File size: 9,310 Bytes
fcaa164 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 |
import csv
import io
import logging
import os
import tempfile
from subprocess import DEVNULL, PIPE, Popen
from typing import Iterable, List, Optional, Tuple
import pandas as pd
from docling_core.types.doc import BoundingBox, CoordOrigin
from docling.datamodel.base_models import Cell, OcrCell, Page
from docling.datamodel.document import ConversionResult
from docling.datamodel.pipeline_options import TesseractCliOcrOptions
from docling.datamodel.settings import settings
from docling.models.base_ocr_model import BaseOcrModel
from docling.utils.ocr_utils import map_tesseract_script
from docling.utils.profiling import TimeRecorder
_log = logging.getLogger(__name__)
class TesseractOcrCliModel(BaseOcrModel):
def __init__(self, enabled: bool, options: TesseractCliOcrOptions):
super().__init__(enabled=enabled, options=options)
self.options: TesseractCliOcrOptions
self.scale = 3 # multiplier for 72 dpi == 216 dpi.
self._name: Optional[str] = None
self._version: Optional[str] = None
self._tesseract_languages: Optional[List[str]] = None
self._script_prefix: Optional[str] = None
if self.enabled:
try:
self._get_name_and_version()
self._set_languages_and_prefix()
except Exception as exc:
raise RuntimeError(
f"Tesseract is not available, aborting: {exc} "
"Install tesseract on your system and the tesseract binary is discoverable. "
"The actual command for Tesseract can be specified in `pipeline_options.ocr_options.tesseract_cmd='tesseract'`. "
"Alternatively, Docling has support for other OCR engines. See the documentation."
)
def _get_name_and_version(self) -> Tuple[str, str]:
if self._name != None and self._version != None:
return self._name, self._version # type: ignore
cmd = [self.options.tesseract_cmd, "--version"]
proc = Popen(cmd, stdout=PIPE, stderr=PIPE)
stdout, stderr = proc.communicate()
proc.wait()
# HACK: Windows versions of Tesseract output the version to stdout, Linux versions
# to stderr, so check both.
version_line = (
(stdout.decode("utf8").strip() or stderr.decode("utf8").strip())
.split("\n")[0]
.strip()
)
# If everything else fails...
if not version_line:
version_line = "tesseract XXX"
name, version = version_line.split(" ")
self._name = name
self._version = version
return name, version
def _run_tesseract(self, ifilename: str):
r"""
Run tesseract CLI
"""
cmd = [self.options.tesseract_cmd]
if "auto" in self.options.lang:
lang = self._detect_language(ifilename)
if lang is not None:
cmd.append("-l")
cmd.append(lang)
elif self.options.lang is not None and len(self.options.lang) > 0:
cmd.append("-l")
cmd.append("+".join(self.options.lang))
if self.options.path is not None:
cmd.append("--tessdata-dir")
cmd.append(self.options.path)
cmd += [ifilename, "stdout", "tsv"]
_log.info("command: {}".format(" ".join(cmd)))
proc = Popen(cmd, stdout=PIPE, stderr=DEVNULL)
output, _ = proc.communicate()
# _log.info(output)
# Decode the byte string to a regular string
decoded_data = output.decode("utf-8")
# _log.info(decoded_data)
# Read the TSV file generated by Tesseract
df = pd.read_csv(io.StringIO(decoded_data), quoting=csv.QUOTE_NONE, sep="\t")
# Display the dataframe (optional)
# _log.info("df: ", df.head())
# Filter rows that contain actual text (ignore header or empty rows)
df_filtered = df[df["text"].notnull() & (df["text"].str.strip() != "")]
return df_filtered
def _detect_language(self, ifilename: str):
r"""
Run tesseract in PSM 0 mode to detect the language
"""
assert self._tesseract_languages is not None
cmd = [self.options.tesseract_cmd]
cmd.extend(["--psm", "0", "-l", "osd", ifilename, "stdout"])
_log.info("command: {}".format(" ".join(cmd)))
proc = Popen(cmd, stdout=PIPE, stderr=DEVNULL)
output, _ = proc.communicate()
decoded_data = output.decode("utf-8")
df = pd.read_csv(
io.StringIO(decoded_data), sep=":", header=None, names=["key", "value"]
)
scripts = df.loc[df["key"] == "Script"].value.tolist()
if len(scripts) == 0:
_log.warning("Tesseract cannot detect the script of the page")
return None
script = map_tesseract_script(scripts[0].strip())
lang = f"{self._script_prefix}{script}"
# Check if the detected language has been installed
if lang not in self._tesseract_languages:
msg = f"Tesseract detected the script '{script}' and language '{lang}'."
msg += " However this language is not installed in your system and will be ignored."
_log.warning(msg)
return None
_log.debug(
f"Using tesseract model for the detected script '{script}' and language '{lang}'"
)
return lang
def _set_languages_and_prefix(self):
r"""
Read and set the languages installed in tesseract and decide the script prefix
"""
# Get all languages
cmd = [self.options.tesseract_cmd]
cmd.append("--list-langs")
_log.info("command: {}".format(" ".join(cmd)))
proc = Popen(cmd, stdout=PIPE, stderr=DEVNULL)
output, _ = proc.communicate()
decoded_data = output.decode("utf-8")
df = pd.read_csv(io.StringIO(decoded_data), header=None)
self._tesseract_languages = df[0].tolist()[1:]
# Decide the script prefix
if any([l.startswith("script/") for l in self._tesseract_languages]):
script_prefix = "script/"
else:
script_prefix = ""
self._script_prefix = script_prefix
def __call__(
self, conv_res: ConversionResult, page_batch: Iterable[Page]
) -> Iterable[Page]:
if not self.enabled:
yield from page_batch
return
for page in page_batch:
assert page._backend is not None
if not page._backend.is_valid():
yield page
else:
with TimeRecorder(conv_res, "ocr"):
ocr_rects = self.get_ocr_rects(page)
all_ocr_cells = []
for ocr_rect in ocr_rects:
# Skip zero area boxes
if ocr_rect.area() == 0:
continue
high_res_image = page._backend.get_page_image(
scale=self.scale, cropbox=ocr_rect
)
try:
with tempfile.NamedTemporaryFile(
suffix=".png", mode="w+b", delete=False
) as image_file:
fname = image_file.name
high_res_image.save(image_file)
df = self._run_tesseract(fname)
finally:
if os.path.exists(fname):
os.remove(fname)
# _log.info(df)
# Print relevant columns (bounding box and text)
for ix, row in df.iterrows():
text = row["text"]
conf = row["conf"]
l = float(row["left"])
b = float(row["top"])
w = float(row["width"])
h = float(row["height"])
t = b + h
r = l + w
cell = OcrCell(
id=ix,
text=text,
confidence=conf / 100.0,
bbox=BoundingBox.from_tuple(
coord=(
(l / self.scale) + ocr_rect.l,
(b / self.scale) + ocr_rect.t,
(r / self.scale) + ocr_rect.l,
(t / self.scale) + ocr_rect.t,
),
origin=CoordOrigin.TOPLEFT,
),
)
all_ocr_cells.append(cell)
# Post-process the cells
page.cells = self.post_process_cells(all_ocr_cells, page.cells)
# DEBUG code:
if settings.debug.visualize_ocr:
self.draw_ocr_rects_and_cells(conv_res, page, ocr_rects)
yield page
|