docs(tests): drop dev-only debug note and dead .claude/ path from e2e test docstring

Resolves `AttributeError: 'DifferentialDiffusion' object has no attribute
'execute'` on older ComfyUI (<0.3.63) where the V3 schema migration has
not landed yet. The prior code called `.execute(model)[0]` directly,
breaking anyone still on the legacy `.apply(model)` API.

Introduce `modules/impact/utils.apply_differential_diffusion(model)`
which uses `hasattr` to pick the correct branch at runtime:
- `.execute` -> V3 classmethod (ComfyUI >= 0.3.63)
- `.apply`   -> legacy instance method (older)
- otherwise  -> AttributeError with upgrade guidance

Replace all 7 direct call sites (animatediff_nodes, core x2,
impact_pack x2, segs_nodes, segs_upscaler) with the helper. The
existing import guard in segs_upscaler is preserved; the helper's
deferred import means ImportError still propagates for very old
ComfyUI builds without `comfy_extras.nodes_differential_diffusion`.

Fixes GitHub issue #1177.

Also add an E2E test harness:
- docs/E2E_TEST_STRATEGY.md — isolated-launch workflow with
  --disable-all-custom-nodes + --whitelist-custom-nodes, Playwright
  smoke test, workflow execution via /prompt + /history + /view,
  verification criteria, operational notes.
- tests/e2e_dd_compat.py — reference test that runs SEGSDetailer
  with noise_mask_feather=20 on a real input image, asserting
  status==success and non-zero pixel delta between input and paste
  previews (proves the detailer loop and compat shim actually ran).

