Add preview downscale and mid-frequency stabilizer

Introduces a 'preview_downscale' option to cap output image size for reduced RAM usage in mg_cade25_easy.py. Adds mid-frequency stabilizer controls to mg_cade25.py for improved hand/object stability at high resolution. Updates README with new module notes and workflow documentation, and revises mg_Easy-Workflow.json for node order and structure.

README.md

@@ -100,7 +100,7 @@ I strongly recommend use `mg_Easy-Workflow` workflow + default settings + your m
 Start with `MG_SuperSimple` for the easiest path:
 1. Drop `MG_SuperSimple` into the graph
 2. Connect `model / positive / negative / vae / latent` and a `Load ControlNet Model` module
-3. Choose `step_count` (2/3/4) and Run
+3. Choose `step_count` (3/4) and Run
 
 or load `mg_SuperSimple-Workflow` in panel ComfyUI
 
@@ -145,6 +145,11 @@ Notes:
 
 15) The 4th step sometimes saves the image for a long time, just wait for the end of the process, it depends on the initial resolution you set.
 
+16) The `CombiNode` node is optional, you can replace it with standard ComfyUI pipelines.
+
+<br></br>
+<details>
+<summary>Repository Layout</summary>
 
 ## Repository Layout
 ```
@@ -180,7 +185,7 @@ MagicNodes/
 │  ├─ mg_combinode.py
 │  ├─ mg_latent_adapter.py
 │  ├─ mg_sagpu_attention.py
-│  └─  mg_seed_latent.py
+│  └─ mg_seed_latent.py
 │  
 ├─ pressets/
 │  ├─ mg_cade25.cfg
@@ -191,7 +196,7 @@ MagicNodes/
 │  └─ check_sageattention.ps1
 │ 
 ├─ depth-anything/              # place Depth Anything v2 weights (.pth), e.g., depth_anything_v2_vitl.pth
-│  └─depth_anything_v2_vitl.pth
+│  └─ depth_anything_v2_vitl.pth
 │ 
 ├─ vendor/
 │  └─ depth_anything_v2/        # vendored Depth Anything v2 code (Apache-2.0)
@@ -203,20 +208,11 @@ MagicNodes/
 └─ requirements.txt
 ```
 
-Depth models (Depth Anything v2)
-- Place DA v2 weights (`.pth`) in `depth-anything/`. Recommended: `depth_anything_v2_vitl.pth` (ViT-L). Supported names include:
-  `depth_anything_v2_vits.pth`, `depth_anything_v2_vitb.pth`, `depth_anything_v2_vitl.pth`, `depth_anything_v2_vitg.pth`,
-  and the metric variants `depth_anything_v2_metric_vkitti_vitl.pth`, `depth_anything_v2_metric_hypersim_vitl.pth`.
-- ControlFusion auto-detects the correct config from the filename and uses this path by default. You can override via the
-  `depth_model_path` parameter (preset) if needed.
-- If no weights are found, ControlFusion falls back gracefully (luminance pseudo-depth), but results are better with DA v2.
-- Where to get weights: see the official Depth Anything v2 repository (https://github.com/DepthAnything/Depth-Anything-V2)
-  and its Hugging Face models page (https://huggingface.co/Depth-Anything) for pre-trained `.pth` files.
-
-
-## Documentation
-- Easy nodes overview and `MG_SuperSimple`: `docs/EasyNodes.md`
-- Hard nodes documentation index: `docs/HardNodes.md`
+</details>
+<br></br>
+<details>
+<summary> Module Notes and Guides</summary>
+<p>A compact set of per‑module notes, knobs, and usage tips covering Control Fusion, CADE 2.5, MG_CleanUp, and the experimental Magic Latent Adapter.</p>
 
 ## Control Fusion (mg_controlfusion.py, mg_controlfusion_easy.py,)
 - Builds depth + edge masks with preserved aspect ratio; hires-friendly mask mode
@@ -231,6 +227,7 @@ Depth models (Depth Anything v2)
   - Smooth start via `polish_start_after` and `polish_keep_low_ramp`
 - `eps_scale` supported for gentle exposure shaping
 
+
 ## MG_CleanUp (final memory cleanup node)
 
 - Purpose: a tiny end-of-graph node that aggressively frees RAM/VRAM and asks the OS to return freed pages. Place it at the very end of a workflow (ideally right after SaveImage).
@@ -255,6 +252,16 @@ Notes:
 ## Depth Anything v2 (vendor)
 - Lives under `vendor/depth_anything_v2`; Apache-2.0 license
 
