organize imports mostly

src/eynollah/eynollah.py

@@ -8,40 +8,26 @@
 document layout analysis (segmentation) with output in PAGE-XML
 """
 
-# cannot use importlib.resources until we move to 3.9+ forimportlib.resources.files
-import sys
-
-if sys.version_info < (3, 10):
-    import importlib_resources
-else:
-    import importlib.resources as importlib_resources
-
 from difflib import SequenceMatcher as sq
 from PIL import Image, ImageDraw, ImageFont
 import math
 import os
-import sys
 import time
 from typing import Dict,  Union,List, Optional, Tuple
-import atexit
 import warnings
 from functools import partial
 from pathlib import Path
 from multiprocessing import cpu_count
 import gc
 import copy
-import json
 
 from concurrent.futures import ProcessPoolExecutor
-import xml.etree.ElementTree as ET
 import cv2
 import numpy as np
 import shapely.affinity
 from scipy.signal import find_peaks
 from scipy.ndimage import gaussian_filter1d
-from numba import cuda
 from skimage.morphology import skeletonize
-from ocrd import OcrdPage
 from ocrd_utils import getLogger, tf_disable_interactive_logs
 import statistics
 
@@ -53,10 +39,6 @@ try:
     import matplotlib.pyplot as plt
 except ImportError:
     plt = None
-try:
-    from transformers import TrOCRProcessor, VisionEncoderDecoderModel
-except ImportError:
-    TrOCRProcessor = VisionEncoderDecoderModel = None
 
 #os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
 tf_disable_interactive_logs()
@@ -290,13 +272,6 @@ class Eynollah:
             if self.tr:
                 loadable.append(('ocr', 'tr'))
                 loadable.append(('ocr_tr_processor', 'tr'))
-                # TODO why here and why only for tr?
-                if torch.cuda.is_available():
-                    self.logger.info("Using GPU acceleration")
-                    self.device = torch.device("cuda:0")
-                else:
-                    self.logger.info("Using CPU processing")
-                    self.device = torch.device("cpu")
             else:
                 loadable.append('ocr')
                 loadable.append('num_to_char')
@@ -307,10 +282,16 @@ class Eynollah:
         if hasattr(self, 'executor') and getattr(self, 'executor'):
             self.executor.shutdown()
             self.executor = None
-        if hasattr(self, 'models') and getattr(self, 'models'):
+        self.model_zoo.shutdown()
-            for model_name in list(self.models):
+
-                if self.models[model_name]:
+    @property
-                    del self.models[model_name]
+    def device(self):
+        # TODO why here and why only for tr?
+        if torch.cuda.is_available():
+            self.logger.info("Using GPU acceleration")
+            return torch.device("cuda:0")
+        self.logger.info("Using CPU processing")
+        return torch.device("cpu")
 
     def cache_images(self, image_filename=None, image_pil=None, dpi=None):
         ret = {}

src/eynollah/eynollah_ocr.py

@@ -1,3 +1,41 @@
+# pyright: reportPossiblyUnboundVariable=false
+
+from logging import getLogger
+from typing import Optional
+from pathlib import Path
+import os
+import json
+import gc
+import sys
+import math
+import cv2
+import time
+
+from keras.layers import StringLookup
+
+from eynollah.utils.resize import resize_image
+from eynollah.utils.utils_ocr import break_curved_line_into_small_pieces_and_then_merge, decode_batch_predictions, fit_text_single_line, get_contours_and_bounding_boxes, get_orientation_moments, preprocess_and_resize_image_for_ocrcnn_model, return_textlines_split_if_needed, rotate_image_with_padding
+
+from .utils import is_image_filename
+
+import xml.etree.ElementTree as ET
+import tensorflow as tf
+from keras.models import load_model
+from PIL import Image, ImageDraw, ImageFont
+import numpy as np
+import torch
+
+# cannot use importlib.resources until we move to 3.9+ forimportlib.resources.files
+if sys.version_info < (3, 10):
+    import importlib_resources
+else:
+    import importlib.resources as importlib_resources
+
+try:
+    from transformers import TrOCRProcessor, VisionEncoderDecoderModel
+except ImportError:
+    TrOCRProcessor = VisionEncoderDecoderModel = None
+
 class Eynollah_ocr:
     def __init__(
         self,
@@ -25,6 +63,7 @@ class Eynollah_ocr:
             else:
                 self.min_conf_value_of_textline_text = 0.3
             if tr_ocr:
+                assert TrOCRProcessor
                 self.processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-printed")
                 self.device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
                 if self.model_name:

src/eynollah/model_zoo.py

@@ -2,7 +2,6 @@ from dataclasses import dataclass
 import json
 import logging
 from pathlib import Path
-from types import MappingProxyType
 from typing import Dict, Literal, Optional, Tuple,  List, Union
 from copy import deepcopy
 
@@ -12,6 +11,8 @@ from transformers import TrOCRProcessor, VisionEncoderDecoderModel
 
 from eynollah.patch_encoder import PatchEncoder, Patches
 
+SomeEynollahModel = Union[VisionEncoderDecoderModel, TrOCRProcessor, Model]
+
 
 # Dict mapping model_category to dict mapping variant (default is '') to Path
 DEFAULT_MODEL_VERSIONS: Dict[str, Dict[str, str]] = {
@@ -134,13 +135,14 @@ class EynollahModelZoo():
     def __init__(
         self,
         basedir: str,
-        model_overrides: List[Tuple[str, str, str]],
+        model_overrides: Optional[List[Tuple[str, str, str]]]=None,
     ) -> None:
         self.model_basedir = Path(basedir)
         self.logger = logging.getLogger('eynollah.model_zoo')
         self.model_versions = deepcopy(DEFAULT_MODEL_VERSIONS)
         if model_overrides:
             self.override_models(*model_overrides)
+        self._loaded: Dict[Tuple[str, str], SomeEynollahModel] = {}
 
     def override_models(self, *model_overrides: Tuple[str, str, str]):
         """
@@ -202,7 +204,7 @@ class EynollahModelZoo():
         model_category: str,
         model_variant: str = '',
         model_filename: str = '',
-    ) -> Union[VisionEncoderDecoderModel, TrOCRProcessor, Model]:
+    ) -> SomeEynollahModel:
         """
         Load any model
         """
@@ -223,9 +225,16 @@ class EynollahModelZoo():
                 self.logger.exception(e)
                 model = load_model(model_path, compile=False, custom_objects={
                     "PatchEncoder": PatchEncoder, "Patches": Patches})
+        self._loaded[(model_category, model_variant)] = model
         return model # type: ignore
 
-    def _load_ocr_model(self, variant: str) -> Union[VisionEncoderDecoderModel, TrOCRProcessor, Model]:
+    def get_model(self, model_categeory, model_variant) -> SomeEynollahModel:
+        needle = (model_categeory, model_variant)
+        if needle not in self._loaded:
+            raise ValueError('Model/variant "{needle} not previously loaded with "load_model(..)"')
+        return self._loaded[needle]
+
+    def _load_ocr_model(self, variant: str) -> SomeEynollahModel:
         """
         Load OCR model
         """
@@ -258,3 +267,12 @@ class EynollahModelZoo():
             'versions': self.model_versions,
         }, indent=2))
 
+    def shutdown(self):
+        """
+        Ensure that a loaded models is not referenced by ``self._loaded`` anymore
+        """
+        if hasattr(self, '_loaded') and getattr(self, '_loaded'):
+            for needle in self._loaded:
+                if self._loaded[needle]:
+                    del self._loaded[needle]
+