docs/E2E_TEST_STRATEGY.md

@@ -0,0 +1,433 @@
+# E2E Test Strategy
+
+End-to-end test strategy for ComfyUI Impact Pack, covering isolated server launch, baseline smoke verification, real workflow execution, and operational notes for reliable test runs.
+
+---
+
+## Table of Contents
+
+1. [Purpose & Scope](#purpose--scope)
+2. [Prerequisites](#prerequisites)
+3. [Server Launch](#server-launch)
+4. [Baseline Smoke Test](#baseline-smoke-test)
+5. [Workflow Execution E2E](#workflow-execution-e2e)
+6. [Verification Criteria](#verification-criteria)
+7. [Operational Notes](#operational-notes)
+8. [Extension Points](#extension-points)
+
+---
+
+## Purpose & Scope
+
+End-to-end (E2E) testing validates ComfyUI Impact Pack as it behaves in a real ComfyUI runtime, not only through unit-level assertions. The goal is to catch regressions that surface only when the full stack is loaded: server startup, node registration, REST API responses, frontend page loading, and actual workflow execution through the `/prompt` API.
+
+**Why isolated E2E**
+- A developer's ComfyUI installation typically has many custom nodes. Any one of them can fail to import, log warnings, bind frontend routes, or shadow Impact Pack behavior.
+- Running Impact Pack against a clean environment removes noise and produces reproducible results.
+- `--disable-all-custom-nodes` combined with `--whitelist-custom-nodes` isolates Impact Pack (and its companion subpack) from every other installed custom node while still letting them load normally.
+
+**What this strategy validates**
+- ComfyUI server starts successfully with Impact Pack and Impact Subpack loaded.
+- The frontend page is served and renders the ComfyUI application shell.
+- The `/object_info` REST endpoint returns the full node catalog for both packs.
+- A baseline count and a sample of expected node names are present, guarding against silent node-registration regressions.
+- Detailer workflows execute through the `/prompt` API and produce non-degenerate outputs, proving the full inference path (detector → SEGSDetailer → SEGSPaste) runs end to end.
+
+**Out of scope** (covered by [Extension Points](#extension-points))
+- UI-driven node creation and connection
+- Visual regression testing beyond pixel-delta sanity checks
+- Performance benchmarking
+
+---
+
+## Prerequisites
+
+### Environment
+
+| Component | Requirement |
+|-----------|-------------|
+| Python | >= 3.12 |
+| Playwright (Python) | >= 1.58.0 |
+| Chromium runtime | Installed via `playwright install chromium` |
+| ComfyUI repository | Checked out at the parent directory of `custom_nodes/comfyui-impact-pack` |
+| Impact Pack | Installed as a custom node (this repository) |
+| Impact Subpack | Installed as a custom node alongside Impact Pack (delivers Ultralytics / SAM node types) |
+
+### Directory Layout
+
+E2E tests assume the standard ComfyUI custom-node layout:
+
+```
+ComfyUI/
+├── main.py
+├── custom_nodes/
+│   ├── comfyui-impact-pack/      ← this repository
+│   └── comfyui-impact-subpack/   ← detector / SAM node provider
+└── ...
+```
+
+### Install Commands
+
+```bash
+# From the ComfyUI repository root
+pip install playwright
+playwright install chromium
+```
+
+Impact Pack's own Python dependencies are expected to be installed already (see `pyproject.toml` / `requirements.txt`). Impact Subpack contributes its own dependency list — install it with its documented procedure.
+
+### Model Assets
+
+Detailer-dependent workflows require model files on disk. Place them at the ComfyUI-relative paths below:
+
+| Path | Purpose |
+|------|---------|
+| `models/checkpoints/SD1.5/realcartoonPixar_v8.safetensors` | SD1.5 checkpoint used by `CheckpointLoaderSimple` (any compatible SD1.5 checkpoint works; adjust the workflow's `ckpt_name` accordingly) |
+| `models/ultralytics/bbox/face_yolov8m.pt` | Face bbox detector used by `UltralyticsDetectorProvider` |
+| `models/sams/sam_vit_b_01ec64.pth` | SAM weights used when a workflow includes `SAMLoader` |
+| `input/ComfyUI_00156_.png` | Portrait with a clearly visible face, used by `LoadImage` in the reference workflow |
+
+The Ultralytics and SAM node classes themselves ship with Impact Subpack — installing the subpack is the delivery vehicle for those node types, separate from the model weights above.
+
+Pure [baseline smoke](#baseline-smoke-test) testing does not need any of these assets; they are required only once a workflow hits a detector or loader node.
+
+---
+
+## Server Launch
+
+### Default Launch
+
+Launch an isolated ComfyUI instance with Impact Pack and Impact Subpack as the only active custom nodes. This is the default for every test beyond the pure smoke layer:
+
+```bash
+# Working directory: the ComfyUI repository root (parent of custom_nodes/)
+python main.py \
+    --disable-all-custom-nodes \
+    --whitelist-custom-nodes comfyui-impact-pack comfyui-impact-subpack \
+    --port 18188
+```
+
+Most detailer workflows depend on `UltralyticsDetectorProvider`, `SAMLoader`, and related detector/segmenter node types shipped by Impact Subpack. Running without the subpack leaves those node classes unregistered, and any workflow referencing them will fail at prompt validation.
+
+### Minimal Launch (smoke only)
+
+For the pure API smoke path — page load + `/object_info` inspection, no workflow execution — Impact Pack alone is sufficient:
+
+```bash
+python main.py \
+    --disable-all-custom-nodes \
+    --whitelist-custom-nodes comfyui-impact-pack \
+    --port 18188
+```
+
+This minimal launch is **insufficient for detection-dependent tests**. Use it only when the test consists of startup + `/object_info` inspection.
+
+### Flag Explanation
+
+| Flag | Purpose |
+|------|---------|
+| `--disable-all-custom-nodes` | Skip import of every custom node in `custom_nodes/`. Eliminates side effects from unrelated packs. |
+| `--whitelist-custom-nodes comfyui-impact-pack comfyui-impact-subpack` | Re-enable only the listed folder names. Accepts multiple values separated by spaces. |
+| `--port 18188` | Bind to a non-default port so the test server does not collide with a developer's regular ComfyUI instance on 8188. |
+
+### Expected Startup Log Markers
+
+After launch, the server log should include lines similar to:
+
+```
+### Loading: ComfyUI-Impact-Pack (V8.28.2)
+### Loading: ComfyUI-Impact-Subpack (V<version>)
+Skipping <other-custom-node> due to disable_all_custom_nodes and whitelist_custom_nodes
+...
+To see the GUI go to: http://127.0.0.1:18188
+```
+
+The `Skipping ...` lines confirm isolation: other custom nodes are present on disk but were not loaded. The final `To see the GUI ...` line confirms the server is ready to accept connections.
+
+---
+
+## Baseline Smoke Test
+
+The smoke test confirms that an isolated server serves both the frontend page and the node catalog. It is intentionally small and has no external dependencies beyond Playwright.
+
+### Script
+
+```python
+# e2e_smoke.py
+# Usage: python e2e_smoke.py
+# Preconditions:
+#   - ComfyUI is running at http://127.0.0.1:18188 with Impact Pack AND
+#     Impact Subpack whitelisted (default launch).
+#   - Playwright Python + chromium runtime are installed.
+
+from playwright.sync_api import sync_playwright
+
+BASE_URL = "http://127.0.0.1:18188"
+REQUIRED_SUBPACK_NODES = {
+    "UltralyticsDetectorProvider",
+    "SAMLoader",
+    "SAMDetectorCombined",
+    "SAMDetectorSegmented",
+}
+
+
+def main() -> None:
+    with sync_playwright() as p:
+        browser = p.chromium.launch(headless=True)
+        page = browser.new_context().new_page()
+
+        # 1. Frontend page loads
+        page.goto(f"{BASE_URL}/", wait_until="networkidle")
+        title = page.title()
+        assert "ComfyUI" in title, f"Unexpected page title: {title!r}"
+
+        # 2. /object_info returns the node catalog
+        resp = page.request.get(f"{BASE_URL}/object_info")
+        assert resp.status == 200, f"/object_info HTTP {resp.status}"
+        object_info = resp.json()
+
+        # 3. Impact Pack nodes are registered
+        impact_nodes = [name for name in object_info if name.startswith("Impact")]
+        assert len(impact_nodes) >= 85, (
+            f"Impact node count regression: got {len(impact_nodes)}, expected >= 85"
+        )
+
+        # 4. Impact Subpack nodes are registered
+        missing = REQUIRED_SUBPACK_NODES - set(object_info.keys())
+        assert not missing, f"Subpack nodes missing: {sorted(missing)}"
+
+        print(f"Title:        {title}")
+        print(f"Total nodes:  {len(object_info)}")
+        print(f"Impact nodes: {len(impact_nodes)}")
+        print(f"Sample:       {impact_nodes[:3]}")
+
+        browser.close()
+
+
+if __name__ == "__main__":
+    main()
+```
+
+### Expected Output
+
+Observed baseline against Impact Pack v8.28.2 + Impact Subpack on an isolated server (default launch with both packs whitelisted):
+
+```
+Title:        *Unsaved Workflow - ComfyUI
+Total nodes:  858
+Impact nodes: 87
+Sample:       ['ImpactSegsAndMask', 'ImpactSegsAndMaskForEach', 'ImpactFlattenMask']
+```
+
+Additional Subpack-contributed node names verified present: `UltralyticsDetectorProvider`, `SAMLoader`, `SAMDetectorCombined`, `SAMDetectorSegmented`.
+
+Exact values will drift as the codebase evolves; the assertions above validate the minimum contract, not literal equality.
+
+---
+
+## Workflow Execution E2E
+
+The baseline smoke test confirms node registration, but it does not exercise execution logic. Workflow execution E2E posts a concrete graph to `/prompt`, polls `/history/{prompt_id}` until completion, and downloads output artifacts from `/view` for inspection. This catches regressions in the inference path that are invisible to catalog-level checks.
+
+### API Pattern
+
+```
+POST /prompt              — submit {prompt, client_id}, receive {prompt_id}
+GET  /queue               — running + pending prompts (progress monitoring)
+GET  /history/{prompt_id} — status + outputs once execution completes
+GET  /view?filename=...   — download an individual output artifact (PNG, etc.)
+```
+
+Polling cadence of ~3s on `/history` is sufficient; the endpoint returns an empty object while the prompt is still in flight and populates fully on completion.
+
+### Flat Prompt Format
+
+The `/prompt` endpoint expects a **flat** graph: a dict keyed by node ID, where each value is `{class_type, inputs}`. Socket connections are expressed as two-element lists `[upstream_node_id, output_slot_index]`.
+
+```python
+PROMPT = {
+    "ckpt": {
+        "class_type": "CheckpointLoaderSimple",
+        "inputs": {"ckpt_name": "SD1.5/realcartoonPixar_v8.safetensors"},
+    },
+    "pos": {
+        "class_type": "CLIPTextEncode",
+        "inputs": {"clip": ["ckpt", 1], "text": "a detailed face, sharp focus"},
+    },
+    "img": {
+        "class_type": "LoadImage",
+        "inputs": {"image": "ComfyUI_00156_.png"},
+    },
+    "detector": {
+        "class_type": "UltralyticsDetectorProvider",
+        "inputs": {"model_name": "bbox/face_yolov8m.pt"},
+    },
+    "detail": {
+        "class_type": "SEGSDetailer",
+        "inputs": {
+            "image": ["img", 0],
+            "segs": ["bbox_segs", 0],
+            # ... sampler knobs elided ...
+            "noise_mask_feather": 20,   # non-zero triggers DifferentialDiffusion path
+        },
+    },
+}
+```
+
+### Pitfall: Subgraph Blueprints
+
+Workflow JSON exported from the ComfyUI UI may contain high-level blueprint nodes such as `workflow/Impact::MAKE_BASIC_PIPE`. These are template/subgraph references that the UI expands client-side; they are not valid `class_type` values for direct `/prompt` submission.
+
+For programmatic E2E, **flatten blueprints into their concrete constituent nodes** before posting. For example, a `MAKE_BASIC_PIPE` blueprint flattens into:
+
+```
+CheckpointLoaderSimple → (model, clip, vae)
+CLIPTextEncode          (positive prompt)
+CLIPTextEncode          (negative prompt)
+ToBasicPipe             (model, clip, vae, positive, negative)
+```
+
+The reference implementation below demonstrates this flattening.
+
+### Reference Implementation
+
+`tests/e2e_dd_compat.py` is a validated reference workflow covering the critical detailer path:
+
+```
+LoadImage
+    → UltralyticsDetectorProvider
+    → BboxDetectorSEGS
+    → SEGSDetailer(noise_mask_feather=20)   # activates DifferentialDiffusion compat
+    → SEGSPaste
+    → PreviewImage (paste output)
+    → PreviewImage (untouched input)
+```
+
+Pass criteria:
+- Submission returns HTTP 200 with a `prompt_id`.
+- `/history/{prompt_id}` eventually reports `status.status_str == "success"` with no `execution_error` messages.
+- Both expected `PreviewImage` outputs are present in `history[prompt_id].outputs`.
+- Input preview and paste preview have matching dimensions.
+- Paste preview has non-degenerate statistics (`std >= 1.0`).
+- Paste preview differs from input (`abs(mean_delta) >= 0.005` or `abs(std_delta) >= 0.005`) — equality would indicate the detailer path, and therefore the DifferentialDiffusion compat shim, was bypassed.
+
+Typical observed deltas for the reference image: `mean_delta ≈ 0.01`, `std_delta ≈ 0.03`. These are small because `SEGSPaste` only rewrites the cropped face region; the majority of the frame is untouched and subtracts out.
+
+---
+
+## Verification Criteria
+
+The smoke test is considered to PASS when **all** of the following hold:
+
+| # | Criterion | How to verify |
+|---|-----------|---------------|
+| 1 | Server startup log contains `Loading: ComfyUI-Impact-Pack` | Inspect server stdout / log tail |
+| 2 | Server startup log contains `Loading: ComfyUI-Impact-Subpack` (default launch) | Inspect server stdout / log tail |
+| 3 | Log contains `Skipping ... due to disable_all_custom_nodes and whitelist_custom_nodes` for at least one other custom node (when other nodes are installed) | Inspect server log |
+| 4 | `http://127.0.0.1:18188/` returns HTTP 200 and a page title containing `ComfyUI` | `page.goto(...)` + `page.title()` |
+| 5 | `GET /object_info` returns HTTP 200 with a JSON body | `page.request.get(...).status` and `.json()` |
+| 6 | `/object_info` contains at least 85 Impact-prefixed node names | Count keys where `name.startswith("Impact")` |
+| 7 | Required Subpack nodes present: `UltralyticsDetectorProvider`, `SAMLoader`, `SAMDetectorCombined`, `SAMDetectorSegmented` | Set membership against `object_info` keys |
+
+The baseline threshold of 85 was chosen below the observed value of 87 to tolerate minor refactors that rename or remove a handful of nodes without triggering a false failure. Raise the threshold deliberately when new nodes ship; lower it only with a reviewed explanation.
+
+For workflow execution tests, pass criteria are scenario-specific; see the per-test criteria listed alongside each reference implementation.
+
+---
+
+## Operational Notes
+
+### Cache Busting
+
+ComfyUI caches sampler outputs across runs when node inputs are identical. This can mask regressions — a workflow may appear to "pass" because it is replaying a cached success.
+
+| Strategy | When to use |
+|----------|-------------|
+| Per-run seed randomization (`seed = int(time.time()) & 0xFFFFFFFF`) | Default; cheapest invalidation for sampler-bearing nodes |
+| Full server restart | After changing Python source inside `modules/impact/` or loaded packages |
+| Clear `modules/impact/__pycache__/` | When `.pyc` files may be stale relative to edited `.py` files |
+
+When restarting the server, kill any prior instance first and confirm the port is free before relaunching:
+
+```bash
+pkill -9 -f 'python main.py'
+# wait a moment, then verify nothing is still listening on the test port
+curl -fsS http://127.0.0.1:18188/system_stats && echo "still up" || echo "port free"
+```
+
+Only relaunch once the probe reports the port is free. Launching while a dying process still holds the socket produces confusing `address already in use` errors downstream.
+
+### Verifying Internal Code Paths Executed
+
+Workflow-level pass criteria (`status_str == "success"`, no exception, non-zero pixel delta) prove the graph ran end to end. They do **not** prove that a specific internal function was reached. A bug that silently bypasses a compat shim can still return `success`.
+
+To confirm a specific branch executed, temporarily instrument the target:
+
+```python
+# modules/impact/utils.py  (temporary)
+import logging
+def apply_differential_diffusion(...):
+    logging.warning("[E2E-MARKER] apply_differential_diffusion:execute")
+    ...
+```
+
+Run the workflow, then grep the server log for the marker:
+
+```bash
+grep 'E2E-MARKER' /tmp/server.log
+```
+
+Absence of the marker despite `status_str == "success"` is a signal that the code path was skipped — typically because an upstream dispatch picked a different branch. Remove the marker before committing.
+
+### Log File Decoding
+
+Progress bars emitted by `tqdm` (used by samplers, detectors, SAM) write carriage returns (`\r`) rather than newlines, collapsing a long run onto a single physical line in the log file. Naive `grep` on that file may report only the final progress state.
+
+Normalize before grepping:
+
+```bash
+tr '\r' '\n' < /tmp/server.log | grep -F '[E2E-MARKER]'
+```
+
+Or in Python:
+
+```python
+with open("/tmp/server.log", "r", errors="replace") as f:
+    text = f.read().replace("\r", "\n")
+```
+
+---
+
+## Extension Points
+
+The smoke and reference workflow tests are the baseline verification layers. Future E2E scenarios should build on the same isolated-launch foundation:
+
+### Reference Test Implementation
+
+`tests/e2e_dd_compat.py` — validated workflow covering LoadImage → UltralyticsDetectorProvider → BboxDetectorSEGS → SEGSDetailer → SEGSPaste → PreviewImage. Demonstrates the full `/prompt` + `/history` + `/view` lifecycle and the pixel-delta assertion pattern. Treat it as the canonical template for new workflow-execution tests.
+
+### Additional Workflow Scenarios
+
+Beyond the detailer compat path, useful workflow-level tests include: FaceDetailer end-to-end (KSampler-generated face pipe), SEGSDetailer with `cycle > 1` (iterative refinement), MASK_TO_SEGS + SEGSPaste (mask-driven editing), and Impact Switch / Pipe nodes (control-flow regressions).
+
+### UI-Driven Node Creation
+
+Use Playwright to open the frontend, drag an Impact node from the node library onto the canvas, and connect inputs/outputs. Validates that frontend metadata (category, display name, input schema) stays synchronized with backend definitions.
+
+### Node Signature Regression Detection
+
+Snapshot the full `/object_info` payload for a known-good release, then diff against the current response. Flag any change in input type, input name, output type, or output count. Useful as a pre-release guard against accidental public API breakage.
+
+### Headed Mode for Debugging
+
+For interactive debugging, launch Playwright with `headless=False` and optionally `slow_mo=500`. Pair with `page.pause()` at the point of failure to inspect the live browser state.
+
+```python
+browser = p.chromium.launch(headless=False, slow_mo=500)
+# ... later ...
+page.pause()  # opens Playwright Inspector
+```
+
+### Cross-Browser Coverage
+
+Extend beyond chromium by parameterizing the browser launcher over `p.chromium`, `p.firefox`, and `p.webkit`. Impact Pack's frontend surface is thin, but cross-browser validation guards against regressions introduced by future frontend-facing features.

