "cnr_id": "comfyui-kjnodes", "ver": "db419cd37b237b60efef67b3cf5e074c19730386", "Node name for S&R": "GetImageSizeAndCount", "aux_id": "kijai/ComfyUI-KJNodes" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 73, "type": "MarkdownNote", "pos": [ 7496.866991559166, 3008.647823321422 ], "size": [ 280, 150 ], "flags": { "pinned": true }, "order": 31, "mode": 0, "inputs": [], "outputs": [], "title": "Upscaling", "properties": {}, "widgets_values": [ "## USDU not required for upscaling\n---\n- You can do a very basic upscale using just the Pre-USDU Upscale group with *Upscale with Model* and *SeedVR2 Upscale* turned off.\n\n- *Upscale with Model* allows you to use an upscale model of your choosing.\n\n- IMO *SeedVR2 Upscale* is just a fancier upscale model and I wanted to try it out." ], "widgets_values_named": { "text": "## USDU not required for upscaling\n---\n- You can do a very basic upscale using just the Pre-USDU Upscale group with *Upscale with Model* and *SeedVR2 Upscale* turned off.\n\n- *Upscale with Model* allows you to use an upscale model of your choosing.\n\n- IMO *SeedVR2 Upscale* is just a fancier upscale model and I wanted to try it out." }, "color": "#332922", "bgcolor": "#593930" }, { "id": 74, "type": "Reroute", "pos": [ 6956.866991559166, 3358.647823321422 ], "size": [ 90.4, 26 ], "flags": { "pinned": true }, "order": 62, "mode": 0, "inputs": [ { "name": "", "type": "*", "widget": { "name": "value" }, "link": 69 } ], "outputs": [ { "name": "STRING", "type": "STRING", "links": [ 158 ] } ], "properties": { "showOutputText": true, "horizontal": false }, "color": "#222", "bgcolor": "#000" }, { "id": 75, "type": "KSamplerSelect", "pos": [ 8846.866991559167, 2058.647823321422 ], "size": [ 270, 60 ], "flags": { "pinned": true }, "order": 32, "mode": 0, "inputs": [], "outputs": [ { "name": "SAMPLER", "type": "SAMPLER", "links": [ 82 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.8.2", "Node name for S&R": "KSamplerSelect" }, "widgets_values": [ "euler" ], "widgets_values_named": { "sampler_name": "euler" }, "color": "#232", "bgcolor": "#353" }, { "id": 76, "type": "LazySwitchKJ", "pos": [ 8846.866991559167, 1928.6478233214218 ], "size": [ 270, 80 ], "flags": { "pinned": true }, "order": 70, "mode": 0, "inputs": [ { "name": "on_false", "type": "*", "link": 70 }, { "name": "on_true", "type": "*", "link": 71 }, { "label": "use lora", "name": "switch", "type": "BOOLEAN", "widget": { "name": "switch" }, "link": null } ], "outputs": [ { "name": "*", "type": "*", "links": [ 76, 78 ] } ], "title": "Use loaded LORA models?", "properties": { "cnr_id": "comfyui-kjnodes", "ver": "c88ac88a8f8a6a090a0d5d607156090cb2911503", "Node name for S&R": "LazySwitchKJ", "aux_id": "kijai/ComfyUI-KJNodes" }, "widgets_values": [ true ], "widgets_values_named": { "switch": true }, "color": "#232", "bgcolor": "#353" }, { "id": 77, "type": "MarkdownNote", "pos": [ 8846.866991559167, 2328.647823321422 ], "size": [ 270, 690 ], "flags": { "pinned": true }, "order": 33, "mode": 0, "inputs": [], "outputs": [], "title": "USDU notes by ChatGPT", "properties": {}, "widgets_values": [ "# Krea 2 Turbo — USDU 2× Upscale Presets\n\n**Source resolution:** 832 × 1216\n**Upscaled resolution:** 1664 × 2432\n**Recommended CFG:** 1.0\n**Preferred sampler:** Euler\n**Preferred scheduler:** Simple\n\n---\n\n## Conservative Preset\n\nBest for faces, clean skin, and minimizing cracked or overprocessed textures.\n\n| Setting | Value |\n| ----------------- | ------------------: |\n| Sampler | Euler |\n| Scheduler | Simple |\n| Steps | 3 |\n| Denoise | 0.20–0.22 |\n| Tile Width | 1024 |\n| Tile Height | 1024 |\n| Tile Padding | 128 |\n| Mask Blur | 8–16 |\n| Upscale Method | Lanczos |\n| USDU Mode | Linear |\n\n**Use this preset when:**\n\n* Skin texture is becoming cracked, scaly, wet, or overly detailed.\n* The original image already has good detail.\n* Character consistency is more important than adding new texture.\n\n---\n\n## Balanced Preset\n\nRecommended general-purpose starting point for most images.\n\n| Setting | Value |\n| ----------------- | -------------------: |\n| Sampler | Euler |\n| Scheduler | Simple |\n| Steps | 4 |\n| Denoise | 0.24–0.26 |\n| Tile Width | 1024–1280 |\n| Tile Height | 1024–1280 |\n| Tile Padding | 128 |\n| Mask Blur | 8–16 |\n| Upscale Method | Lanczos |\n| USDU Mode | Linear |\n\n**Suggested default:**\n\n`Euler + Simple, 4 steps, CFG 1.0, denoise 0.25, 1024 × 1024 tiles, 128 padding`\n\n**Use this preset when:**\n\n* You want additional clothing, hair, and environment detail.\n* The face already looks correct but needs mild refinement.\n* You want a reliable default for sharing a workflow.\n\n---\n\n## High-Detail Preset\n\nBest for clothing, armor, environments, machinery, and complex materials.