Fixed rebased issues

Signed-off-by: ahn <ahn@zurich.ibm.com>

docling/datamodel/pipeline_options.py

@@ -7,6 +7,7 @@ from pathlib import Path
 from typing import Annotated, Any, Dict, List, Literal, Optional, Union
 
 from pydantic import (
+    AnyUrl,
     BaseModel,
     ConfigDict,
     Field,
@@ -66,6 +67,7 @@ class AcceleratorOptions(BaseSettings):
         """
         if isinstance(data, dict):
             input_num_threads = data.get("num_threads")
+            # Check if to set the num_threads from the alternative envvar
             if input_num_threads is None:
                 docling_num_threads = os.getenv("DOCLING_NUM_THREADS")
                 omp_num_threads = os.getenv("OMP_NUM_THREADS")

docling/models/easyocr_model.py

@@ -18,6 +18,7 @@ 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
+from docling.utils.utils import download_url_with_progress
 
 _log = logging.getLogger(__name__)
 
@@ -81,6 +82,40 @@ class EasyOcrModel(BaseOcrModel):
                 verbose=False,
             )
 
+    @staticmethod
+    def download_models(
+        detection_models: List[str] = ["craft"],
+        recognition_models: List[str] = ["english_g2", "latin_g2"],
+        local_dir: Optional[Path] = None,
+        force: bool = False,
+        progress: bool = False,
+    ) -> Path:
+        # Models are located in https://github.com/JaidedAI/EasyOCR/blob/master/easyocr/config.py
+        from easyocr.config import detection_models as det_models_dict
+        from easyocr.config import recognition_models as rec_models_dict
+
+        if local_dir is None:
+            local_dir = settings.cache_dir / "models" / EasyOcrModel._model_repo_folder
+
+        local_dir.mkdir(parents=True, exist_ok=True)
+
+        # Collect models to download
+        download_list = []
+        for model_name in detection_models:
+            if model_name in det_models_dict:
+                download_list.append(det_models_dict[model_name])
+        for model_name in recognition_models:
+            if model_name in rec_models_dict["gen2"]:
+                download_list.append(rec_models_dict["gen2"][model_name])
+
+        # Download models
+        for model_details in download_list:
+            buf = download_url_with_progress(model_details["url"], progress=progress)
+            with zipfile.ZipFile(buf, "r") as zip_ref:
+                zip_ref.extractall(local_dir)
+
+        return local_dir
+
     def __call__(
         self, conv_res: ConversionResult, page_batch: Iterable[Page]
     ) -> Iterable[Page]:

docs/examples/run_with_accelerator.py

@@ -31,11 +31,11 @@ def main():
     # )
 
     # easyocr doesnt support cuda:N allocation, defaults to cuda:0
-    # accelerator_options = AcceleratorOptions(num_threads=8, device="cuda:1")
+    accelerator_options = AcceleratorOptions(num_threads=8, device="cuda:1")
 
     pipeline_options = PdfPipelineOptions()
     pipeline_options.accelerator_options = accelerator_options
-    pipeline_options.do_ocr = True
+    pipeline_options.do_ocr = False
     pipeline_options.do_table_structure = True
     pipeline_options.table_structure_options.do_cell_matching = True