perf: lazy img_np loading and chunked parse_into_bboxes for large PDFs (#14385)

## Summary

- **Lazy img_np loading**: `np.array(img)` is now deferred until the
first OCR text extraction is actually needed, avoiding unnecessary
memory allocation for pages that already have text.
- **Chunked parse_into_bboxes**: Large PDFs (>50 pages, configurable via
`PDF_PARSER_PAGE_BATCH_SIZE`) are processed in batches. Each chunk's
boxes are normalized with `_to_global_boxes` to produce globally
consistent page numbers and position tags.
- **DLA early init**: Move remote-client initialization before model
loading in `LayoutRecognizer.__init__` so `DEEPDOC_URL` (or legacy
`TENSORRT_DLA_SVR`) short-circuits unnecessary model download for parser
containers relying on remote inference.
- **Fix outline regression**: Restore `self.outlines =
extract_pdf_outlines(fnm)` in `parse_into_bboxes`; this was dropped
during refactoring and is required by downstream `remove_toc` and
metadata handling in `rag/flow/parser/parser.py`.

## Test plan

- [ ] Small PDF (<=50 pages): verify parse succeeds and `self.outlines`
is populated
- [ ] Large PDF (>50 pages): verify chunked processing produces globally
consistent page numbers
- [ ] With `DEEPDOC_URL` set: verify remote DLA client is used and local
model is not downloaded
- [ ] With legacy `TENSORRT_DLA_SVR` set: verify backward compatibility

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>

deepdoc/vision/layout_recognizer.py

@@ -46,6 +46,18 @@ class LayoutRecognizer(Recognizer):
     ]
 
     def __init__(self, domain):
+        self.garbage_layouts = ["footer", "header", "reference"]
+        self.client = None
+
+        dla_url = os.environ.get("DEEPDOC_URL") or os.environ.get("TENSORRT_DLA_SVR")
+        if dla_url:
+            from deepdoc.vision.dla_cli import DLAClient
+
+            self.client = DLAClient(dla_url)
+            env_used = "DEEPDOC_URL" if os.environ.get("DEEPDOC_URL") else "TENSORRT_DLA_SVR"
+            logging.info(f"LayoutRecognizer using remote DLA client at {dla_url} (via {env_used})")
+            return
+
         try:
             model_dir = os.path.join(get_project_base_directory(), "rag/res/deepdoc")
             super().__init__(self.labels, domain, model_dir)
@@ -53,13 +65,6 @@ class LayoutRecognizer(Recognizer):
             model_dir = snapshot_download(repo_id="InfiniFlow/deepdoc", local_dir=os.path.join(get_project_base_directory(), "rag/res/deepdoc"), local_dir_use_symlinks=False)
             super().__init__(self.labels, domain, model_dir)
 
-        self.garbage_layouts = ["footer", "header", "reference"]
-        self.client = None
-        if os.environ.get("TENSORRT_DLA_SVR"):
-            from deepdoc.vision.dla_cli import DLAClient
-
-            self.client = DLAClient(os.environ["TENSORRT_DLA_SVR"])
-
     def __call__(self, image_list, ocr_res, scale_factor=3, thr=0.2, batch_size=16, drop=True):
         def __is_garbage(b):
             patt = [r"\(cid\s*:\s*\d+\s*\)"]