\n\n| Setting | Value |\n| ----------------- | --------------------------------: |\n| Sampler | Euler |\n| Scheduler | Simple |\n| Steps | 5 |\n| Denoise | 0.28–0.30 |\n| Tile Width | 1280–1536 |\n| Tile Height | 1280–1536 |\n| Tile Padding | 128–160 |\n| Mask Blur | 12–20 |\n| Upscale Method | Lanczos or a mild neural upscaler |\n| USDU Mode | Linear or Chess |\n\n**Use this preset when:**\n\n* Clothing and background detail are more important than perfectly smooth skin.\n* The image contains intricate materials or environmental textures.\n* The conservative preset looks too soft.\n\n**Warning:** This preset has the highest chance of producing exaggerated pores, skin cracks, freckles, droplets, or artificial surface texture.\n\n---\n\n# Tile Padding Guidance\n\nFor a 2× upscale from 832 × 1216:\n\n| Padding | Recommendation |\n| ------: | ------------------------------------------- |\n| 64 | Usually too low; higher seam risk |\n| 96 | Efficient, but may show texture transitions |\n| 128 | Recommended balance |\n| 160 | Safer for complex textures |\n| 192 | Usually unnecessary for a simple 2× upscale |\n\nUse **128 padding** as the general default.\n\nIncrease padding when:\n\n* Tile seams are visible.\n* Skin or clothing texture changes at tile boundaries.\n* Large features cross between multiple tiles.\n\nReduce padding when:\n\n* VRAM usage is too high.\n* Processing is unusually slow.\n* Large tiles already provide sufficient context.\n\n---\n\n# Troubleshooting\n\n## Cracked, scaly, or overly detailed skin\n\nTry these changes in order:\n\n1. Reduce steps to 3 or 4.\n2. Lower denoise toward 0.20–0.24.\n3. Increase tile size.\n4. Disable realism, skin, photography, or texture LoRAs during USDU.\n5. Replace the neural upscale model with Lanczos.\n6. Remove skin-related prompt language.\n\n---\n\n## Visible tile seams\n\nTry:\n\n1. Increase padding from 96 to 128.\n2. Increase mask blur.\n3. Use Linear mode while testing.\n4. Use larger square tiles.\n5. Avoid very low denoise values that prevent proper blending.\n\n---\n\n## Image looks too soft\n\nTry:\n\n1. Increase steps from 3 to 4.\n2. Raise denoise by approximately 0.02.\n3. Increase tile size before adding more steps.\n4. Test a mild neural upscaler after confirming that Lanczos works cleanly.\n\n---\n\n## Character or face changes too much\n\nTry:\n\n1. Lower denoise.\n2. Reduce USDU steps.\n3. Disable character LoRAs during the upscale pass.\n4. Use the original generation prompt without additional detail language.\n5. Use larger tiles so the model retains more facial context.\n\n---\n\n# Recommended Workflow Default\n\nFor most 832 × 1216 images upscaled to 1664 × 2432:\n\n`Euler + Simple | 4 steps | CFG 1.0 | Denoise 0.25 | 1024 × 1024 tiles | 128 padding | Lanczos | Linear mode`\n\nFor especially sensitive skin:\n\n`Euler + Simple | 3 steps | CFG 1.0 | Denoise 0.21 | 1024 × 1024 tiles | 128 padding | Lanczos | Linear mode`\n" ], "widgets_values_named": { "text": "# Krea 2 Turbo — USDU 2× Upscale Presets\n\n**Source resolution:** 832 × 1216\n**Upscaled resolution:** 1664 × 2432\n**Recommended CFG:** 1.0\n**Preferred sampler:** Euler\n**Preferred scheduler:** Simple\n\n---\n\n## Conservative Preset\n\nBest for faces, clean skin, and minimizing cracked or overprocessed textures.\n\n| Setting | Value |\n| ----------------- | ------------------: |\n| Sampler | Euler |\n| Scheduler | Simple |\n| Steps | 3 |\n| Denoise | 0.20–0.22 |\n| Tile Width | 1024 |\n| Tile Height | 1024 |\n| Tile Padding | 128 |\n| Mask Blur | 8–16 |\n| Upscale Method | Lanczos |\n| USDU Mode | Linear |\n\n**Use this preset when:**\n\n* Skin texture is becoming cracked, scaly, wet, or overly detailed.\n* The original image already has good detail.\n* Character consistency is more important than adding new texture.\n\n---\n\n## Balanced Preset\n\nRecommended general-purpose starting point for most images.\n\n| Setting | Value |\n| ----------------- | -------------------: |\n| Sampler | Euler |\n| Scheduler | Simple |\n| Steps | 4 |\n| Denoise | 0.24–0.26 |\n| Tile Width | 1024–1280 |\n| Tile Height | 1024–1280 |\n| Tile Padding | 128 |\n| Mask Blur | 8–16 |\n| Upscale Method | Lanczos |\n| USDU Mode | Linear |\n\n**Suggested default:**\n\n`Euler + Simple, 4 steps, CFG 1.0, denoise 0.25, 1024 × 1024 tiles, 128 padding`\n\n**Use this preset when:**\n\n* You want additional clothing, hair, and environment detail.\n* The face already looks correct but needs mild refinement.\n* You want a reliable default for sharing a workflow.\n\n---\n\n## High-Detail Preset\n\nBest for clothing, armor, environments, machinery, and complex materials.