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Fix t_recognizer.py after model updating. (#4330)
### What problem does this PR solve? #4230 ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)
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@ -23,8 +23,7 @@ sys.path.insert(
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'../../')))
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'../../')))
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from deepdoc.vision.seeit import draw_box
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from deepdoc.vision.seeit import draw_box
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from deepdoc.vision import Recognizer, LayoutRecognizer, TableStructureRecognizer, OCR, init_in_out
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from deepdoc.vision import LayoutRecognizer, TableStructureRecognizer, OCR, init_in_out
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from api.utils.file_utils import get_project_base_directory
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import argparse
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import argparse
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import re
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import re
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import numpy as np
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import numpy as np
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@ -33,13 +32,7 @@ import numpy as np
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def main(args):
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def main(args):
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images, outputs = init_in_out(args)
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images, outputs = init_in_out(args)
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if args.mode.lower() == "layout":
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if args.mode.lower() == "layout":
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labels = LayoutRecognizer.labels
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detr = LayoutRecognizer("layout")
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detr = Recognizer(
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labels,
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"layout",
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os.path.join(
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get_project_base_directory(),
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"rag/res/deepdoc/"))
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if args.mode.lower() == "tsr":
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if args.mode.lower() == "tsr":
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labels = TableStructureRecognizer.labels
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labels = TableStructureRecognizer.labels
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detr = TableStructureRecognizer()
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detr = TableStructureRecognizer()
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@ -64,7 +57,7 @@ def main(args):
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def get_table_html(img, tb_cpns, ocr):
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def get_table_html(img, tb_cpns, ocr):
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boxes = ocr(np.array(img))
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boxes = ocr(np.array(img))
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boxes = Recognizer.sort_Y_firstly(
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boxes = LayoutRecognizer.sort_Y_firstly(
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[{"x0": b[0][0], "x1": b[1][0],
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[{"x0": b[0][0], "x1": b[1][0],
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"top": b[0][1], "text": t[0],
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"top": b[0][1], "text": t[0],
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"bottom": b[-1][1],
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"bottom": b[-1][1],
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@ -75,26 +68,26 @@ def get_table_html(img, tb_cpns, ocr):
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def gather(kwd, fzy=10, ption=0.6):
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def gather(kwd, fzy=10, ption=0.6):
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nonlocal boxes
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nonlocal boxes
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eles = Recognizer.sort_Y_firstly(
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eles = LayoutRecognizer.sort_Y_firstly(
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[r for r in tb_cpns if re.match(kwd, r["label"])], fzy)
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[r for r in tb_cpns if re.match(kwd, r["label"])], fzy)
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eles = Recognizer.layouts_cleanup(boxes, eles, 5, ption)
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eles = LayoutRecognizer.layouts_cleanup(boxes, eles, 5, ption)
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return Recognizer.sort_Y_firstly(eles, 0)
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return LayoutRecognizer.sort_Y_firstly(eles, 0)
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headers = gather(r".*header$")
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headers = gather(r".*header$")
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rows = gather(r".* (row|header)")
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rows = gather(r".* (row|header)")
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spans = gather(r".*spanning")
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spans = gather(r".*spanning")
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clmns = sorted([r for r in tb_cpns if re.match(
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clmns = sorted([r for r in tb_cpns if re.match(
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r"table column$", r["label"])], key=lambda x: x["x0"])
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r"table column$", r["label"])], key=lambda x: x["x0"])
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clmns = Recognizer.layouts_cleanup(boxes, clmns, 5, 0.5)
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clmns = LayoutRecognizer.layouts_cleanup(boxes, clmns, 5, 0.5)
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for b in boxes:
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for b in boxes:
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ii = Recognizer.find_overlapped_with_threashold(b, rows, thr=0.3)
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ii = LayoutRecognizer.find_overlapped_with_threashold(b, rows, thr=0.3)
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if ii is not None:
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if ii is not None:
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b["R"] = ii
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b["R"] = ii
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b["R_top"] = rows[ii]["top"]
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b["R_top"] = rows[ii]["top"]
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b["R_bott"] = rows[ii]["bottom"]
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b["R_bott"] = rows[ii]["bottom"]
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ii = Recognizer.find_overlapped_with_threashold(b, headers, thr=0.3)
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ii = LayoutRecognizer.find_overlapped_with_threashold(b, headers, thr=0.3)
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if ii is not None:
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if ii is not None:
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b["H_top"] = headers[ii]["top"]
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b["H_top"] = headers[ii]["top"]
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b["H_bott"] = headers[ii]["bottom"]
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b["H_bott"] = headers[ii]["bottom"]
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@ -102,13 +95,13 @@ def get_table_html(img, tb_cpns, ocr):
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b["H_right"] = headers[ii]["x1"]
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b["H_right"] = headers[ii]["x1"]
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b["H"] = ii
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b["H"] = ii
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ii = Recognizer.find_horizontally_tightest_fit(b, clmns)
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ii = LayoutRecognizer.find_horizontally_tightest_fit(b, clmns)
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if ii is not None:
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if ii is not None:
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b["C"] = ii
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b["C"] = ii
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b["C_left"] = clmns[ii]["x0"]
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b["C_left"] = clmns[ii]["x0"]
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b["C_right"] = clmns[ii]["x1"]
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b["C_right"] = clmns[ii]["x1"]
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ii = Recognizer.find_overlapped_with_threashold(b, spans, thr=0.3)
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ii = LayoutRecognizer.find_overlapped_with_threashold(b, spans, thr=0.3)
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if ii is not None:
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if ii is not None:
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b["H_top"] = spans[ii]["top"]
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b["H_top"] = spans[ii]["top"]
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b["H_bott"] = spans[ii]["bottom"]
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b["H_bott"] = spans[ii]["bottom"]
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