js/common.js

@@ -135,3 +135,147 @@ function refreshPreview(event) {
 }
 
 api.addEventListener("impact-preview", refreshPreview);
+
+
+// ============================================================================
+// MaskRectArea Shared Utilities
+// ============================================================================
+
+/**
+ * Reads a numeric value from a connected link by inspecting the origin node widget.
+ * More reliable than getInputData() in ComfyUI's frontend execution model.
+ *
+ * @param {LGraphNode} node - LiteGraph node instance
+ * @param {string} inputName - Name of the input to read
+ * @returns {number|null} The numeric value or null if not available
+ */
+export function readLinkedNumber(node, inputName) {
+    try {
+        if (!node || !node.graph || !Array.isArray(node.inputs)) {
+            return null;
+        }
+        const inp = node.inputs.find(i => i && i.name === inputName);
+        if (!inp || inp.link == null) {
+            return null;
+        }
+
+        const link = node.graph.links && node.graph.links[inp.link];
+        if (!link) {
+            return null;
+        }
+
+        const originNode = node.graph.getNodeById
+            ? node.graph.getNodeById(link.origin_id)
+            : null;
+        if (!originNode || !Array.isArray(originNode.widgets) || originNode.widgets.length === 0) {
+            return null;
+        }
+
+        const w = originNode.widgets.find(ww => ww && ww.name === "value")
+            || originNode.widgets[0];
+        const v = w ? w.value : null;
+
+        return (typeof v === "number") ? v : null;
+    } catch (e) {
+        return null;
+    }
+}
+
+/**
+ * Generates a color based on percentage using HSL color space.
+ *
+ * @param {number} percent - Value between 0 and 1
+ * @param {string} alpha - Hex alpha value (e.g., "ff", "80")
+ * @returns {string} Hex color string with alpha (e.g., "#ff8040ff")
+ */
+export function getDrawColor(percent, alpha) {
+    let h = 360 * percent;
+    let s = 50;
+    let l = 50;
+    l /= 100;
+    const a = s * Math.min(l, 1 - l) / 100;
+    const f = n => {
+        const k = (n + h / 30) % 12;
+        const color = l - a * Math.max(Math.min(k - 3, 9 - k, 1), -1);
+        return Math.round(255 * color).toString(16).padStart(2, '0');
+    };
+    return `#${f(0)}${f(8)}${f(4)}${alpha}`;
+}
+
+/**
+ * Computes and adjusts canvas size for preview widgets.
+ *
+ * @param {LGraphNode} node - LiteGraph node instance
+ * @param {[number, number]} size - [width, height] array
+ * @param {number} minHeight - Minimum canvas height (REQUIRED)
+ * @param {number} minWidth - Minimum canvas width (REQUIRED)
+ * @returns {void}
+ */
+export function computeCanvasSize(node, size, minHeight, minWidth) {
+    // Validate required parameters
+    if (typeof minHeight !== 'number' || typeof minWidth !== 'number') {
+        console.warn('[computeCanvasSize] minHeight and minWidth are required parameters');
+        return;
+    }
+
+    // Null safety check for widgets array
+    if (!node.widgets?.length || node.widgets[0].last_y == null) {
+        return;
+    }
+
+    // LiteGraph global availability check
+    const NODE_WIDGET_HEIGHT = (typeof LiteGraph !== 'undefined' && LiteGraph.NODE_WIDGET_HEIGHT)
+        ? LiteGraph.NODE_WIDGET_HEIGHT
+        : 20;
+
+    let y = node.widgets[0].last_y + 5;
+    let freeSpace = size[1] - y;
+
+    // Compute the height of all non-customCanvas widgets
+    let widgetHeight = 0;
+    for (let i = 0; i < node.widgets.length; i++) {
+        const w = node.widgets[i];
+        if (w.type !== "customCanvas") {
+            if (w.computeSize) {
+                widgetHeight += w.computeSize()[1] + 4;
+            } else {
+                widgetHeight += NODE_WIDGET_HEIGHT + 5;
+            }
+        }
+    }
+
+    // Ensure there is enough vertical space
+    freeSpace -= widgetHeight;
+
+    // Clamp minimum canvas height
+    if (freeSpace < minHeight) {
+        freeSpace = minHeight;
+    }
+
+    // Allow both grow and shrink to fit content
+    const targetHeight = y + widgetHeight + freeSpace;
+    if (node.size[1] !== targetHeight) {
+        node.size[1] = targetHeight;
+        node.graph.setDirtyCanvas(true);
+    }
+
+    // Ensure the node width meets the minimum width requirement
+    if (node.size[0] < minWidth) {
+        node.size[0] = minWidth;
+        node.graph.setDirtyCanvas(true);
+    }
+
+    // Position each of the widgets
+    for (const w of node.widgets) {
+        w.y = y;
+        if (w.type === "customCanvas") {
+            y += freeSpace;
+        } else if (w.computeSize) {
+            y += w.computeSize()[1] + 4;
+        } else {
+            y += NODE_WIDGET_HEIGHT + 4;
+        }
+    }
+
+    node.canvasHeight = freeSpace;
+}

js/mask-rect-area-advanced.js

@@ -1,4 +1,5 @@
 import { app } from "../../scripts/app.js";
+import { readLinkedNumber, getDrawColor, computeCanvasSize } from "./common.js";
 function showPreviewCanvas(node, app) {
 
     const widget = {
@@ -15,7 +16,7 @@ function showPreviewCanvas(node, app) {
             // If we are initially offscreen when created we wont have received a resize event
             // Calculate it here instead
             if (!node.canvasHeight) {
-                computeCanvasSize(node, node.size);
+                computeCanvasSize(node, node.size, 220, 240);
             }
 
             const visible = true;
@@ -23,9 +24,16 @@ function showPreviewCanvas(node, app) {
             const margin = 12;
             const border = 2;
             const widgetHeight = node.canvasHeight;
-            const width = Math.round(node.properties["width"]);
+
-            const height = Math.round(node.properties["height"]);
+            // Keep preview in sync when inputs are driven by links.
-            const scale = Math.min((widgetWidth - margin * 3) / width, (widgetHeight - margin * 3) / height);
+            syncLinkedInputsToPropertiesAdvanced(node);
+
+            const width = Math.max(1, Math.round(node.properties["width"]));
+            const height = Math.max(1, Math.round(node.properties["height"]));
+            const scale = Math.min(
+                    (widgetWidth - margin * 3) / width,
+                    (widgetHeight - margin * 3) / height
+                    );
             const blurRadius = node.properties["blur_radius"] || 0;
             const index = 0;
 
@@ -120,11 +128,11 @@ function showPreviewCanvas(node, app) {
                 xOffset += (widgetWidth - backgroundWidth) / 2 - margin;
             }
 
-            // Ajustar las coordenadas X e Y
+            // Adjust X and Y coordinates
             const barHeight = 8;
             let widgetYBar = widgetY + backgroundHeight + margin;
 
-            // Dibujar el borde negro alrededor de la barra
+            // Draw the border around the progress bar
             ctx.fillStyle = globalThis.LiteGraph.WIDGET_OUTLINE_COLOR;
             ctx.fillRect(
                     widgetX - border,
@@ -133,8 +141,8 @@ function showPreviewCanvas(node, app) {
                     barHeight + border * 2
                     );
 
-            // Dibujar el área principal de la barra (fondo)
+            // Draw the main bar area (background)
-            ctx.fillStyle = globalThis.LiteGraph.WIDGET_BGCOLOR; // Mismo color de fondo que el canvas
+            ctx.fillStyle = globalThis.LiteGraph.WIDGET_BGCOLOR;
             ctx.fillRect(
                     widgetX,
                     widgetYBar,
@@ -142,16 +150,15 @@ function showPreviewCanvas(node, app) {
                     barHeight
                     );
 