\n\n| Setting | Value |\n| ----------------- | --------------------------------: |\n| Sampler | Euler |\n| Scheduler | Simple |\n| Steps | 5 |\n| Denoise | 0.28–0.30 |\n| Tile Width | 1280–1536 |\n| Tile Height | 1280–1536 |\n| Tile Padding | 128–160 |\n| Mask Blur | 12–20 |\n| Upscale Method | Lanczos or a mild neural upscaler |\n| USDU Mode | Linear or Chess |\n\n**Use this preset when:**\n\n* Clothing and background detail are more important than perfectly smooth skin.\n* The image contains intricate materials or environmental textures.\n* The conservative preset looks too soft.\n\n**Warning:** This preset has the highest chance of producing exaggerated pores, skin cracks, freckles, droplets, or artificial surface texture.\n\n---\n\n# Tile Padding Guidance\n\nFor a 2× upscale from 832 × 1216:\n\n| Padding | Recommendation |\n| ------: | ------------------------------------------- |\n| 64 | Usually too low; higher seam risk |\n| 96 | Efficient, but may show texture transitions |\n| 128 | Recommended balance |\n| 160 | Safer for complex textures |\n| 192 | Usually unnecessary for a simple 2× upscale |\n\nUse **128 padding** as the general default.\n\nIncrease padding when:\n\n* Tile seams are visible.\n* Skin or clothing texture changes at tile boundaries.\n* Large features cross between multiple tiles.\n\nReduce padding when:\n\n* VRAM usage is too high.\n* Processing is unusually slow.\n* Large tiles already provide sufficient context.\n\n---\n\n# Troubleshooting\n\n## Cracked, scaly, or overly detailed skin\n\nTry these changes in order:\n\n1. Reduce steps to 3 or 4.\n2. Lower denoise toward 0.20–0.24.\n3. Increase tile size.\n4. Disable realism, skin, photography, or texture LoRAs during USDU.\n5. Replace the neural upscale model with Lanczos.\n6. Remove skin-related prompt language.\n\n---\n\n## Visible tile seams\n\nTry:\n\n1. Increase padding from 96 to 128.\n2. Increase mask blur.\n3. Use Linear mode while testing.\n4. Use larger square tiles.\n5. Avoid very low denoise values that prevent proper blending.\n\n---\n\n## Image looks too soft\n\nTry:\n\n1. Increase steps from 3 to 4.\n2. Raise denoise by approximately 0.02.\n3. Increase tile size before adding more steps.\n4. Test a mild neural upscaler after confirming that Lanczos works cleanly.\n\n---\n\n## Character or face changes too much\n\nTry:\n\n1. Lower denoise.\n2. Reduce USDU steps.\n3. Disable character LoRAs during the upscale pass.\n4. Use the original generation prompt without additional detail language.\n5. Use larger tiles so the model retains more facial context.\n\n---\n\n# Recommended Workflow Default\n\nFor most 832 × 1216 images upscaled to 1664 × 2432:\n\n`Euler + Simple | 4 steps | CFG 1.0 | Denoise 0.25 | 1024 × 1024 tiles | 128 padding | Lanczos | Linear mode`\n\nFor especially sensitive skin:\n\n`Euler + Simple | 3 steps | CFG 1.0 | Denoise 0.21 | 1024 × 1024 tiles | 128 padding | Lanczos | Linear mode`\n" }, "color": "#232", "bgcolor": "#353" }, { "id": 78, "type": "Image Comparer (rgthree)", "pos": [ 8436.866991559167, 1928.6478233214218 ], "size": [ 380, 600 ], "flags": { "pinned": true }, "order": 99, "mode": 0, "inputs": [ { "dir": 3, "label": "after", "name": "image_a", "type": "IMAGE", "link": 166 }, { "dir": 3, "label": "before", "name": "image_b", "type": "IMAGE", "link": 73 } ], "outputs": [ { "dir": 4, "name": "images", "shape": 3, "type": "IMAGE", "links": null } ], "title": "Before and After Pre-USDU Upscale", "properties": { "cnr_id": "rgthree-comfy", "ver": 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}, "order": 97, "mode": 0, "inputs": [ { "dir": 3, "label": "SeedVR2", "name": "any_01", "type": "IMAGE", "link": 74 }, { "dir": 3, "label": "Basic Upscale", "name": "any_02", "type": "IMAGE", "link": 75 }, { "dir": 3, "name": "any_03", "type": "IMAGE", "link": null }, { "dir": 3, "name": "any_04", "type": "IMAGE", "link": null }, { "dir": 3, "name": "any_05", "type": "IMAGE", "link": null } ], "outputs": [ { "dir": 4, "label": "IMAGE", "name": "*", "shape": 3, "type": "IMAGE", "links": [ 77, 85, 166 ] } ], "properties": { "cnr_id": "rgthree-comfy", "ver": "1.0.2607232129" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 82, "type": "BasicScheduler", "pos": [ 8846.866991559167, 2168.647823321422 ], "size": [ 270, 110 ], "flags": { "pinned": true }, "order": 76, "mode": 0, "inputs": [ { "name": "model", "type": "MODEL", "link": 76 } ], "outputs": [ { "name": "SIGMAS", "type": "SIGMAS", "links": [ 83 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.15.1", "Node name for S&R": "BasicScheduler" }, "widgets_values": [ "normal", 4, 0.24 ], "widgets_values_named": { "scheduler": "normal", "steps": 4, "denoise": 0.24 }, "color": "#232", "bgcolor": "#353" }, { "id": 83, "type": "UltimateSDUpscaleCustomSample", "pos": [ 9146.866991559167, 1928.6478233214218 ], "size": [ 350, 1090 ], "flags": { "pinned": true }, "order": 98, "mode": 0, "inputs": [ { "name": "image", "type": "IMAGE", "link": 77 }, { "name": "model", "type": "MODEL", "link": 78 }, { "name": "positive", "type": "CONDITIONING", "link": 79 }, { "name": "negative", "type": "CONDITIONING", "link": 80 }, { "name": "vae", "type": "VAE", "link": 81 }, { "name": "upscale_model", "shape": 7, "type": "UPSCALE_MODEL", "link": null }, { "name": "custom_sampler", "shape": 7, "type": "SAMPLER", "link": 82 }, { "name": "custom_sigmas", "shape": 7, "type": "SIGMAS", "link": 83 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 84, 90, 93, 95, 98 ] } ], "properties": { "cnr_id": "comfyui_ultimatesdupscale", "ver": "1.6.2", "Node name for S&R": "UltimateSDUpscaleCustomSample", "aux_id": "ssitu/ComfyUI_UltimateSDUpscale" }, "widgets_values": [ 1, 3733834352, "randomize", 4, 1, "euler", "normal", 0.2, "Linear", 1280, 1280, 8, 96, "None", 1, 64, 8, 16, true, false, 1 ], "widgets_values_named": { "upscale_by": 1, "seed": 3733834352, "control_after_generate": "randomize", "steps": 4, "cfg": 1, "sampler_name": "euler", "scheduler": "normal", "denoise": 0.2, "mode_type": "Linear", "tile_width": 1280, "tile_height": 1280, "mask_blur": 8, "tile_padding": 96, "seam_fix_mode": "None", "seam_fix_denoise": 1, "seam_fix_width": 64, "seam_fix_mask_blur": 8, "seam_fix_padding": 16, "force_uniform_tiles": true, "tiled_decode": false, "batch_size": 1 }, "color": "#232", "bgcolor": "#353" }, { "id": 84, "type": "Image Comparer (rgthree)", "pos": [ 9526.866991559167, 1928.6478233214218 ], "size": [ 380, 600 ], "flags": { "pinned": true }, "order": 100, "mode": 0, "inputs": [ { "dir": 3, "label": "after", "name": "image_a", "type": "IMAGE", "link": 84 }, { "dir": 3, "label": "before", "name": "image_b", "type": "IMAGE", "link": 85 } ], "outputs": [ { "dir": 4, "name": "images", "shape": 3, "type": "IMAGE", "links": null } ], "title": "Before and After USDU", "properties": { "cnr_id": "rgthree-comfy", "ver": "8ff50e4521881eca1fe26aec9615fc9362474931", "comparer_mode": "Slide", "aux_id": "rgthree/rgthree-comfy" }, "widgets_values": [ [ { "name": "A", "selected": true, "url": "/api/view?filename=rgthree.compare._temp_hzhsh_00019_.png&type=temp&subfolder=&rand=0.22440321904760685" }, { "name": "B", "selected": true, "url": "/api/view?filename=rgthree.compare._temp_hzhsh_00020_.png&type=temp&subfolder=&rand=0.899796674034289" } ] ], "widgets_values_named": { "rgthree_comparer": { "images": [ { "name": "A", "selected": true, "url": "/api/view?filename=rgthree.compare._temp_hzhsh_00019_.png&type=temp&subfolder=&rand=0.22440321904760685", "img": {} }, { "name": "B", "selected": true, "url": "/api/view?filename=rgthree.compare._temp_hzhsh_00020_.png&type=temp&subfolder=&rand=0.899796674034289", "img": {} } ] } }, "color": "#232", "bgcolor": "#353" }, { "id": 85, "type": "MarkdownNote", "pos": [ 9936.866991559167, 2968.647823321422 ], "size": [ 340, 540 ], "flags": { "pinned": true }, "order": 34, "mode": 0, "inputs": [], "outputs": [], "title": "Detailer Recommendations by Gemini", "properties": {}, "widgets_values": [ "## 🧠 Impact Pack: The Detailer Logic\n\n| Parameter | What it actually does | Impact on Speed | Impact on Quality |\n| :--- | :--- | :--- | :--- |\n| **Guide Size** | The **target resolution** for the internal crop. If a face is smaller than this, the node upscales the patch to this size before detailing. | 🔴 **HIGH.** Doubling this can quadruple render time (quadratic scaling). | 🟢 **SWEET SPOT.** Setting this to the model's native res (1024) gives the most \"intelligent\" results. |\n| **Max Size** | The **hard limit**. If the crop (bbox * crop_factor) exceeds this, it is forced to downscale. This is your \"Safety Valve.\" | 🟡 **MEDIUM.** Prevents your GPU from crashing on accidentally massive crops. | 🟡 **NEUTRAL.** Only matters if your crop factor is so large it exceeds your GPU's VRAM limit. |\n\n---\n\n### 🚀 The Sweet Spot\nSince you are using 1024-native models, use these settings to drop from 40s/step to ~2s/step:\n\n* **guide_size: 1024** (Matches the model's training; prevents \"over-detailing\" or grainy skin).\n* **max_size: 1280** (Gives a little breathing room for hair/necks without exploding the resolution).\n* **guide_size_for: bbox** (Ensures the 1024 target applies specifically to the face, not the whole background crop).\n\n### ⚠️ Why your high settings are \"Bad\" for Quality:\nIf your target is 2432px, the model sees a single skin pore as a giant crater. \nIt tries to fill that \"crater\" with noise, resulting in:\n1. **The \"Sandpaper\" Effect:** Excessive grain and micro-contrast.\n2. **Double Features:** Two pupils or extra eyelashes (the model gets \"lost\" on such a huge canvas).\n3. **Flatness:** Paradoxically, too many pixels can make the lighting look \"averaged out\" and flat." ], "widgets_values_named": { "text": "## 🧠 Impact Pack: The Detailer Logic\n\n| Parameter | What it actually does | Impact on Speed | Impact on Quality |\n| :--- | :--- | :--- | :--- |\n| **Guide Size** | The **target resolution** for the internal crop. If a face is smaller than this, the node upscales the patch to this size before detailing. | 🔴 **HIGH.