feat(nodes): add ComicPageComposer (rect + bbox metadata)

Assembles per-panel IMAGE tensors onto full page canvases via compose_page,
emits panel_bboxes_json metadata, and passes the original panel stack through.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

tk_comfyui_batch_image/nodes/page_composer.py

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+"""ComicPageComposer — assemble panels into full page images."""
+from __future__ import annotations
+import json
+import numpy as np
+import torch
+
+from ..core.compositor import compose_page
+from ..core.types import COMIC_SCRIPT_TYPE, SolvedScript
+
+
+def _pil_to_tensor(img) -> np.ndarray:
+    return np.asarray(img.convert("RGB"), dtype=np.float32) / 255.0
+
+
+def _bboxes_metadata(script: SolvedScript) -> dict:
+    return {
+        "job_id": script.job_id,
+        "reading_direction": script.reading_direction,
+        "pages": [
+            {
+                "page_index": page.page_index,
+                "page_width": page.page_width,
+                "page_height": page.page_height,
+                "panels": [
+                    {
+                        "panel_index": panel.panel_index,
+                        "bbox_topleft": list(panel.bbox_topleft),
+                        "bbox_size":    list(panel.bbox_size),
+                        "shape_type":   panel.shape_type,
+                    } for panel in page.panels
+                ],
+            } for page in script.pages
+        ],
+    }
+
+
+class ComicPageComposer:
+    CATEGORY = "comic/io"
+    FUNCTION = "compose"
+    RETURN_TYPES = ("IMAGE", "STRING", "IMAGE")
+    RETURN_NAMES = ("composed_pages", "panel_bboxes_json", "individual_panels")
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "generated_panels": ("IMAGE",),
+                "comic_script":     (COMIC_SCRIPT_TYPE,),
+                "debug_overlay":    ("BOOLEAN", {"default": False}),
+            }
+        }
+
+    def compose(self, generated_panels: torch.Tensor, comic_script: SolvedScript,
+                debug_overlay: bool):
+        panels_np = generated_panels.cpu().numpy()   # (N, Hmax, Wmax, 3)
+
+        out_pages: list[np.ndarray] = []
+        idx = 0
+        for page in comic_script.pages:
+            panel_imgs: list[tuple] = []
+            for panel in page.panels:
+                raw = panels_np[idx]
+                w, h = panel.bbox_size
+                cropped = raw[:h, :w, :]   # matching what BatchGenerator placed (top-left of padding)
+                panel_imgs.append((panel, cropped))
+                idx += 1
+            pil = compose_page(page, panel_imgs)
+            out_pages.append(_pil_to_tensor(pil))
+
+        # Pad composed pages to same shape if sizes differ (M1: all same)
+        max_h = max(p.shape[0] for p in out_pages)
+        max_w = max(p.shape[1] for p in out_pages)
+        padded = [np.pad(p, ((0, max_h - p.shape[0]), (0, max_w - p.shape[1]), (0, 0)),
+                         constant_values=1.0) for p in out_pages]
+        pages_tensor = torch.from_numpy(np.stack(padded, axis=0)).float()
+
+        bboxes = json.dumps(_bboxes_metadata(comic_script), indent=2, ensure_ascii=False)
+        return pages_tensor, bboxes, generated_panels

tk_comfyui_batch_image/tests/test_page_composer.py

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+# tests/test_page_composer.py
+import json
+from pathlib import Path
+import numpy as np
+import torch
+from PIL import Image
+
+from tk_comfyui_batch_image.core.normalizer import normalize_script
+from tk_comfyui_batch_image.nodes.page_composer import ComicPageComposer
+
+FIXTURES = Path(__file__).parent / "fixtures" / "scripts"
+
+
+def _make_panel_stack(script) -> torch.Tensor:
+    """Produce a solid-colour IMAGE batch matching each panel's bbox_size."""
+    imgs = []
+    for page in script.pages:
+        for panel in page.panels:
+            w, h = panel.bbox_size
+            arr = np.full((h, w, 3), 0.5, dtype=np.float32)
+            imgs.append(arr)
+    # Pad to same H/W by placing each into a max-sized canvas
+    max_h = max(a.shape[0] for a in imgs)
+    max_w = max(a.shape[1] for a in imgs)
+    padded = [np.pad(a, ((0, max_h - a.shape[0]), (0, max_w - a.shape[1]), (0, 0)),
+                     constant_values=1.0) for a in imgs]
+    return torch.from_numpy(np.stack(padded, axis=0)).float()
+
+
+def test_compose_basic_script_yields_n_pages():
+    data = json.loads((FIXTURES / "basic.json").read_text(encoding="utf-8"))
+    script = normalize_script(data)
+    stack = _make_panel_stack(script)
+    pages, bboxes_json, pass_panels = ComicPageComposer().compose(
+        generated_panels=stack, comic_script=script, debug_overlay=False,
+    )
+    assert isinstance(pages, torch.Tensor)
+    assert pages.shape[0] == 2   # 2 pages
+    assert pages.shape[-1] == 3
+    assert pages.shape[1] == script.pages[0].page_height
+    assert pages.shape[2] == script.pages[0].page_width
+
+
+def test_bboxes_json_includes_all_panels():
+    data = json.loads((FIXTURES / "basic.json").read_text(encoding="utf-8"))
+    script = normalize_script(data)
+    stack = _make_panel_stack(script)
+    _, bboxes_json, _ = ComicPageComposer().compose(
+        generated_panels=stack, comic_script=script, debug_overlay=False,
+    )
+    parsed = json.loads(bboxes_json)
+    assert len(parsed["pages"]) == 2
+    assert len(parsed["pages"][0]["panels"]) == 3
+    p0 = parsed["pages"][0]["panels"][0]
+    assert "bbox_topleft" in p0 and "bbox_size" in p0
+
+
+def test_individual_panels_passthrough_preserves_order():
+    data = json.loads((FIXTURES / "basic.json").read_text(encoding="utf-8"))
+    script = normalize_script(data)
+    stack = _make_panel_stack(script)
+    _, _, pass_panels = ComicPageComposer().compose(
+        generated_panels=stack, comic_script=script, debug_overlay=False,
+    )
+    assert torch.equal(pass_panels, stack)