-
             // Draw progress bar grid
             ctx.beginPath();
             ctx.lineWidth = 1;
             ctx.strokeStyle = "#66666650";
 
-            // Calcular el número de líneas en función del tamaño de la barra
+            // Calculate the number of grid lines based on the bar size
             const numLines = Math.floor(backgroundWidth / 64);
 
-            // Dibujar líneas del grid
+            // Draw grid lines
             for (let x = 0; x <= width / 64; x += 1) {
                 ctx.moveTo(widgetX + x * 64 * scale, widgetYBar);
                 ctx.lineTo(widgetX + x * 64 * scale, widgetYBar + barHeight);
@@ -159,7 +166,7 @@ function showPreviewCanvas(node, app) {
             ctx.stroke();
             ctx.closePath();
 
-            // Dibujar progreso (basado en blur_radius)
+            // Draw progress (based on blur_radius)
             const progress = Math.min(blurRadius / 255, 1);
             ctx.fillStyle = "rgba(0, 120, 255, 0.5)";
 
@@ -176,6 +183,13 @@ function showPreviewCanvas(node, app) {
     widget.canvas.className = "mask-rect-area-canvas";
     widget.parent = node;
 
+    widget.computeLayoutSize = function (node) {
+        return {
+            minHeight: 200,
+            maxHeight: 300
+        };
+    };
+
     document.body.appendChild(widget.canvas);
     node.addCustomWidget(widget);
 
@@ -196,32 +210,92 @@ function showPreviewCanvas(node, app) {
     };
 
     node.onResize = function (size) {
-        computeCanvasSize(node, size);
+        computeCanvasSize(node, size, 220, 240);
     };
 
     return {minWidth: 200, minHeight: 200, widget};
 }
 
 app.registerExtension({
-    name: 'drltdata.MaskRectAreaAdvanced',
+    name: "drltdata.MaskRectAreaAdvanced",
     async beforeRegisterNodeDef(nodeType, nodeData, app) {
-        if (nodeData.name === "MaskRectAreaAdvanced") {
+        if (nodeData.name !== "MaskRectAreaAdvanced") {
-            const onNodeCreated = nodeType.prototype.onNodeCreated;
+            return;
-            nodeType.prototype.onNodeCreated = function () {
+        }
-                const r = onNodeCreated ? onNodeCreated.apply(this, arguments) : undefined;
 
-                this.setProperty("width", 512);
+        const onNodeCreated = nodeType.prototype.onNodeCreated;
-                this.setProperty("height", 512);
+        nodeType.prototype.onNodeCreated = function () {
-                this.setProperty("x", 0);
+            const r = onNodeCreated ? onNodeCreated.apply(this, arguments) : undefined;
-                this.setProperty("y", 0);
-                this.setProperty("w", 256);
-                this.setProperty("h", 256);
-                this.setProperty("blur_radius", 0);
 
-                this.selected = false;
+            this.setProperty("width", 512);
-                this.index = 3;
+            this.setProperty("height", 512);
-                this.serialize_widgets = true;
+            this.setProperty("x", 0);
+            this.setProperty("y", 0);
+            this.setProperty("w", 256);
+            this.setProperty("h", 256);
+            this.setProperty("blur_radius", 0);
 
+            this.selected = false;
+            this.index = 3;
+            this.serialize_widgets = true;
+
+            // If the node already provides widgets from Python/ComfyUI, do NOT recreate them
+            const hasExisting = Array.isArray(this.widgets) && this.widgets.some(w => w && w.name === "x");
+
+            // Helper: attach callbacks to existing widgets to keep node.properties in sync (canvas preview).
+            const hookWidget = (node, widgetName, propName, opts) => {
+                if (!Array.isArray(node.widgets)) {
+                    return;
+                }
+                const w = node.widgets.find(ww => ww && ww.name === widgetName);
+                if (!w) {
+                    return;
+                }
+
+                const min = (opts && typeof opts.min === "number") ? opts.min : undefined;
+                const max = (opts && typeof opts.max === "number") ? opts.max : undefined;
+                const step = (opts && typeof opts.step === "number") ? opts.step : undefined;
+
+                if (node.properties && Object.prototype.hasOwnProperty.call(node.properties, propName)) {
+                    w.value = node.properties[propName];
+                } else {
+                    node.properties[propName] = w.value;
+                }
+
+                const prevCb = w.callback;
+                w.callback = function (v, ...args) {
+                    let val = v;
+                    if (typeof val === "number") {
+                        if (typeof step === "number" && step > 0) {
+                            const s = step / 10;
+                            val = Math.round(val / s) * s;
+                        } else {
+                            val = Math.round(val);
+                        }
+                        if (typeof min === "number") {
+                            val = Math.max(min, val);
+                        }
+                        if (typeof max === "number") {
+                            val = Math.min(max, val);
+                        }
+                    }
+                    this.value = val;
+                    node.properties[propName] = val;
+                    if (prevCb) {
+                        return prevCb.call(this, val, ...args);
+                    }
+                };
+            };
+
+            if (hasExisting) {
+                hookWidget(this, "x", "x", {"step": 10});
+                hookWidget(this, "y", "y", {"step": 10});
+                hookWidget(this, "width", "w", {"step": 10});
+                hookWidget(this, "height", "h", {"step": 10});
+                hookWidget(this, "image_width", "width", {"step": 10});
+                hookWidget(this, "image_height", "height", {"step": 10});
+                hookWidget(this, "blur_radius", "blur_radius", {"min": 0, "max": 255, "step": 10});
+            } else {
                 CUSTOM_INT(this, "x", 0, function (v, _, node) {
                     const s = this.options.step / 10;
                     this.value = Math.round(v / s) * s;
@@ -258,19 +332,19 @@ app.registerExtension({
                 },
                         {"min": 0, "max": 255, "step": 10}
                 );
+            }
 
-                showPreviewCanvas(this, app);
+            showPreviewCanvas(this, app);
 
-                this.onSelected = function () {
+            this.onSelected = function () {
-                    this.selected = true;
+                this.selected = true;
-                };
-                this.onDeselected = function () {
-                    this.selected = false;
-                };
-
-                return r;
             };
-        }
+            this.onDeselected = function () {
+                this.selected = false;
+            };
+
+            return r;
+        };
     }
 });
 
@@ -311,71 +385,75 @@ function CUSTOM_INT(node, inputName, val, func, config = {}) {
     };
 }
 
-function getDrawColor(percent, alpha) {
+function syncLinkedInputsToPropertiesAdvanced(node) {
-    let h = 360 * percent;
+    let changed = false;
-    let s = 50;
-    let l = 50;
-    l /= 100;
-    const a = s * Math.min(l, 1 - l) / 100;
-    const f = n => {
-        const k = (n + h / 30) % 12;
-        const color = l - a * Math.max(Math.min(k - 3, 9 - k, 1), -1);
-        return Math.round(255 * color).toString(16).padStart(2, '0');   // convert to Hex and prefix "0" if needed
-    };
-    return `#${f(0)}${f(8)}${f(4)}${alpha}`;
-}
 
-function computeCanvasSize(node, size) {
+    const vx = readLinkedNumber(node, "x");
-    if (node.widgets[0].last_y == null) {
+    if (vx != null) {
-        return;
+        const nv = Math.max(0, Math.round(vx));
-    }
+        if (node.properties["x"] !== nv) {
-
+            node.properties["x"] = nv;
-    const MIN_HEIGHT = 220;
+            changed = true;
-    const MIN_WIDTH = 240;
-
-    let y = LiteGraph.NODE_WIDGET_HEIGHT * Math.max(node.inputs.length, node.outputs.length) + 5;
-    let freeSpace = size[1] - y;
-
-    // Compute the height of all non-customCanvas widgets
-    let widgetHeight = 0;
-    for (let i = 0; i < node.widgets.length; i++) {
-        const w = node.widgets[i];
-        if (w.type !== "customCanvas") {
-            if (w.computeSize) {
-                widgetHeight += w.computeSize()[1] + 4;
-            } else {
-                widgetHeight += LiteGraph.NODE_WIDGET_HEIGHT + 5;
-            }
         }
     }
 
-    // Ensure there is enough vertical space
+    const vy = readLinkedNumber(node, "y");
-    freeSpace -= widgetHeight;
+    if (vy != null) {
-
+        const nv = Math.max(0, Math.round(vy));
-    // Adjust the height of the node if needed
+        if (node.properties["y"] !== nv) {
-    if (freeSpace < MIN_HEIGHT) {
+            node.properties["y"] = nv;
-        freeSpace = MIN_HEIGHT;
+            changed = true;
-        node.size[1] = y + widgetHeight + freeSpace;
-        node.graph.setDirtyCanvas(true);
-    }
-
-    // Ensure the node width meets the minimum width requirement
-    if (node.size[0] < MIN_WIDTH) {
-        node.size[0] = MIN_WIDTH;
-        node.graph.setDirtyCanvas(true);
-    }
-
-    // Position each of the widgets
-    for (const w of node.widgets) {
-        w.y = y;
-        if (w.type === "customCanvas") {
-            y += freeSpace;
-        } else if (w.computeSize) {
-            y += w.computeSize()[1] + 4;
-        } else {
-            y += LiteGraph.NODE_WIDGET_HEIGHT + 4;
         }
     }
 