** Doubling this can quadruple render time (quadratic scaling). | 🟢 **SWEET SPOT.** Setting this to the model's native res (1024) gives the most \"intelligent\" results. |\n| **Max Size** | The **hard limit**. If the crop (bbox * crop_factor) exceeds this, it is forced to downscale. This is your \"Safety Valve.\" | 🟡 **MEDIUM.** Prevents your GPU from crashing on accidentally massive crops. | 🟡 **NEUTRAL.** Only matters if your crop factor is so large it exceeds your GPU's VRAM limit. |\n\n---\n\n### 🚀 The Sweet Spot\nSince you are using 1024-native models, use these settings to drop from 40s/step to ~2s/step:\n\n* **guide_size: 1024** (Matches the model's training; prevents \"over-detailing\" or grainy skin).\n* **max_size: 1280** (Gives a little breathing room for hair/necks without exploding the resolution).\n* **guide_size_for: bbox** (Ensures the 1024 target applies specifically to the face, not the whole background crop).\n\n### ⚠️ Why your high settings are \"Bad\" for Quality:\nIf your target is 2432px, the model sees a single skin pore as a giant crater. \nIt tries to fill that \"crater\" with noise, resulting in:\n1. **The \"Sandpaper\" Effect:** Excessive grain and micro-contrast.\n2. **Double Features:** Two pupils or extra eyelashes (the model gets \"lost\" on such a huge canvas).\n3. **Flatness:** Paradoxically, too many pixels can make the lighting look \"averaged out\" and flat." }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 86, "type": "MarkdownNote", "pos": [ 9936.866991559167, 3548.647823321422 ], "size": [ 340, 410 ], "flags": { "pinned": true }, "order": 35, "mode": 0, "inputs": [], "outputs": [], "title": "Detailer Recommendations by Gemini", "properties": {}, "widgets_values": [ "### 🛠️ The 'Force Inpaint' Toggle (Impact Pack)\n\nOne of the most common reasons a Detailer \"does nothing\" (even when it detects a face) is the interaction between `guide_size` and `force_inpaint`.\n\n* **The Logic (force_inpaint: FALSE):**\n * By default, the Detailer is \"lazy\" to save you time. \n * If the face it finds is **already larger** than your `guide_size` (e.g., your guide is 1024 but the face in the image is 1200px), the Detailer assumes the face already has enough resolution and **skips it entirely**.\n * This is why people often see the detector \"box\" appear, but no actual detail changes—the image was already \"good enough\" according to the settings.\n\n* **The Logic (force_inpaint: TRUE):**\n * Setting this to **TRUE** disables the \"Skip Logic.\"\n * The Detailer will run a full inpainting pass on the face **no matter how large it is**. Even if the face is 4K, it will crop it, process it at your guide_size, and stitch it back.\n\n### ❓ Why isn't my Detailer doing anything?\nIf your Detailer is running but the image isn't changing, check these three things in order:\n1. **Force Inpaint:** Set this to **TRUE** if you want to ensure the face is always refined.\n2. **Denoise:** If your denoise is too low (e.g., 0.1), the changes might be too subtle to see.\n3. **Drop Size:** If the face is very small and your `drop_size` is too high, the node will skip the face because it thinks it's just \"noise.\"" ], "widgets_values_named": { "text": "### 🛠️ The 'Force Inpaint' Toggle (Impact Pack)\n\nOne of the most common reasons a Detailer \"does nothing\" (even when it detects a face) is the interaction between `guide_size` and `force_inpaint`.\n\n* **The Logic (force_inpaint: FALSE):**\n * By default, the Detailer is \"lazy\" to save you time. \n * If the face it finds is **already larger** than your `guide_size` (e.g., your guide is 1024 but the face in the image is 1200px), the Detailer assumes the face already has enough resolution and **skips it entirely**.\n * This is why people often see the detector \"box\" appear, but no actual detail changes—the image was already \"good enough\" according to the settings.\n\n* **The Logic (force_inpaint: TRUE):**\n * Setting this to **TRUE** disables the \"Skip Logic.\"\n * The Detailer will run a full inpainting pass on the face **no matter how large it is**. Even if the face is 4K, it will crop it, process it at your guide_size, and stitch it back.\n\n### ❓ Why isn't my Detailer doing anything?\nIf your Detailer is running but the image isn't changing, check these three things in order:\n1. **Force Inpaint:** Set this to **TRUE** if you want to ensure the face is always refined.\n2. **Denoise:** If your denoise is too low (e.g., 0.1), the changes might be too subtle to see.\n3. **Drop Size:** If the face is very small and your `drop_size` is too high, the node will skip the face because it thinks it's just \"noise.