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perf: Move expensive imports closer to usage (#1863)

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* Move expensive imports closer to usage

Signed-off-by: William Easton <bill.easton@elastic.co>

* DCO Remediation Commit for William Easton <bill.easton@elastic.co>

I, William Easton <bill.easton@elastic.co>, hereby add my Signed-off-by to this commit: 8a7412ce5bb131a01bb6403067aeb948c9093b0b

Signed-off-by: William Easton <bill.easton@elastic.co>

* formatting fixes

Signed-off-by: William Easton <bill.easton@elastic.co>

* DCO Remediation Commit for William Easton <bill.easton@elastic.co>

I, William Easton <bill.easton@elastic.co>, hereby add my Signed-off-by to this commit: 8a7412ce5bb131a01bb6403067aeb948c9093b0b
I, William Easton <bill.easton@elastic.co>, hereby add my Signed-off-by to this commit: 963e34325071db5e844841f10c27b396a054a0a1

Signed-off-by: William Easton <bill.easton@elastic.co>

* Fix baseocrmodel test issue

Signed-off-by: William Easton <bill.easton@elastic.co>

---------

Signed-off-by: William Easton <bill.easton@elastic.co>
This commit is contained in:
William Easton 2025-07-01 15:27:17 -05:00 committed by GitHub
parent 56a0e104f7
commit 3089cf2d26
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GPG Key ID: B5690EEEBB952194
5 changed files with 22 additions and 15 deletions
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8
docling/models/base_ocr_model.py
View File

@ -3,14 +3,13 @@ import logging
from abc import abstractmethod
from collections.abc import Iterable
from pathlib import Path
from typing import List, Optional, Type
from typing import TYPE_CHECKING, List, Optional, Type
import numpy as np
from docling_core.types.doc import BoundingBox, CoordOrigin
from docling_core.types.doc.page import TextCell
from PIL import Image, ImageDraw
from rtree import index
from scipy.ndimage import binary_dilation, find_objects, label
from docling.datamodel.accelerator_options import AcceleratorOptions
from docling.datamodel.base_models import Page
@ -31,11 +30,16 @@ class BaseOcrModel(BasePageModel, BaseModelWithOptions):
options: OcrOptions,
accelerator_options: AcceleratorOptions,
):
# Make sure any delay/error from import occurs on ocr model init and not first use
from scipy.ndimage import binary_dilation, find_objects, label
self.enabled = enabled
self.options = options
# Computes the optimum amount and coordinates of rectangles to OCR on a given page
def get_ocr_rects(self, page: Page) -> List[BoundingBox]:
from scipy.ndimage import binary_dilation, find_objects, label
BITMAP_COVERAGE_TRESHOLD = 0.75
assert page.size is not None

3
docling/models/layout_model.py
View File

@ -7,7 +7,6 @@ from typing import Optional
import numpy as np
from docling_core.types.doc import DocItemLabel
from docling_ibm_models.layoutmodel.layout_predictor import LayoutPredictor
from PIL import Image
from docling.datamodel.accelerator_options import AcceleratorOptions
@ -51,6 +50,8 @@ class LayoutModel(BasePageModel):
def __init__(
self, artifacts_path: Optional[Path], accelerator_options: AcceleratorOptions
):
from docling_ibm_models.layoutmodel.layout_predictor import LayoutPredictor
device = decide_device(accelerator_options.device)
if artifacts_path is None:

18
docling/models/plugins/defaults.py
View File

@ -1,13 +1,10 @@
from docling.models.easyocr_model import EasyOcrModel
from docling.models.ocr_mac_model import OcrMacModel
from docling.models.picture_description_api_model import PictureDescriptionApiModel
from docling.models.picture_description_vlm_model import PictureDescriptionVlmModel
from docling.models.rapid_ocr_model import RapidOcrModel
from docling.models.tesseract_ocr_cli_model import TesseractOcrCliModel
from docling.models.tesseract_ocr_model import TesseractOcrModel
def ocr_engines():
from docling.models.easyocr_model import EasyOcrModel
from docling.models.ocr_mac_model import OcrMacModel
from docling.models.rapid_ocr_model import RapidOcrModel
from docling.models.tesseract_ocr_cli_model import TesseractOcrCliModel
from docling.models.tesseract_ocr_model import TesseractOcrModel
return {
"ocr_engines": [
EasyOcrModel,
@ -20,6 +17,9 @@ def ocr_engines():
def picture_description():
from docling.models.picture_description_api_model import PictureDescriptionApiModel
from docling.models.picture_description_vlm_model import PictureDescriptionVlmModel
return {
"picture_description": [
PictureDescriptionVlmModel,

4
docling/models/table_structure_model.py
View File

@ -10,7 +10,6 @@ from docling_core.types.doc.page import (
BoundingRectangle,
TextCellUnit,
)
from docling_ibm_models.tableformer.data_management.tf_predictor import TFPredictor
from PIL import ImageDraw
from docling.datamodel.accelerator_options import AcceleratorDevice, AcceleratorOptions
@ -70,6 +69,9 @@ class TableStructureModel(BasePageModel):
# Third Party
import docling_ibm_models.tableformer.common as c
from docling_ibm_models.tableformer.data_management.tf_predictor import (
TFPredictor,
)
device = decide_device(accelerator_options.device)

4
docling/utils/accelerator_utils.py
View File

@ -1,8 +1,6 @@
import logging
from typing import List, Optional
import torch
from docling.datamodel.accelerator_options import AcceleratorDevice
_log = logging.getLogger(__name__)
@ -18,6 +16,8 @@ def decide_device(
1. AUTO: Check for the best available device on the system.
2. User-defined: Check if the device actually exists, otherwise fall-back to CPU
"""
import torch
device = "cpu"
has_cuda = torch.backends.cuda.is_built() and torch.cuda.is_available()