-    node.canvasHeight = freeSpace;
+    // Input "width" is the rectangle width in px -> property "w"
+    const vw = readLinkedNumber(node, "width");
+    if (vw != null) {
+        const nv = Math.max(0, Math.round(vw));
+        if (node.properties["w"] !== nv) {
+            node.properties["w"] = nv;
+            changed = true;
+        }
+    }
+
+    // Input "height" is the rectangle height in px -> property "h"
+    const vh = readLinkedNumber(node, "height");
+    if (vh != null) {
+        const nv = Math.max(0, Math.round(vh));
+        if (node.properties["h"] !== nv) {
+            node.properties["h"] = nv;
+            changed = true;
+        }
+    }
+
+    // Image size (must be >=1 to avoid division by zero in getDrawArea)
+    const viw = readLinkedNumber(node, "image_width");
+    if (viw != null) {
+        const nv = Math.max(1, Math.round(viw));
+        if (node.properties["width"] !== nv) {
+            node.properties["width"] = nv;
+            changed = true;
+        }
+    }
+
+    const vih = readLinkedNumber(node, "image_height");
+    if (vih != null) {
+        const nv = Math.max(1, Math.round(vih));
+        if (node.properties["height"] !== nv) {
+            node.properties["height"] = nv;
+            changed = true;
+        }
+    }
+
+    const vbr = readLinkedNumber(node, "blur_radius");
+    if (vbr != null) {
+        const nv = Math.max(0, Math.min(255, Math.round(vbr)));
+        if (node.properties["blur_radius"] !== nv) {
+            node.properties["blur_radius"] = nv;
+            changed = true;
+        }
+    }
+
+    return changed;
 }
+

js/mask-rect-area.js

@@ -1,4 +1,5 @@
 import { app } from "../../scripts/app.js";
+import { readLinkedNumber, getDrawColor, computeCanvasSize } from "./common.js";
 function showPreviewCanvas(node, app) {
 
     const widget = {
@@ -15,7 +16,7 @@ function showPreviewCanvas(node, app) {
             // If we are initially offscreen when created we wont have received a resize event
             // Calculate it here instead
             if (!node.canvasHeight) {
-                computeCanvasSize(node, node.size);
+                computeCanvasSize(node, node.size, 200, 200);
             }
 
             const visible = true;
@@ -64,6 +65,9 @@ function showPreviewCanvas(node, app) {
             ctx.fillStyle = globalThis.LiteGraph.WIDGET_BGCOLOR;
             ctx.fillRect(widgetX, widgetY, backgroundWidth, backgroundHeight);
 
+            // Keep preview in sync when inputs are driven by links.
+            syncLinkedInputsToProperties(node);
+
             // Draw the conditioning zone
             let [x, y, w, h] = getDrawArea(node, backgroundWidth, backgroundHeight);
 
@@ -100,7 +104,6 @@ function showPreviewCanvas(node, app) {
             ctx.strokeStyle = globalThis.LiteGraph.NODE_SELECTED_TITLE_COLOR;
             ctx.lineWidth = 2;
             ctx.strokeRect(widgetX + sx, widgetY + sy, sw, sh);
-            //ctx.strokeRect(finalSX, finalSY, finalSW, finalSH);
 
             // Display
             ctx.beginPath();
@@ -173,6 +176,13 @@ function showPreviewCanvas(node, app) {
     widget.canvas.className = "mask-rect-area-canvas";
     widget.parent = node;
 
+    widget.computeLayoutSize = function (node) {
+        return {
+            minHeight: 200,
+            maxHeight: 300
+        };
+    };
+
     document.body.appendChild(widget.canvas);
     node.addCustomWidget(widget);
 
@@ -193,7 +203,7 @@ function showPreviewCanvas(node, app) {
     };
 
     node.onResize = function (size) {
-        computeCanvasSize(node, size);
+        computeCanvasSize(node, size, 200, 200);
     };
 
     return {minWidth: 200, minHeight: 200, widget};
@@ -202,25 +212,82 @@ function showPreviewCanvas(node, app) {
 app.registerExtension({
     name: 'drltdata.MaskRectArea',
     async beforeRegisterNodeDef(nodeType, nodeData, app) {
-        if (nodeData.name === "MaskRectArea") {
+        if (nodeData.name !== "MaskRectArea") {
-            const onNodeCreated = nodeType.prototype.onNodeCreated;
+            return;
-            nodeType.prototype.onNodeCreated = function () {
+        }
-                const r = onNodeCreated ? onNodeCreated.apply(this, arguments) : undefined;
 
-                this.setProperty("width", 512);
+        const onNodeCreated = nodeType.prototype.onNodeCreated;
-                this.setProperty("height", 512);
+        nodeType.prototype.onNodeCreated = function () {
-                this.setProperty("x", 0);
+            const r = onNodeCreated ? onNodeCreated.apply(this, arguments) : undefined;
-                this.setProperty("y", 0);
-                this.setProperty("w", 50);
-                this.setProperty("h", 50);
-                this.setProperty("blur_radius", 0);
 
-                this.selected = false;
+            this.setProperty("width", 512);
-                this.index = 3;
+            this.setProperty("height", 512);
-                this.serialize_widgets = true;
+            this.setProperty("x", 0);
+            this.setProperty("y", 0);
+            this.setProperty("w", 50);
+            this.setProperty("h", 50);
+            this.setProperty("blur_radius", 0);
 
+            this.selected = false;
+            this.index = 3;
+            this.serialize_widgets = true;
+
+            // If Python/ComfyUI already created typed widgets, do not recreate them (avoid duplicates).
+            const hasExisting = Array.isArray(this.widgets) && this.widgets.some(w => w && w.name === "x");
+
+            // Hook existing widgets to keep node.properties in sync (canvas uses properties).
+            const hookWidget = (node, widgetName, propName, opts) => {
+                if (!Array.isArray(node.widgets)) {
+                    return;
+                }
+                const w = node.widgets.find(ww => ww && ww.name === widgetName);
+                if (!w) {
+                    return;
+                }
+
+                const min = (opts && typeof opts.min === "number") ? opts.min : undefined;
+                const max = (opts && typeof opts.max === "number") ? opts.max : undefined;
+
+                if (node.properties && Object.prototype.hasOwnProperty.call(node.properties, propName)) {
+                    w.value = node.properties[propName];
+                } else {
+                    node.properties[propName] = w.value;
+                }
+
+                const prevCb = w.callback;
+                w.callback = function (v, ...args) {
+                    let val = v;
+
+                    if (typeof val === "number") {
+                        val = Math.round(val);
+
+                        if (typeof min === "number") {
+                            val = Math.max(min, val);
+                        }
+                        if (typeof max === "number") {
+                            val = Math.min(max, val);
+                        }
+                    }
+
+                    this.value = val;
+                    node.properties[propName] = val;
+
+                    if (prevCb) {
+                        return prevCb.call(this, val, ...args);
+                    }
+                };
+            };
+
+            if (hasExisting) {
+                // Note: "width"/"height" widgets map to "w"/"h" properties (percent-based).
+                hookWidget(this, "x", "x", {"min": 0, "max": 100});
+                hookWidget(this, "y", "y", {"min": 0, "max": 100});
+                hookWidget(this, "width", "w", {"min": 0, "max": 100});
+                hookWidget(this, "height", "h", {"min": 0, "max": 100});
+                hookWidget(this, "blur_radius", "blur_radius", {"min": 0, "max": 255});
+            } else {
                 CUSTOM_INT(this, "x", 0, function (v, _, node) {
-                    this.value = Math.max(0, Math.min(100, Math.round(v))); // Limitar entre 0 y 100
+                    this.value = Math.max(0, Math.min(100, Math.round(v)));
                     node.properties["x"] = this.value;
                 });
                 CUSTOM_INT(this, "y", 0, function (v, _, node) {
@@ -238,25 +305,104 @@ app.registerExtension({
                 CUSTOM_INT(this, "blur_radius", 0, function (v, _, node) {
                     this.value = Math.round(v) || 0;
                     node.properties["blur_radius"] = this.value;
-                },
+                }, {"min": 0, "max": 255, "step": 10});
-                        {"min": 0, "max": 255, "step": 10}
-                );
 
-                showPreviewCanvas(this, app);
+                // If Python widgets exist, they will be used instead; this is back-compat only.
+            }
 
-                this.onSelected = function () {
+            showPreviewCanvas(this, app);
-                    this.selected = true;
+
-                };
+            // Sync linked input values -> node.properties so the preview updates when driven by connections.
-                this.onDeselected = function () {
+            const prevOnExecute = this.onExecute;
-                    this.selected = false;
+            this.onExecute = function () {
+                const rr = prevOnExecute ? prevOnExecute.apply(this, arguments) : undefined;
+
+                const readLinkedInt = (inputName) => {
+                    if (!Array.isArray(this.inputs)) {
+                        return null;
+                    }
+                    const inp = this.inputs.find(i => i && i.name === inputName);
+                    if (!inp || !inp.link) {
+                        return null;
+                    }
+                    try {
+                        const v = this.getInputData(inputName);
+                        return (typeof v === "number") ? v : null;
+                    } catch (e) {
+                        return null;
+                    }
                 };
 