\"" }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 87, "type": "MarkdownNote", "pos": [ 9936.866991559167, 2508.647823321422 ], "size": [ 340, 420 ], "flags": { "pinned": true }, "order": 36, "mode": 0, "inputs": [], "outputs": [], "title": "Detailer Recommendations by Gemini", "properties": {}, "widgets_values": [ "### 🧩 MASK to SEGS (Impact Pack)\nUse this node to convert masks (from Segment Anything, manual painting, etc.) into \"SEGS\" for the Detailer.\n\n* **The 'Combined' Setting:**\n * **TRUE (Default):** Merges all mask islands into one single bounding box. Fast, but less precise for scattered objects.\n * **FALSE:** Generates a separate \"SEGS\" entry for every disconnected part of the mask. Highly recommended for multiple subjects or distant objects.\n\n* **The 'Drop Size' Parameter (Efficiency Booster):**\n * **What it does:** Sets a minimum pixel threshold. Any mask segment smaller than this number is ignored and \"dropped\" from the detailer pass.\n * **Why it matters:** If your mask has tiny accidental specks of \"dust\" or very small distant background objects, the Detailer will try to run a full sampling pass on each one. \n * **Recommended Value:** **10 to 15**. This ensures only meaningful shapes are processed, saving you from wasting time on invisible artifacts.\n\n* **The 'BBox Fill' Setting:**\n * **Status:** Usually keep this **FALSE**. If set to True, it ignores the specific shape of your mask and just details the entire square box around it, which can lead to \"square-shaped\" artifacts in your final image." ], "widgets_values_named": { "text": "### 🧩 MASK to SEGS (Impact Pack)\nUse this node to convert masks (from Segment Anything, manual painting, etc.) into \"SEGS\" for the Detailer.\n\n* **The 'Combined' Setting:**\n * **TRUE (Default):** Merges all mask islands into one single bounding box. Fast, but less precise for scattered objects.\n * **FALSE:** Generates a separate \"SEGS\" entry for every disconnected part of the mask. Highly recommended for multiple subjects or distant objects.\n\n* **The 'Drop Size' Parameter (Efficiency Booster):**\n * **What it does:** Sets a minimum pixel threshold. Any mask segment smaller than this number is ignored and \"dropped\" from the detailer pass.\n * **Why it matters:** If your mask has tiny accidental specks of \"dust\" or very small distant background objects, the Detailer will try to run a full sampling pass on each one. \n * **Recommended Value:** **10 to 15**. This ensures only meaningful shapes are processed, saving you from wasting time on invisible artifacts.\n\n* **The 'BBox Fill' Setting:**\n * **Status:** Usually keep this **FALSE**. If set to True, it ignores the specific shape of your mask and just details the entire square box around it, which can lead to \"square-shaped\" artifacts in your final image." }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 88, "type": "MarkdownNote", "pos": [ 9936.866991559167, 1928.6478233214218 ], "size": [ 340, 540 ], "flags": { "pinned": true }, "order": 37, "mode": 0, "inputs": [], "outputs": [], "title": "Detailer Recommendations by Gemini", "properties": {}, "widgets_values": [ "## 👁️ Detailer & Detection Troubleshooting\n---\n\n### 🛠️ Issue: \"The Detailer is ruining my image!\"\nIf you are seeing weird artifacts—like only one eye being fixed while the other is ignored—follow this stability checklist:\n\n1. **Lock the Seed:** Change your **Global Seed** mode to **`fixed`**. \n2. **Handle Wildcards:** If using wildcards, set the **ImpactWildcardProcessor** to **`reproduce`**.\n * *Note:* If you retry, you **must** ensure it hasn't reset to `populate`.\n3. **Force Focus:** Type `eye` (or the specific part you are fixing) into the **wildcard_spec** field on the Detailer node to guide the model.\n4. **The ComfyUI \"Glitch\":** Recent updates sometimes force a full restart even on a fixed seed. If it still rerolls, try bypass/unbypass the node to \"nudge\" it.\n\n---\n\n### 🎯 Issue: \"The Detector is flagging the wrong things!\"\n*(Example: Face detection picking up anatomy it shouldn't)*\n\n* **Increase Threshold:** Raise the **threshold** on the **BBOX Detector SEGS** node. This makes the model \"stricter\" about what it calls a face.\n* **Model Limits:** Some detection models have \"false positives\" baked into their training. If it keeps failing, try swapping to a different detector model.\n\n---\n\n### 🔍 Issue: \"The Detector isn't finding anything!\"\n\n* **Decrease Threshold:** Lower the **threshold** value. This makes the detector more \"desperate\" to find a match.\n* **The Last Resort:** If the model still won't see it, the subject might be too small or too obscured in the latent space for that specific detection model to register." ], "widgets_values_named": { "text": "## 👁️ Detailer & Detection Troubleshooting\n---\n\n### 🛠️ Issue: \"The Detailer is ruining my image!