fix:t_recognizer TypeError: 'super' object is not callable (#4404)

### What problem does this PR solve?

[Bug]: layout recognizer failed for wrong boxes class type #4230
(https://github.com/infiniflow/ragflow/issues/4230)

### Type of change

- [✅ ] Bug Fix (non-breaking change which fixes an issue)

---------

Co-authored-by: youzhiqiang <zhiqiang.you@aminer.com>
Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>

deepdoc/vision/layout_recognizer.py

@@ -153,6 +153,8 @@ class LayoutRecognizer(Recognizer):
         ocr_res = [b for b in ocr_res if b["text"].strip() not in garbag_set]
         return ocr_res, page_layout
 
+    def forward(self, image_list, thr=0.7, batch_size=16):
+        return super().__call__(image_list, thr, batch_size)
 
 class LayoutRecognizer4YOLOv10(LayoutRecognizer):
     labels = [

deepdoc/vision/t_recognizer.py

@@ -23,7 +23,7 @@ sys.path.insert(
             '../../')))
 
 from deepdoc.vision.seeit import draw_box
-from deepdoc.vision import LayoutRecognizer, TableStructureRecognizer, OCR, init_in_out, Recognizer
+from deepdoc.vision import LayoutRecognizer, TableStructureRecognizer, OCR, init_in_out
 import argparse
 import re
 import numpy as np
@@ -33,9 +33,8 @@ def main(args):
     images, outputs = init_in_out(args)
     if args.mode.lower() == "layout":
         detr = LayoutRecognizer("layout")
-        layouts = super(Recognizer, detr)(images, thr=float(args.threshold))
+        layouts = detr.forward(images, thr=float(args.threshold))
     if args.mode.lower() == "tsr":
-        labels = TableStructureRecognizer.labels
         detr = TableStructureRecognizer()
         ocr = OCR()
         layouts = detr(images, thr=float(args.threshold))
@@ -50,7 +49,7 @@ def main(args):
                 "bbox": [t["x0"], t["top"], t["x1"], t["bottom"]],
                 "score": t["score"]
             } for t in lyt]
-        img = draw_box(images[i], lyt, labels, float(args.threshold))
+        img = draw_box(images[i], lyt, detr.labels, float(args.threshold))
         img.save(outputs[i], quality=95)
         logging.info("save result to: " + outputs[i])