Docling/docling/models/easyocr_model.py
Christoph Auer 60dc852f16
feat: Updated Layout processing with forms and key-value areas (#530)
* Upgraded Layout Postprocessing, sending old code back to ERZ

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Implement hierachical cluster layout processing

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Pass nested cluster processing through full pipeline

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Pass nested clusters through GLM as payload

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Move to_docling_document from ds-glm to this repo

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Clean up imports again

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* feat(Accelerator): Introduce options to control the num_threads and device from API, envvars, CLI.
- Introduce the AcceleratorOptions, AcceleratorDevice and use them to set the device where the models run.
- Introduce the accelerator_utils with function to decide the device and resolve the AUTO setting.
- Refactor the way how the docling-ibm-models are called to match the new init signature of models.
- Translate the accelerator options to the specific inputs for third-party models.
- Extend the docling CLI with parameters to set the num_threads and device.
- Add new unit tests.
- Write new example how to use the accelerator options.

* fix: Improve the pydantic objects in the pipeline_options and imports.

Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>

* fix: TableStructureModel: Refactor the artifacts path to use the new structure for fast/accurate model

Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>

* Updated test ground-truth

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Updated test ground-truth (again), bugfix for empty layout

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* fix: Do proper check to set the device in EasyOCR, RapidOCR.

Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>

* fix: Correct the way to set GPU for EasyOCR, RapidOCR

Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>

* fix: Ocr AccleratorDevice

Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>

* Merge pull request #556 from DS4SD/cau/layout-processing-improvement

feat: layout processing improvements and bugfixes

* Update lockfile

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Update tests

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Update HF model ref, reset test generate

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Repin to release package versions

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Many layout processing improvements, add document index type

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Update pinnings to docling-core

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Update test GT

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Fix table box snapping

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Fixes for cluster pre-ordering

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Introduce OCR confidence, propagate to orphan in post-processing

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Fix form and key value area groups

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Adjust confidence in EasyOcr

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Roll back CLI changes from main

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Update test GT

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Update docling-core pinning

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Annoying fixes for historical python versions

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Updated test GT for legacy

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Comment cleanup

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

---------

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>
Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com>
Co-authored-by: Nikos Livathinos <nli@zurich.ibm.com>
2024-12-17 17:32:24 +01:00

133 lines
4.9 KiB
Python

import logging
import warnings
from typing import Iterable
import numpy
import torch
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 (
AcceleratorDevice,
AcceleratorOptions,
EasyOcrOptions,
)
from docling.datamodel.settings import settings
from docling.models.base_ocr_model import BaseOcrModel
from docling.utils.accelerator_utils import decide_device
from docling.utils.profiling import TimeRecorder
_log = logging.getLogger(__name__)
class EasyOcrModel(BaseOcrModel):
def __init__(
self,
enabled: bool,
options: EasyOcrOptions,
accelerator_options: AcceleratorOptions,
):
super().__init__(enabled=enabled, options=options)
self.options: EasyOcrOptions
self.scale = 3 # multiplier for 72 dpi == 216 dpi.
if self.enabled:
try:
import easyocr
except ImportError:
raise ImportError(
"EasyOCR is not installed. Please install it via `pip install easyocr` to use this OCR engine. "
"Alternatively, Docling has support for other OCR engines. See the documentation."
)
if self.options.use_gpu is None:
device = decide_device(accelerator_options.device)
# Enable easyocr GPU if running on CUDA, MPS
use_gpu = any(
[
device.startswith(x)
for x in [
AcceleratorDevice.CUDA.value,
AcceleratorDevice.MPS.value,
]
]
)
else:
warnings.warn(
"Deprecated field. Better to set the `accelerator_options.device` in `pipeline_options`. "
"When `use_gpu and accelerator_options.device == AcceleratorDevice.CUDA` the GPU is used "
"to run EasyOCR. Otherwise, EasyOCR runs in CPU."
)
use_gpu = self.options.use_gpu
self.reader = easyocr.Reader(
lang_list=self.options.lang,
gpu=use_gpu,
model_storage_directory=self.options.model_storage_directory,
recog_network=self.options.recog_network,
download_enabled=self.options.download_enabled,
verbose=False,
)
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
)
im = numpy.array(high_res_image)
result = self.reader.readtext(im)
del high_res_image
del im
cells = [
OcrCell(
id=ix,
text=line[1],
confidence=line[2],
bbox=BoundingBox.from_tuple(
coord=(
(line[0][0][0] / self.scale) + ocr_rect.l,
(line[0][0][1] / self.scale) + ocr_rect.t,
(line[0][2][0] / self.scale) + ocr_rect.l,
(line[0][2][1] / self.scale) + ocr_rect.t,
),
origin=CoordOrigin.TOPLEFT,
),
)
for ix, line in enumerate(result)
if line[2] >= self.options.confidence_threshold
]
all_ocr_cells.extend(cells)
# 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