\"\nIf you are seeing weird artifacts—like only one eye being fixed while the other is ignored—follow this stability checklist:\n\n1. **Lock the Seed:** Change your **Global Seed** mode to **`fixed`**. \n2. **Handle Wildcards:** If using wildcards, set the **ImpactWildcardProcessor** to **`reproduce`**.\n * *Note:* If you retry, you **must** ensure it hasn't reset to `populate`.\n3. **Force Focus:** Type `eye` (or the specific part you are fixing) into the **wildcard_spec** field on the Detailer node to guide the model.\n4. **The ComfyUI \"Glitch\":** Recent updates sometimes force a full restart even on a fixed seed. If it still rerolls, try bypass/unbypass the node to \"nudge\" it.\n\n---\n\n### 🎯 Issue: \"The Detector is flagging the wrong things!\"\n*(Example: Face detection picking up anatomy it shouldn't)*\n\n* **Increase Threshold:** Raise the **threshold** on the **BBOX Detector SEGS** node. This makes the model \"stricter\" about what it calls a face.\n* **Model Limits:** Some detection models have \"false positives\" baked into their training. If it keeps failing, try swapping to a different detector model.\n\n---\n\n### 🔍 Issue: \"The Detector isn't finding anything!\"\n\n* **Decrease Threshold:** Lower the **threshold** value. This makes the detector more \"desperate\" to find a match.\n* **The Last Resort:** If the model still won't see it, the subject might be too small or too obscured in the latent space for that specific detection model to register." }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 89, "type": "Bookmark (rgthree)", "pos": [ 9886.866991559167, 1798.6478233214218 ], "size": [ 210, 70 ], "flags": { "collapsed": true, "pinned": true }, "order": 38, "mode": 0, "inputs": [], "outputs": [], "title": "Detailers", "properties": {}, "widgets_values": [ "4", 1 ], "widgets_values_named": { "shortcut_key": "4", "zoom": 1 }, "color": "#223", "bgcolor": "#335" }, { "id": 90, "type": "MaskToImage", "pos": [ 10296.866991559167, 3078.647823321422 ], "size": [ 270, 30 ], "flags": { "collapsed": false, "pinned": true }, "order": 103, "mode": 4, "inputs": [ { "name": "mask", "type": "MASK", "link": 86 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 87 ] } ], "properties": { "cnr_id": 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"cnr_id": "comfyui-kjnodes", "ver": "7519171dd6b6ccea43091c6b73e42443bba11f5b", "Node name for S&R": "WidgetToString", "aux_id": "kijai/ComfyUI-KJNodes" }, "widgets_values": [ 28, "steps", false, "", 2 ], "widgets_values_named": { "id": 28, "widget_name": "steps", "return_all": false, "node_title": "", "allowed_float_decimals": 2 }, "color": "#432", "bgcolor": "#653" }, { "id": 81, "type": "MarkdownNote", "pos": [ 8440, 2900 ], "size": [ 380, 180 ], "flags": {}, "order": 47, "mode": 0, "inputs": [], "outputs": [], "title": "Regarding SeedVR2", "properties": {}, "widgets_values": [ "#### The nodes used for SeedVR2 are taken from the searchable template for the seedVR2_3b found when clicking on the templates button typically located on the left side of your ComfyUI canvas.\n\n- These nodes are hidden in a subgraph on the template, but these were the default settings. I haven't messed with the settings, so change them at your own peril.\n\n- **The default denoise setting is 1.0**\n- Changing the **denoise** to lower values does seem to reduce the effect, but other than that IDK.\n- Denoise 0.40 works well for me when using it with SeedVR2 before USDU." ], "widgets_values_named": { "text": "#### The nodes used for SeedVR2 are taken from the searchable template for the seedVR2_3b found when clicking on the templates button typically located on the left side of your ComfyUI canvas.\n\n- These nodes are hidden in a subgraph on the template, but these were the default settings. I haven't messed with the settings, so change them at your own peril.\n\n- **The default denoise setting is 1.0**\n- Changing the **denoise** to lower values does seem to reduce the effect, but other than that IDK.