fix: remove stderr from tesseract cli and introduce fuzziness in the text validation of OCR tests (#138)
* feat(OCR tests): Introduce fuzziness in the text validation of OCR tests Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com> * fix(TesseractOcrCliModel): Send the stderr to devnull to avoid poluting the console with messages from tesseract cmd Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com> --------- Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>
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@ -1,7 +1,7 @@
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import io
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import logging
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import tempfile
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from subprocess import PIPE, Popen
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from subprocess import DEVNULL, PIPE, Popen
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from typing import Iterable, Tuple
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import pandas as pd
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@ -81,7 +81,7 @@ class TesseractOcrCliModel(BaseOcrModel):
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cmd += [ifilename, "stdout", "tsv"]
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_log.info("command: {}".format(" ".join(cmd)))
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proc = Popen(cmd, stdout=PIPE)
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proc = Popen(cmd, stdout=PIPE, stderr=DEVNULL)
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output, _ = proc.communicate()
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# _log.info(output)
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@ -94,5 +94,5 @@ def test_e2e_conversions():
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input_path=pdf_path,
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doc_result=doc_result,
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generate=GENERATE,
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skip_cells=True,
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fuzzy=True,
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)
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@ -11,6 +11,42 @@ from docling.datamodel.base_models import ConversionStatus, Page
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from docling.datamodel.document import ConversionResult
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def levenshtein(str1: str, str2: str) -> int:
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# Ensure str1 is the shorter string to optimize memory usage
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if len(str1) > len(str2):
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str1, str2 = str2, str1
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# Previous and current row buffers
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previous_row = list(range(len(str2) + 1))
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current_row = [0] * (len(str2) + 1)
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# Compute the Levenshtein distance row by row
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for i, c1 in enumerate(str1, start=1):
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current_row[0] = i
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for j, c2 in enumerate(str2, start=1):
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insertions = previous_row[j] + 1
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deletions = current_row[j - 1] + 1
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substitutions = previous_row[j - 1] + (c1 != c2)
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current_row[j] = min(insertions, deletions, substitutions)
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# Swap rows for the next iteration
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previous_row, current_row = current_row, previous_row
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# The result is in the last element of the previous row
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return previous_row[-1]
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def verify_text(gt: str, pred: str, fuzzy: bool, fuzzy_threshold: float = 0.4):
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if len(gt) == 0 or not fuzzy:
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assert gt == pred, f"{gt}!={pred}"
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else:
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dist = levenshtein(gt, pred)
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diff = dist / len(gt)
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assert diff < fuzzy_threshold, f"{gt}!~{pred}"
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return True
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def verify_cells(doc_pred_pages: List[Page], doc_true_pages: List[Page]):
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assert len(doc_pred_pages) == len(
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@ -32,7 +68,6 @@ def verify_cells(doc_pred_pages: List[Page], doc_true_pages: List[Page]):
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true_text = cell_true_item.text
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pred_text = cell_pred_item.text
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assert true_text == pred_text, f"{true_text}!={pred_text}"
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true_bbox = cell_true_item.bbox.as_tuple()
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@ -69,7 +104,7 @@ def verify_maintext(doc_pred: DsDocument, doc_true: DsDocument):
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return True
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def verify_tables(doc_pred: DsDocument, doc_true: DsDocument):
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def verify_tables(doc_pred: DsDocument, doc_true: DsDocument, fuzzy: bool):
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if doc_true.tables is None:
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# No tables to check
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assert doc_pred.tables is None, "not expecting any table on this document"
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@ -102,9 +137,7 @@ def verify_tables(doc_pred: DsDocument, doc_true: DsDocument):
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# print("pred: ", pred_item.data[i][j].text)
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# print("")
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assert (
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true_item.data[i][j].text == pred_item.data[i][j].text
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), "table-cell does not have the same text"
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verify_text(true_item.data[i][j].text, pred_item.data[i][j].text, fuzzy)
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assert (
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true_item.data[i][j].obj_type == pred_item.data[i][j].obj_type
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@ -121,12 +154,12 @@ def verify_output(doc_pred: DsDocument, doc_true: DsDocument):
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return True
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def verify_md(doc_pred_md, doc_true_md):
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return doc_pred_md == doc_true_md
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def verify_md(doc_pred_md: str, doc_true_md: str, fuzzy: bool):
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return verify_text(doc_true_md, doc_pred_md, fuzzy)
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def verify_dt(doc_pred_dt, doc_true_dt):
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return doc_pred_dt == doc_true_dt
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def verify_dt(doc_pred_dt: str, doc_true_dt: str, fuzzy: bool):
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return verify_text(doc_true_dt, doc_pred_dt, fuzzy)
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def verify_conversion_result(
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@ -134,7 +167,7 @@ def verify_conversion_result(
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doc_result: ConversionResult,
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generate: bool = False,
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ocr_engine: str = None,
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skip_cells: bool = False,
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fuzzy: bool = False,
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):
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PageList = TypeAdapter(List[Page])
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@ -178,7 +211,7 @@ def verify_conversion_result(
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with open(dt_path, "r") as fr:
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doc_true_dt = fr.read()
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if not skip_cells:
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if not fuzzy:
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assert verify_cells(
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doc_pred_pages, doc_true_pages
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), f"Mismatch in PDF cell prediction for {input_path}"
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@ -188,13 +221,13 @@ def verify_conversion_result(
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# ), f"Mismatch in JSON prediction for {input_path}"
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assert verify_tables(
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doc_pred, doc_true
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doc_pred, doc_true, fuzzy
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), f"verify_tables(doc_pred, doc_true) mismatch for {input_path}"
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assert verify_md(
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doc_pred_md, doc_true_md
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doc_pred_md, doc_true_md, fuzzy
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), f"Mismatch in Markdown prediction for {input_path}"
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assert verify_dt(
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doc_pred_dt, doc_true_dt
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doc_pred_dt, doc_true_dt, fuzzy
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), f"Mismatch in DocTags prediction for {input_path}"
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