+Depth models (Depth Anything v2)
+- Place DA v2 weights (`.pth`) in `depth-anything/`. Recommended: `depth_anything_v2_vitl.pth` (ViT-L). Supported names include:
+  `depth_anything_v2_vits.pth`, `depth_anything_v2_vitb.pth`, `depth_anything_v2_vitl.pth`, `depth_anything_v2_vitg.pth`,
+  and the metric variants `depth_anything_v2_metric_vkitti_vitl.pth`, `depth_anything_v2_metric_hypersim_vitl.pth`.
+- ControlFusion auto-detects the correct config from the filename and uses this path by default. You can override via the
+  `depth_model_path` parameter (preset) if needed.
+- If no weights are found, ControlFusion falls back gracefully (luminance pseudo-depth), but results are better with DA v2.
+- Where to get weights: see the official Depth Anything v2 repository (https://github.com/DepthAnything/Depth-Anything-V2)
+  and its Hugging Face models page (https://huggingface.co/Depth-Anything) for pre-trained `.pth` files.
+
 ## MG_ZeSmartSampler (Experimental)
 - Custom sampler that builds hybrid sigma schedules (Karras/Beta blend) with tail smoothing
 - Inputs/Outputs match KSampler: `MODEL/SEED/STEPS/CFG/base_sampler/schedule/CONDITIONING/LATENT` -> `LATENT`
@@ -280,6 +287,13 @@ Notes:
 - Usage: place before CADE/your sampler. In `generate` mode you can also enable image mixing via VAE; in `adapt` mode feed any upstream `LATENT` and the current `MODEL`. A simple family switch (`auto / SD / SDXL / FLUX`) controls stride fallback when VAE isn’t provided.
 - Notes: quality with FLUX/Qwen models also depends on using the proper text encoders/conditioning nodes for those families; this adapter only solves latent shapes, not conditioning mismatches.
 
+</details>
+<br></br>
+
+## Documentation
+- Easy nodes overview and `MG_SuperSimple`: `docs/EasyNodes.md`
+- Hard nodes documentation index: `docs/HardNodes.md`
+
 ## Dependencies (Why These Packages)
 - transformers — used by CADE for CLIPSeg (CIDAS/clipseg-rd64-refined) to build text‑driven masks (e.g., face/hands). If missing, CLIPSeg is disabled gracefully.
  

mod/easy/mg_cade25_easy.py

@@ -1998,6 +1998,8 @@ class ComfyAdaptiveDetailEnhancer25:
                 "clipseg_blend": (["fuse", "replace", "intersect"], {"default": "fuse", "tooltip": "How to combine CLIPSeg with ONNX mask."}),
                 "clipseg_ref_gate": ("BOOLEAN", {"default": False, "tooltip": "If reference provided, boost mask when far from reference (CLIP-Vision)."}),
                 "clipseg_ref_threshold": ("FLOAT", {"default": 0.03, "min": 0.0, "max": 0.2, "step": 0.001}),
+                # Preview/output image cap (helps RAM during save/preview)
+                "preview_downscale": ("BOOLEAN", {"default": True, "tooltip": "Cap final IMAGE to max 1920 on the longer side to reduce RAM spike during save/preview. Disable for full-res output."}),
                 # Under-the-hood saving (disabled by default to avoid duplicate saves)
                 "auto_save": ("BOOLEAN", {"default": False, "tooltip": "Save final IMAGE directly from CADE (uses low PNG compress to reduce RAM)."}),
                 "save_prefix": ("STRING", {"default": "ComfyUI", "multiline": False}),
@@ -2040,9 +2042,10 @@ class ComfyAdaptiveDetailEnhancer25:
                      clipseg_enable=False, clipseg_text="", clipseg_preview=224,
                      clipseg_threshold=0.40, clipseg_blur=7.0, clipseg_dilate=4,
                      clipseg_gain=1.0, clipseg_blend="fuse", clipseg_ref_gate=False, clipseg_ref_threshold=0.03,
-                    polish_enable=False, polish_keep_low=0.4, polish_edge_lock=0.2, polish_sigma=1.0,
-                   polish_start_after=1, polish_keep_low_ramp=0.2,
-                    auto_save=False, save_prefix="ComfyUI", save_compress=1,
+                     polish_enable=False, polish_keep_low=0.4, polish_edge_lock=0.2, polish_sigma=1.0,
+                    polish_start_after=1, polish_keep_low_ramp=0.2,
+                     preview_downscale=False,
+                     auto_save=False, save_prefix="ComfyUI", save_compress=1,
                      preset_step="Step 1", custom_override=False):
         # Cooperative cancel before any heavy work
         model_management.throw_exception_if_processing_interrupted()
@@ -3015,17 +3018,19 @@ class ComfyAdaptiveDetailEnhancer25:
             pass
 
         # Under-the-hood preview downscale for UI/output IMAGE to cap RAM during save/preview
+        preview_downscale = False  # hard-coded default (can be toggled here if needed)
         try:
-            B, H, W, C = image.shape
-            max_side = max(int(H), int(W))
-            cap = 4096
-            if max_side > cap:
-                scale = float(cap) / float(max_side)
-                nh = max(1, int(round(H * scale)))
-                nw = max(1, int(round(W * scale)))
-                x = image.movedim(-1, 1)
-                x = F.interpolate(x, size=(nh, nw), mode='bilinear', align_corners=False)
-                image = x.movedim(1, -1).clamp(0, 1).to(dtype=image.dtype)
+            if bool(preview_downscale):
+                B, H, W, C = image.shape
+                max_side = max(int(H), int(W))
+                cap = 1920
+                if max_side > cap:
+                    scale = float(cap) / float(max_side)
+                    nh = max(1, int(round(H * scale)))
+                    nw = max(1, int(round(W * scale)))
+                    x = image.movedim(-1, 1)
+                    x = F.interpolate(x, size=(nh, nw), mode='bilinear', align_corners=False)
+                    image = x.movedim(1, -1).clamp(0, 1).to(dtype=image.dtype)
         except Exception:
             pass
 