\n- Denoise 0.40 works well for me when using it with SeedVR2 before USDU." }, "color": "#332922", "bgcolor": "#593930" }, { "id": 7, "type": "Power Lora Loader (rgthree)", "pos": [ 4580, 1930 ], "size": [ 350, 280 ], "flags": { "pinned": true }, "order": 65, "mode": 0, "inputs": [ { "dir": 3, "name": "model", "type": "MODEL", "link": 1 }, { "dir": 3, "name": "clip", "type": "CLIP", "link": 2 } ], "outputs": [ { "dir": 4, "name": "MODEL", "shape": 3, "type": "MODEL", "links": [ 7, 10, 12, 71, 97, 115, 135 ] }, { "dir": 4, "name": "CLIP", "shape": 3, "type": "CLIP", "links": [ 4, 101, 120, 139 ] } ], "properties": { "cnr_id": "rgthree-comfy", "ver": "1.0.2607232129", "Show Strengths": "Single Strength", "Match": "" }, "widgets_values": [ {}, { "type": "PowerLoraLoaderHeaderWidget" }, {}, "" ], "widgets_values_named": { "divider": {}, "PowerLoraLoaderHeaderWidget": { "type": "PowerLoraLoaderHeaderWidget" }, "➕ Add Lora": "" }, "color": "#323", "bgcolor": "#535" }, { "id": 8, "type": "StringFunction|pysssss", "pos": [ 4956.866991559166, 1928.6478233214218 ], "size": [ 690, 610 ], "flags": { "pinned": true }, "order": 48, "mode": 0, "inputs": [], "outputs": [ { "label": "positive", "name": "STRING", "type": "STRING", "links": [ 5, 11 ] } ], "title": "Positive Prompt", "properties": { "cnr_id": "comfyui-custom-scripts", "ver": "1.2.5", "Node name for S&R": "StringFunction|pysssss", "aux_id": "pythongosssss/ComfyUI-Custom-Scripts" }, "widgets_values": [ "append", "no", "", "", "" ], "widgets_values_named": { "action": "append", "tidy_tags": "no", "text_a": "", "text_b": "", "text_c": "" }, "color": "#223", "bgcolor": "#335" }, { "id": 4, "type": "ImpactWildcardProcessor", "pos": [ 5676.866991559166, 1928.6478233214218 ], "size": [ 670, 430 ], "flags": { "pinned": true }, "order": 49, "mode": 4, "inputs": [], "outputs": [ { "name": "processed text", "type": "STRING", "links": [] } ], "properties": { "cnr_id": "comfyui-impact-pack", "ver": "8.28.2", "Node name for S&R": "ImpactWildcardProcessor" }, "widgets_values": [ "", "", "populate", 3733834349, "randomize", "Select Wildcard 🟢 Full Cache" ], "widgets_values_named": { "wildcard_text": "", "populated_text": "", "mode": "populate", "seed": 3733834349, "control_after_generate": "randomize", "Select to add Wildcard": "Select Wildcard 🟢 Full Cache" }, "color": "#232", "bgcolor": "#353" }, { "id": 80, "type": "MarkdownNote", "pos": [ 8436.866991559167, 2578.647823321422 ], "size": [ 380, 270 ], "flags": { "pinned": true }, "order": 50, "mode": 0, "inputs": [], "outputs": [], "title": "Note: SeedVR2 Model Links", "properties": {}, "widgets_values": [ "## Model Links\n\n**vae**\n\n- [seedvr2_ema_vae_fp16.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/vae/seedvr2_ema_vae_fp16.safetensors)\n\n**diffusion_models**\n\n- [seedvr2_3b_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/diffusion_models/seedvr2_3b_int8_convrot.safetensors)\n\n\n## Model Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 vae/\n│ │ └── seedvr2_ema_vae_fp16.safetensors\n│ └── 📂 diffusion_models/\n│ └── seedvr2_3b_int8_convrot.safetensors\n```\n" ], "widgets_values_named": { "text": "## Model Links\n\n**vae**\n\n- [seedvr2_ema_vae_fp16.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/vae/seedvr2_ema_vae_fp16.safetensors)\n\n**diffusion_models**\n\n- [seedvr2_3b_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/diffusion_models/seedvr2_3b_int8_convrot.safetensors)\n\n\n## Model Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 vae/\n│ │ └── seedvr2_ema_vae_fp16.safetensors\n│ └── 📂 diffusion_models/\n│ └── seedvr2_3b_int8_convrot.safetensors\n```\n" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 134, "type": "MarkdownNote", "pos": [ 3440, 2610 ], "size": [ 430, 270 ], "flags": { "pinned": true }, "order": 51, "mode": 0, "inputs": [], "outputs": [], "title": "Note: SeedVR2 Model Links", "properties": {}, "widgets_values": [ "## Model Links\n\n**vae**\n\n- [seedvr2_ema_vae_fp16.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/vae/seedvr2_ema_vae_fp16.safetensors)\n\n**diffusion_models**\n\n- [seedvr2_3b_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/diffusion_models/seedvr2_3b_int8_convrot.safetensors)\n\n\n## Model Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 vae/\n│ │ └── seedvr2_ema_vae_fp16.safetensors\n│ └── 📂 diffusion_models/\n│ └── seedvr2_3b_int8_convrot.safetensors\n```\n" ], "widgets_values_named": { "text": "## Model Links\n\n**vae**\n\n- [seedvr2_ema_vae_fp16.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/vae/seedvr2_ema_vae_fp16.safetensors)\n\n**diffusion_models**\n\n- [seedvr2_3b_int8_convrot.safetensors](https://huggingface.co/Comfy-Org/SeedVR2/resolve/main/diffusion_models/seedvr2_3b_int8_convrot.safetensors)\n\n\n## Model Storage Location\n\n```\n📂 ComfyUI/\n├── 📂 models/\n│ ├── 📂 vae/\n│ │ └── seedvr2_ema_vae_fp16.safetensors\n│ └── 📂 diffusion_models/\n│ └── seedvr2_3b_int8_convrot.safetensors\n```\n" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 1, "type": "Bookmark (rgthree)", "pos": [ 3390, 1800 ], "size": [ 210, 70 ], "flags": { "collapsed": true, "pinned": true }, "order": 52, "mode": 0, "inputs": [], "outputs": [], "title": "Start Here", "properties": {}, "widgets_values": [ "1", 1 ], "widgets_values_named": { "shortcut_key": "1", "zoom": 1 }, "color": "#432", "bgcolor": "#653" } ], "links": [ [ 1, 38, 0, 7, 0, "MODEL" ], [ 2, 59, 0, 7, 1, "CLIP" ], [ 4, 7, 1, 16, 0, "CLIP" ], 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