-                return r;
+                let changed = false;
+
+                const vx = readLinkedInt("x");
+                if (vx != null) {
+                    const nv = Math.max(0, Math.min(100, Math.round(vx)));
+                    if (this.properties["x"] !== nv) {
+                        this.properties["x"] = nv;
+                        changed = true;
+                    }
+                }
+
+                const vy = readLinkedInt("y");
+                if (vy != null) {
+                    const nv = Math.max(0, Math.min(100, Math.round(vy)));
+                    if (this.properties["y"] !== nv) {
+                        this.properties["y"] = nv;
+                        changed = true;
+                    }
+                }
+
+                const vw = readLinkedInt("width");
+                if (vw != null) {
+                    const nv = Math.max(0, Math.min(100, Math.round(vw)));
+                    if (this.properties["w"] !== nv) {
+                        this.properties["w"] = nv;
+                        changed = true;
+                    }
+                }
+
+                const vh = readLinkedInt("height");
+                if (vh != null) {
+                    const nv = Math.max(0, Math.min(100, Math.round(vh)));
+                    if (this.properties["h"] !== nv) {
+                        this.properties["h"] = nv;
+                        changed = true;
+                    }
+                }
+
+                const vbr = readLinkedInt("blur_radius");
+                if (vbr != null) {
+                    const nv = Math.max(0, Math.min(255, Math.round(vbr)));
+                    if (this.properties["blur_radius"] !== nv) {
+                        this.properties["blur_radius"] = nv;
+                        changed = true;
+                    }
+                }
+
+                if (changed) {
+                    this.setDirtyCanvas(true, true);
+                    if (this.graph) {
+                        this.graph.setDirtyCanvas(true, true);
+                    }
+                }
+
+                return rr;
             };
-        }
+
+            this.onSelected = function () {
+                this.selected = true;
+            };
+            this.onDeselected = function () {
+                this.selected = false;
+            };
+
+            return r;
+        };
     }
 });
 
+
 // Calculate the drawing area using percentage-based properties.
 function getDrawArea(node, backgroundWidth, backgroundHeight) {
     // Convert percentages to actual pixel values based on the background dimensions
@@ -296,71 +442,53 @@ function CUSTOM_INT(node, inputName, val, func, config = {}) {
     };
 }
 
-function getDrawColor(percent, alpha) {
+function syncLinkedInputsToProperties(node) {
-    let h = 360 * percent;
+    let changed = false;
-    let s = 50;
-    let l = 50;
-    l /= 100;
-    const a = s * Math.min(l, 1 - l) / 100;
-    const f = n => {
-        const k = (n + h / 30) % 12;
-        const color = l - a * Math.max(Math.min(k - 3, 9 - k, 1), -1);
-        return Math.round(255 * color).toString(16).padStart(2, '0');   // convert to Hex and prefix "0" if needed
-    };
-    return `#${f(0)}${f(8)}${f(4)}${alpha}`;
-}
 
-function computeCanvasSize(node, size) {
+    const vx = readLinkedNumber(node, "x");
-    if (node.widgets[0].last_y == null) {
+    if (vx != null) {
-        return;
+        const nv = Math.max(0, Math.min(100, Math.round(vx)));
-    }
+        if (node.properties["x"] !== nv) {
-
+            node.properties["x"] = nv;
-    const MIN_HEIGHT = 200;
+            changed = true;
-    const MIN_WIDTH = 200;
-
-    let y = LiteGraph.NODE_WIDGET_HEIGHT * Math.max(node.inputs.length, node.outputs.length) + 5;
-    let freeSpace = size[1] - y;
-
-    // Compute the height of all non-customCanvas widgets
-    let widgetHeight = 0;
-    for (let i = 0; i < node.widgets.length; i++) {
-        const w = node.widgets[i];
-        if (w.type !== "customCanvas") {
-            if (w.computeSize) {
-                widgetHeight += w.computeSize()[1] + 4;
-            } else {
-                widgetHeight += LiteGraph.NODE_WIDGET_HEIGHT + 5;
-            }
         }
     }
 
-    // Ensure there is enough vertical space
+    const vy = readLinkedNumber(node, "y");
-    freeSpace -= widgetHeight;
+    if (vy != null) {
-
+        const nv = Math.max(0, Math.min(100, Math.round(vy)));
-    // Adjust the height of the node if needed
+        if (node.properties["y"] !== nv) {
-    if (freeSpace < MIN_HEIGHT) {
+            node.properties["y"] = nv;
-        freeSpace = MIN_HEIGHT;
+            changed = true;
-        node.size[1] = y + widgetHeight + freeSpace;
-        node.graph.setDirtyCanvas(true);
-    }
-
-    // Ensure the node width meets the minimum width requirement
-    if (node.size[0] < MIN_WIDTH) {
-        node.size[0] = MIN_WIDTH;
-        node.graph.setDirtyCanvas(true);
-    }
-
-    // Position each of the widgets
-    for (const w of node.widgets) {
-        w.y = y;
-        if (w.type === "customCanvas") {
-            y += freeSpace;
-        } else if (w.computeSize) {
-            y += w.computeSize()[1] + 4;
-        } else {
-            y += LiteGraph.NODE_WIDGET_HEIGHT + 4;
         }
     }
 
-    node.canvasHeight = freeSpace;
+    const vw = readLinkedNumber(node, "width");
+    if (vw != null) {
+        const nv = Math.max(0, Math.min(100, Math.round(vw)));
+        if (node.properties["w"] !== nv) {
+            node.properties["w"] = nv;
+            changed = true;
+        }
+    }
+
+    const vh = readLinkedNumber(node, "height");
+    if (vh != null) {
+        const nv = Math.max(0, Math.min(100, Math.round(vh)));
+        if (node.properties["h"] !== nv) {
+            node.properties["h"] = nv;
+            changed = true;
+        }
+    }
+
+    const vbr = readLinkedNumber(node, "blur_radius");
+    if (vbr != null) {
+        const nv = Math.max(0, Math.min(255, Math.round(vbr)));
+        if (node.properties["blur_radius"] !== nv) {
+            node.properties["blur_radius"] = nv;
+            changed = true;
+        }
+    }
+
+    return changed;
 }

modules/impact/animatediff_nodes.py

@@ -66,7 +66,7 @@ class SEGSDetailerForAnimateDiff:
         cnet_image_list = []
 
         if not (isinstance(model, str) and model == "DUMMY") and noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
-            model = nodes_differential_diffusion.DifferentialDiffusion().execute(model)[0]
+            model = utils.apply_differential_diffusion(model)
 
         for seg in segs[1]:
             cropped_image_frames = None

modules/impact/config.py

@@ -2,7 +2,7 @@ import configparser
 import logging
 import os
 
-version_code = [8, 28]
+version_code = [8, 28, 3]
 version = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
 
 my_path = os.path.dirname(__file__)

modules/impact/core.py

@@ -262,7 +262,7 @@ def enhance_detail(image, model, clip, vae, guide_size, guide_size_for_bbox, max
         noise_mask = noise_mask.squeeze(3)
 
         if noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
-            model = nodes_differential_diffusion.DifferentialDiffusion().execute(model)[0]
+            model = utils.apply_differential_diffusion(model)
 
     if wildcard_opt is not None and wildcard_opt != "":
         model, _, wildcard_positive = wildcards.process_with_loras(wildcard_opt, model, clip)
@@ -435,7 +435,7 @@ def enhance_detail_for_animatediff(image_frames, model, clip, vae, guide_size, g
         noise_mask = noise_mask.squeeze(3)
 
     if noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
-        model = nodes_differential_diffusion.DifferentialDiffusion().execute(model)[0]
+        model = utils.apply_differential_diffusion(model)
 
     if wildcard_opt is not None and wildcard_opt != "":
         model, _, wildcard_positive = wildcards.process_with_loras(wildcard_opt, model, clip)

modules/impact/impact_pack.py

@@ -301,7 +301,7 @@ class DetailerForEach:
             ordered_segs = segs[1]
 
         if not (isinstance(model, str) and model == "DUMMY") and noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
-            model = nodes_differential_diffusion.DifferentialDiffusion().execute(model)[0]
+            model = utils.apply_differential_diffusion(model)
 
         for i, seg in enumerate(ordered_segs):
             cropped_image = utils.crop_ndarray4(image.cpu().numpy(), seg.crop_region)  # Never use seg.cropped_image to handle overlapping area
@@ -518,7 +518,7 @@ class DetailerForEachAutoRetry:
             ordered_segs = segs[1]
 
         if not (isinstance(model, str) and model == "DUMMY") and noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
-            model = nodes_differential_diffusion.DifferentialDiffusion().execute(model)[0]
+            model = utils.apply_differential_diffusion(model)
 
         for i, seg in enumerate(ordered_segs):
             cropped_image = utils.crop_ndarray4(image.cpu().numpy(), seg.crop_region)  # Never use seg.cropped_image to handle overlapping area
@@ -2157,6 +2157,12 @@ class MaskRectArea:
     def INPUT_TYPES(cls):
         return {
             "required": {
+                # Added typed INT inputs so this node can be driven by other INT nodes.
+                "x": ("INT", {"default": 0, "min": 0, "max": 100, "step": 1}),
+                "y": ("INT", {"default": 0, "min": 0, "max": 100, "step": 1}),
+                "width": ("INT", {"default": 50, "min": 0, "max": 100, "step": 1}),
+                "height": ("INT", {"default": 50, "min": 0, "max": 100, "step": 1}),
+                "blur_radius": ("INT", {"default": 0, "min": 0, "step": 1})
             },
             "hidden": {"extra_pnginfo": "EXTRA_PNGINFO", "unique_id": "UNIQUE_ID"}
         }
@@ -2166,34 +2172,68 @@ class MaskRectArea:
     CATEGORY = "ImpactPack/Operation"
     FUNCTION = "create_mask"
 