mod/hard/mg_cade25.py

@@ -1498,6 +1498,12 @@ class ComfyAdaptiveDetailEnhancer25:
                 "fdg_low_max": ("FLOAT", {"default": 0.70, "min": 0.0, "max": 2.0, "step": 0.01, "tooltip": "Upper bound for adaptive fdg_low."}),
                 "fdg_ema_beta": ("FLOAT", {"default": 0.80, "min": 0.0, "max": 0.99, "step": 0.01, "tooltip": "EMA smoothing for spectral ratio (higher = smoother)."}),
 
+                # Mid-frequency stabilizer (hands/objects scale)
+                "midfreq_enable": ("BOOLEAN", {"default": True, "tooltip": "Enable mid-frequency stabilizer (band-pass) to keep hands/objects stable at hi-res."}),
+                "midfreq_gain": ("FLOAT", {"default": 0.65, "min": 0.0, "max": 2.0, "step": 0.01, "tooltip": "Blend amount of mid-frequency band added on top of FDG guidance (0..2)."}),
+                "midfreq_sigma_lo": ("FLOAT", {"default": 0.55, "min": 0.05, "max": 2.0, "step": 0.01, "tooltip": "Lower Gaussian sigma for band split (controls smaller forms)."}),
+                "midfreq_sigma_hi": ("FLOAT", {"default": 1.30, "min": 0.10, "max": 3.0, "step": 0.01, "tooltip": "Upper Gaussian sigma for band split (controls larger forms)."}),
+
                 # ONNX local guidance and keypoints removed
 
                 # Muse Blend global directional post-mix
@@ -1555,6 +1561,7 @@ class ComfyAdaptiveDetailEnhancer25:
                      fdg_low=0.6, fdg_high=1.3, fdg_sigma=1.0, ze_res_zero_steps=2,
                      ze_adaptive=False, ze_r_switch_hi=0.60, ze_r_switch_lo=0.45,
                      fdg_low_adaptive=False, fdg_low_min=0.45, fdg_low_max=0.70, fdg_ema_beta=0.80,
+                     midfreq_enable=True, midfreq_gain=0.65, midfreq_sigma_lo=0.55, midfreq_sigma_hi=1.30,
                      muse_blend=False, muse_blend_strength=0.5,
                      eps_scale_enable=False, eps_scale=0.005,
                      clipseg_enable=False, clipseg_text="", clipseg_preview=224,
@@ -1706,7 +1713,7 @@ class ComfyAdaptiveDetailEnhancer25:
                       model, guidance_mode, rescale_multiplier, momentum_beta, cfg_curve, perp_damp,
                       use_zero_init=bool(use_zero_init), zero_init_steps=int(zero_init_steps),
                       fdg_low=float(fdg_low), fdg_high=float(fdg_high), fdg_sigma=float(fdg_sigma),
-                      midfreq_enable=bool(False), midfreq_gain=float(0.0), midfreq_sigma_lo=float(0.8), midfreq_sigma_hi=float(2.0),
+                      midfreq_enable=bool(midfreq_enable), midfreq_gain=float(midfreq_gain), midfreq_sigma_lo=float(midfreq_sigma_lo), midfreq_sigma_hi=float(midfreq_sigma_hi),
                       ze_zero_steps=int(ze_res_zero_steps),
                       ze_adaptive=bool(ze_adaptive), ze_r_switch_hi=float(ze_r_switch_hi), ze_r_switch_lo=float(ze_r_switch_lo),
                       fdg_low_adaptive=bool(fdg_low_adaptive), fdg_low_min=float(fdg_low_min), fdg_low_max=float(fdg_low_max), fdg_ema_beta=float(fdg_ema_beta),

workflows/mg_Easy-Workflow.json

@@ -1 +1 @@
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S&R":"PreviewImage"},"widgets_values":[]},{"id":7,"type":"SaveImage","pos":[2796.435012229308,813.9383242288463],"size":[645.60324992196,715.7559184038435],"flags":{},"order":36,"mode":0,"inputs":[{"localized_name":"images","name":"images","type":"IMAGE","link":48},{"localized_name":"filename_prefix","name":"filename_prefix","type":"STRING","widget":{"name":"filename_prefix"},"link":null}],"outputs":[],"properties":{},"widgets_values":["ComfyUI"]},{"id":26,"type":"PreviewImage","pos":[2402.088511427638,-384.4257289383634],"size":[204.34144162678967,246],"flags":{},"order":32,"mode":0,"inputs":[{"localized_name":"images","name":"images","type":"IMAGE","link":41}],"outputs":[],"properties":{"Node name for 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