-    def create_mask(self, extra_pnginfo, unique_id, **kwargs):
+    def create_mask(self, x, y, width, height, blur_radius, extra_pnginfo, unique_id):
-        # search for node
+        # Backward-compat: if node properties exist in workflow, prefer them.
-        node_found = False
+        try:
-        for node in extra_pnginfo["workflow"]["nodes"]:
+            for node in extra_pnginfo["workflow"]["nodes"]:
-            if str(node["id"]) == unique_id:
+                if str(node["id"]) == str(unique_id):
-                min_x = node["properties"].get("x", 0) / 100
+                    props = node.get("properties", {})
-                min_y = node["properties"].get("y", 0) / 100
+                    x = int(props.get("x", x))
-                width = node["properties"].get("w", 0) / 100
+                    y = int(props.get("y", y))
-                height = node["properties"].get("h", 0) / 100
+                    width = int(props.get("w", width))
-                blur_radius = node["properties"].get("blur_radius", 0)
+                    height = int(props.get("h", height))
-                node_found = True
+                    blur_radius = int(props.get("blur_radius", blur_radius))
-                break
+                    break
+        except Exception:
+            pass
 
-        if not node_found:
+        # Clamp percent inputs
-            raise ValueError(f"No node found with unique_id {unique_id}.")
+        if x < 0:
+            x = 0
+        if y < 0:
+            y = 0
+        if width < 0:
+            width = 0
+        if height < 0:
+            height = 0
+        if x > 100:
+            x = 100
+        if y > 100:
+            y = 100
+        if width > 100:
+            width = 100
+        if height > 100:
+            height = 100
+
+        # Convert percent to ratio
+        min_x = x / 100.0
+        min_y = y / 100.0
+        w_ratio = width / 100.0
+        h_ratio = height / 100.0
 
         # Create a mask with standard resolution (e.g., 512x512)
         resolution = 512
-        mask = torch.zeros((resolution, resolution))
+        mask = torch.zeros((resolution, resolution), dtype=torch.float32)
 
         # Calculate pixel coordinates
         min_x_px = int(min_x * resolution)
         min_y_px = int(min_y * resolution)
-        max_x_px = int((min_x + width) * resolution)
+        max_x_px = int((min_x + w_ratio) * resolution)
-        max_y_px = int((min_y + height) * resolution)
+        max_y_px = int((min_y + h_ratio) * resolution)
+
+        # Clamp pixel bounds
+        if min_x_px < 0:
+            min_x_px = 0
+        if min_y_px < 0:
+            min_y_px = 0
+        if max_x_px > resolution:
+            max_x_px = resolution
+        if max_y_px > resolution:
+            max_y_px = resolution
 
         # Draw the rectangle on the mask
-        mask[min_y_px:max_y_px, min_x_px:max_x_px] = 1
+        if max_x_px > min_x_px and max_y_px > min_y_px:
+            mask[min_y_px:max_y_px, min_x_px:max_x_px] = 1.0
 
         # Apply blur if the radii are greater than 0
         if blur_radius > 0:
@@ -2222,6 +2262,13 @@ class MaskRectAreaAdvanced:
     def INPUT_TYPES(cls):
         return {
             "required": {
+                "x": ("INT", {"default": 0, "min": 0, "step": 1}),
+                "y": ("INT", {"default": 0, "min": 0, "step": 1}),
+                "width": ("INT", {"default": 256, "min": 0, "step": 1}),
+                "height": ("INT", {"default": 320, "min": 0, "step": 1}),
+                "image_width": ("INT", {"default": 512, "min": 1, "step": 1}),
+                "image_height": ("INT", {"default": 320, "min": 1, "step": 1}),
+                "blur_radius": ("INT", {"default": 0, "min": 0, "step": 1})
             },
             "hidden": {"extra_pnginfo": "EXTRA_PNGINFO", "unique_id": "UNIQUE_ID"}
         }
@@ -2231,46 +2278,50 @@ class MaskRectAreaAdvanced:
     CATEGORY = "ImpactPack/Operation"
     FUNCTION = "create_mask_advanced"
 
-    def create_mask_advanced(self, extra_pnginfo, unique_id, **kwargs):
+    def create_mask_advanced(self, x, y, width, height, image_width, image_height, blur_radius, extra_pnginfo, unique_id):
-        # search for node
+        # Backward-compat fallback: if node properties exist in workflow, prefer them
-        node_found = False
+        try:
-        for node in extra_pnginfo["workflow"]["nodes"]:
+            for node in extra_pnginfo["workflow"]["nodes"]:
-            if node["id"] == int(unique_id):
+                if node["id"] == int(unique_id):
-                min_x = node["properties"]["x"]
+                    props = node.get("properties", {})
-                min_y = node["properties"]["y"]
+                    x = int(props.get("x", x))
-                width = node["properties"]["w"]
+                    y = int(props.get("y", y))
-                height = node["properties"]["h"]
+                    width = int(props.get("w", width))
-                image_width = node["properties"]["width"]
+                    height = int(props.get("h", height))
-                image_height = node["properties"]["height"]
+                    image_width = int(props.get("width", image_width))
-                blur_radius = node["properties"]["blur_radius"]
+                    image_height = int(props.get("height", image_height))
-                node_found = True
+                    blur_radius = int(props.get("blur_radius", blur_radius))
-                break
+                    break
+        except Exception:
+            pass
 
-        if not node_found:
+        # Clamp to safe bounds
-            raise ValueError(f"No node found with unique_id {unique_id}.")
+        if image_width < 1:
+            image_width = 1
+        if image_height < 1:
+            image_height = 1
+        if width < 0:
+            width = 0
+        if height < 0:
+            height = 0
+        if x < 0:
+            x = 0
+        if y < 0:
+            y = 0
 
-        # Calculate maximum coordinates
+        max_x = min(x + width, image_width)
-        max_x = min_x + width
+        max_y = min(y + height, image_height)
-        max_y = min_y + height
 
-        # Create a mask with the image dimensions
+        mask = torch.zeros((image_height, image_width), dtype=torch.float32)
-        mask = torch.zeros((image_height, image_width))
 
-        # Draw the rectangle on the mask
+        if max_x > x and max_y > y:
-        mask[int(min_y):int(max_y), int(min_x):int(max_x)] = 1
+            mask[y:max_y, x:max_x] = 1.0
 
         # Apply blur if the radii are greater than 0
         if blur_radius > 0:
-            dx = blur_radius * 2 + 1
+            k = blur_radius * 2 + 1
-            dy = blur_radius * 2 + 1
-
-            # Convert the mask to a format compatible with OpenCV (numpy array)
             mask_np = mask.cpu().numpy().astype("float32")
-
+            blurred_mask = cv2.GaussianBlur(mask_np, (k, k), 0)
-            # Apply Gaussian Blur
-            blurred_mask = cv2.GaussianBlur(mask_np, (dx, dy), 0)
-
-            # Convert back to tensor
             mask = torch.from_numpy(blurred_mask)
 
         # Return the mask as a tensor with an additional channel

modules/impact/segs_nodes.py

@@ -86,7 +86,7 @@ class SEGSDetailer:
         cnet_pil_list = []
 
         if not (isinstance(model, str) and model == "DUMMY") and noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
-            model = nodes_differential_diffusion.DifferentialDiffusion().execute(model)[0]
+            model = utils.apply_differential_diffusion(model)
 
         for i in range(batch_size):
             seed += 1

modules/impact/segs_upscaler.py

@@ -102,7 +102,7 @@ def img2img_segs(image, model, clip, vae, seed, steps, cfg, sampler_name, schedu
         noise_mask = noise_mask.squeeze(3)
 
         if noise_mask_feather > 0 and 'denoise_mask_function' not in model.model_options:
-            model = nodes_differential_diffusion.DifferentialDiffusion().execute(model)[0]
+            model = utils.apply_differential_diffusion(model)
 
     if control_net_wrapper is not None:
         positive, negative, _ = control_net_wrapper.apply(positive, negative, image, noise_mask)

modules/impact/utils.py

@@ -690,6 +690,22 @@ def try_install_custom_node(custom_node_url, msg):
         logging.info("[Impact Pack] ComfyUI-Manager is outdated. The custom node installation feature is not available.")
 
 
+def apply_differential_diffusion(model):
+    # ComfyUI ≥0.3.63 exposes V3 schema (classmethod `execute`); older versions use instance method `apply`.
+    # Import is deferred so callers with guarded imports (e.g. segs_upscaler.py) still work when the
+    # comfy_extras module is absent on very old ComfyUI — the ImportError propagates as before.
+    from comfy_extras import nodes_differential_diffusion
+    dd = nodes_differential_diffusion.DifferentialDiffusion()
+    if hasattr(dd, 'execute'):
+        return dd.execute(model)[0]
+    if hasattr(dd, 'apply'):
+        return dd.apply(model)[0]
+    raise AttributeError(
+        "DifferentialDiffusion has neither 'execute' nor 'apply'. "
+        "Update ComfyUI (≥0.3.63 for V3) or reinstall Impact Pack."
+    )
+
+
 # author: Trung0246 --->
 class TautologyStr(str):
     def __ne__(self, other):

pyproject.toml

@@ -1,9 +1,20 @@
 [project]
 name = "comfyui-impact-pack"
 description = "This node pack offers various detector nodes and detailer nodes that allow you to configure a workflow that automatically enhances facial details. And provide iterative upscaler."
-version = "8.28"
+version = "8.28.3"
 license = { file = "LICENSE.txt" }
-dependencies = ["segment-anything", "scikit-image", "piexif", "transformers", "opencv-python-headless", "GitPython", "scipy>=1.11.4"]
+dependencies = [
+    "segment-anything",
+    "scikit-image",
+    "piexif",
+    "transformers",
+    "opencv-python-headless",
+    "scipy",
+    "numpy",
+    "dill",
+    "matplotlib",
+    "sam2 @ git+https://github.com/facebookresearch/sam2"
+]
 
 [project.urls]
 Repository = "https://github.com/ltdrdata/ComfyUI-Impact-Pack"

tests/e2e_dd_compat.py

@@ -0,0 +1,260 @@
+"""E2E test for the DifferentialDiffusion cross-version compat shim.
+
+Exercises the `utils.apply_differential_diffusion` helper end-to-end through
+a real SEGSDetailer inference with `noise_mask_feather > 0`. This is the
+smallest graph that deterministically triggers the helper without relying on
+FaceDetailer's KSampler-generated face pipeline.
+
+Prerequisites:
+- ComfyUI running on http://127.0.0.1:18188 with impact-pack AND
+  impact-subpack whitelisted:
+    python main.py --disable-all-custom-nodes \
+        --whitelist-custom-nodes comfyui-impact-pack comfyui-impact-subpack \
+        --port 18188
+- Models available:
+    models/checkpoints/SD1.5/realcartoonPixar_v8.safetensors
+    models/ultralytics/bbox/face_yolov8m.pt
+- Input image with a visible face at input/ComfyUI_00156_.png
+- Python Playwright 1.58+ (`pip install playwright && playwright install chromium`)
+
+What it verifies:
+1. SEGSDetailer inference runs without AttributeError on DifferentialDiffusion.
+2. Output image differs slightly from input (detailer actually edited the face).
+3. Execution returns status=success.
+"""
+from playwright.sync_api import sync_playwright
+import json
+import time
+import sys
+import urllib.parse
+
+BASE_URL = "http://127.0.0.1:18188"
+TIMEOUT_S = 600
+
+_SEED = int(time.time()) & 0xFFFFFFFF
+
+PROMPT = {
+    "ckpt": {
+        "class_type": "CheckpointLoaderSimple",
+        "inputs": {"ckpt_name": "SD1.5/realcartoonPixar_v8.safetensors"},
+    },
+    "pos": {
+        "class_type": "CLIPTextEncode",
+        "inputs": {"clip": ["ckpt", 1], "text": "a detailed face, high quality, sharp focus"},
+    },
+    "neg": {
+        "class_type": "CLIPTextEncode",
+        "inputs": {"clip": ["ckpt", 1], "text": "blurry, low quality"},
+    },
+    "pipe": {
+        "class_type": "ToBasicPipe",
+        "inputs": {
+            "model": ["ckpt", 0],
+            "clip": ["ckpt", 1],
+            "vae": ["ckpt", 2],
+            "positive": ["pos", 0],
+            "negative": ["neg", 0],
+        },
+    },
+    "img": {
+        "class_type": "LoadImage",
+        "inputs": {"image": "ComfyUI_00156_.png"},
+    },
+    "detector": {
+        "class_type": "UltralyticsDetectorProvider",
+        "inputs": {"model_name": "bbox/face_yolov8m.pt"},
+    },
+    "bbox_segs": {
+        "class_type": "BboxDetectorSEGS",
+        "inputs": {
+            "bbox_detector": ["detector", 0],
+            "image": ["img", 0],
+            "threshold": 0.30,
+            "dilation": 10,
+            "crop_factor": 3.0,
+            "drop_size": 10,
+            "labels": "all",
+        },
+    },
+    # Non-zero noise_mask_feather is the critical knob — this is what
+    # activates the DifferentialDiffusion path inside enhance_detail and
+    # SEGSDetailer.do_detail.
+    "detail": {
+        "class_type": "SEGSDetailer",
+        "inputs": {
+            "image": ["img", 0],
+            "segs": ["bbox_segs", 0],
+            "guide_size": 512,
+            "guide_size_for": True,
+            "max_size": 1024,
+            "seed": _SEED,
+            "steps": 10,
+            "cfg": 7.0,
+            "sampler_name": "euler",
+            "scheduler": "normal",
+            "denoise": 0.5,
+            "noise_mask": True,
+            "force_inpaint": True,
+            "basic_pipe": ["pipe", 0],
+            "refiner_ratio": 0.2,
+            "batch_size": 1,
+            "cycle": 1,
+            "noise_mask_feather": 20,
+        },
+    },
+    "paste": {
+        "class_type": "SEGSPaste",
+        "inputs": {
+            "image": ["img", 0],
+            "segs": ["detail", 0],
+            "feather": 5,
+            "alpha": 255,
+        },
+    },
+    "preview_paste": {
+        "class_type": "PreviewImage",
+        "inputs": {"images": ["paste", 0]},
+    },
+    "preview_input": {
+        "class_type": "PreviewImage",
+        "inputs": {"images": ["img", 0]},
+    },
+}
+
+
+def fail(msg: str, code: int = 1) -> None:
+    print(f"FAIL: {msg}")
+    sys.exit(code)
+
+
+def main() -> None:
+    with sync_playwright() as p:
+        browser = p.chromium.launch(headless=True)
+        ctx = browser.new_context(viewport={"width": 1280, "height": 800})
+        page = ctx.new_page()
+        page.goto(f"{BASE_URL}/", wait_until="domcontentloaded", timeout=30000)
+
+        submit = page.evaluate(
+            """async (prompt) => {
+                const client_id = (window.api && window.api.clientId) || crypto.randomUUID();
+                const resp = await fetch('/prompt', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ prompt, client_id })
+                });
+                const text = await resp.text();
+                let parsed = null; try { parsed = JSON.parse(text); } catch {}
+                return { status: resp.status, body: parsed || text };
+            }""",
+            PROMPT,
+        )
+        if submit.get("status") != 200 or not isinstance(submit.get("body"), dict):
+            fail(f"submission failed: {submit}", 2)
+        prompt_id = submit["body"].get("prompt_id")
+        if not prompt_id:
+            fail("no prompt_id returned", 2)
+        print(f"prompt_id: {prompt_id}")
+
+        deadline = time.time() + TIMEOUT_S
+        last_sig = None
+        history_entry = None
+        while time.time() < deadline:
+            state = page.evaluate(
+                f"""async () => {{
+                    const h = await fetch('/history/{prompt_id}').then(r => r.json());
+                    const q = await fetch('/queue').then(r => r.json());
+                    return {{ h, q }};
+                }}"""
+            )
+            q = state["q"]
+            sig = f"running={len(q.get('queue_running', []))} pending={len(q.get('queue_pending', []))}"
+            if sig != last_sig:
+                print(f"[{int(TIMEOUT_S - (deadline - time.time())):>3}s] {sig}")
+                last_sig = sig
+            if prompt_id in state["h"]:
+                history_entry = state["h"][prompt_id]
+                break
+            time.sleep(3)
+        if history_entry is None:
+            fail(f"prompt did not complete within {TIMEOUT_S}s", 2)
+
+        status = history_entry.get("status", {})
+        messages = status.get("messages", [])
+        status_str = status.get("status_str")
+        print(f"status_str: {status_str}")
+
+        exec_errors = [m[1] for m in messages if m[0] == "execution_error"]
+        for err in exec_errors:
+            print(f"[ERROR] node={err.get('node_id')} {err.get('exception_type')}: {err.get('exception_message')}")
+            for t in err.get("traceback", [])[-5:]:
+                print(f"    {t.strip()}")
+        if exec_errors:
+            fail("execution_error present (DD compat shim or unrelated)", 1)
+        if status_str != "success":
+            fail(f"status_str={status_str!r}")
+
+        outputs = history_entry.get("outputs", {})
+        if "preview_input" not in outputs or "preview_paste" not in outputs:
+            fail(f"expected previews missing from outputs: {list(outputs)}")
+
+        def fetch_png_stats(meta):
+            qs = urllib.parse.urlencode(
+                {
+                    "filename": meta.get("filename", ""),
+                    "subfolder": meta.get("subfolder", ""),
+                    "type": meta.get("type", "output"),
+                }
+            )
+            raw_list = page.evaluate(
+                f"""async () => {{
+                    const r = await fetch('/view?{qs}');
+                    if (!r.ok) return null;
+                    const ab = await r.arrayBuffer();
+                    return Array.from(new Uint8Array(ab));
+                }}"""
+            )
+            if not raw_list:
+                return None
+            import io as _io
+            import numpy as np
+            from PIL import Image as PILImage
+
+            pim = PILImage.open(_io.BytesIO(bytes(raw_list)))
+            arr = np.array(pim)
+            return {
+                "size": pim.size,
+                "mean": float(arr.mean()),
+                "std": float(arr.std()),
+            }
+
+        in_stats = fetch_png_stats(outputs["preview_input"]["images"][0])
+        out_stats = fetch_png_stats(outputs["preview_paste"]["images"][0])
+        if in_stats is None or out_stats is None:
+            fail("could not fetch one or both preview images")
+
+        print(f"input : {in_stats}")
+        print(f"paste : {out_stats}")
+
+        if out_stats["std"] < 1.0:
+            fail("paste output is degenerate (flat image)")
+
+        if in_stats["size"] != out_stats["size"]:
+            fail(f"size mismatch: {in_stats['size']} vs {out_stats['size']}")
+
+        # SEGSPaste with a detailed face should produce a slightly different mean/std
+        # vs the untouched input. Exact equality would indicate the detailer path
+        # (and thus the DD compat shim) was bypassed.
+        mean_delta = abs(out_stats["mean"] - in_stats["mean"])
+        std_delta = abs(out_stats["std"] - in_stats["std"])
+        if mean_delta < 0.005 and std_delta < 0.005:
+            fail(
+                f"output identical to input (mean_delta={mean_delta:.4f}, "
+                f"std_delta={std_delta:.4f}) — detailer likely didn't run"
+            )
+
+        print(f"PASS: detailer ran, mean_delta={mean_delta:.4f}, std_delta={std_delta:.4f}")
+        browser.close()
+
+
+if __name__ == "__main__":
+    main()