v1.2.2

rkcosmos · rkcosmos · commit 0b67787e6c50 · 2021-01-05T20:45:05.000+07:00
diff --git a/README.md b/README.md
@@ -9,6 +9,10 @@
 Ready-to-use OCR with 70+ languages supported including Chinese, Japanese, Korean and Thai.
 
 ## What's new
+- 5 January 2021 - Version 1.2.2
+    - Add `optimal_num_chars` to `detect` method. If specified, bounding boxes with estimated number of characters near this value are returned first. (thanks [@adamfrees](https://github.com/adamfrees))
+    - Add `rotation_info` to `readtext` method. Allow EasyOCR to rotate each text box and return the one with the best confident score. Eligible values are 90, 180 and 270. For example, try [90, 180 ,270] for all possible text orientations. (thanks [@mijoo308](https://github.com/mijoo308))
+    - Update [documentation](https://www.jaided.ai/easyocr/documentation).
 - 17 November 2020 - Version 1.2
     - New language supports for Telugu and Kannada. These are experimental lite recognition models. Their file sizes are only around 7% of other models and they are ~6x faster at inference with CPU.
 - 12 October 2020 - Version 1.1.10
diff --git a/easyocr/__init__.py b/easyocr/__init__.py
@@ -1,3 +1,3 @@
 from .easyocr import Reader
 
-__version__ = '1.2.1'
+__version__ = '1.2.2'
diff --git a/easyocr/easyocr.py b/easyocr/easyocr.py
@@ -75,23 +75,24 @@ def __init__(self, lang_list, gpu=True, model_storage_directory=None,
         # check and download detection model
         corrupt_msg = 'MD5 hash mismatch, possible file corruption'
         detector_path = os.path.join(self.model_storage_directory, DETECTOR_FILENAME)
-        if os.path.isfile(detector_path) == False:
-            if not self.download_enabled:
-                raise FileNotFoundError("Missing %s and downloads disabled" % detector_path)
-            LOGGER.warning('Downloading detection model, please wait. '
-                           'This may take several minutes depending upon your network connection.')
-            download_and_unzip(model_url['detector'][0], DETECTOR_FILENAME, self.model_storage_directory)
-            assert calculate_md5(detector_path) == model_url['detector'][1], corrupt_msg
-            LOGGER.info('Download complete')
-        elif calculate_md5(detector_path) != model_url['detector'][1]:
-            if not self.download_enabled:
-                raise FileNotFoundError("MD5 mismatch for %s and downloads disabled" % detector_path)
-            LOGGER.warning(corrupt_msg)
-            os.remove(detector_path)
-            LOGGER.warning('Re-downloading the detection model, please wait. '
-                           'This may take several minutes depending upon your network connection.')
-            download_and_unzip(model_url['detector'][0], DETECTOR_FILENAME, self.model_storage_directory)
-            assert calculate_md5(detector_path) == model_url['detector'][1], corrupt_msg
+        if detector:
+            if os.path.isfile(detector_path) == False:
+                if not self.download_enabled:
+                    raise FileNotFoundError("Missing %s and downloads disabled" % detector_path)
+                LOGGER.warning('Downloading detection model, please wait. '
+                               'This may take several minutes depending upon your network connection.')
+                download_and_unzip(model_url['detector'][0], DETECTOR_FILENAME, self.model_storage_directory)
+                assert calculate_md5(detector_path) == model_url['detector'][1], corrupt_msg
+                LOGGER.info('Download complete')
+            elif calculate_md5(detector_path) != model_url['detector'][1]:
+                if not self.download_enabled:
+                    raise FileNotFoundError("MD5 mismatch for %s and downloads disabled" % detector_path)
+                LOGGER.warning(corrupt_msg)
+                os.remove(detector_path)
+                LOGGER.warning('Re-downloading the detection model, please wait. '
+                               'This may take several minutes depending upon your network connection.')
+                download_and_unzip(model_url['detector'][0], DETECTOR_FILENAME, self.model_storage_directory)
+                assert calculate_md5(detector_path) == model_url['detector'][1], corrupt_msg
 
         # recognition model
         separator_list = {}
@@ -197,24 +198,25 @@ def __init__(self, lang_list, gpu=True, model_storage_directory=None,
 
             model_path = os.path.join(self.model_storage_directory, model_file)
             # check recognition model file
-            if os.path.isfile(model_path) == False:
-                if not self.download_enabled:
-                    raise FileNotFoundError("Missing %s and downloads disabled" % model_path)
-                LOGGER.warning('Downloading recognition model, please wait. '
-                               'This may take several minutes depending upon your network connection.')
-                download_and_unzip(model_url[model_file][0], model_file, self.model_storage_directory)
-                assert calculate_md5(model_path) == model_url[model_file][1], corrupt_msg
-                LOGGER.info('Download complete.')
-            elif calculate_md5(model_path) != model_url[model_file][1]:
-                if not self.download_enabled:
-                    raise FileNotFoundError("MD5 mismatch for %s and downloads disabled" % model_path)
-                LOGGER.warning(corrupt_msg)
-                os.remove(model_path)
-                LOGGER.warning('Re-downloading the recognition model, please wait. '
-                               'This may take several minutes depending upon your network connection.')
-                download_and_unzip(model_url[model_file][0], model_file, self.model_storage_directory)
-                assert calculate_md5(model_path) == model_url[model_file][1], corrupt_msg
-                LOGGER.info('Download complete')
+            if recognizer:
+                if os.path.isfile(model_path) == False:
+                    if not self.download_enabled:
+                        raise FileNotFoundError("Missing %s and downloads disabled" % model_path)
+                    LOGGER.warning('Downloading recognition model, please wait. '
+                                   'This may take several minutes depending upon your network connection.')
+                    download_and_unzip(model_url[model_file][0], model_file, self.model_storage_directory)
+                    assert calculate_md5(model_path) == model_url[model_file][1], corrupt_msg
+                    LOGGER.info('Download complete.')
+                elif calculate_md5(model_path) != model_url[model_file][1]:
+                    if not self.download_enabled:
+                        raise FileNotFoundError("MD5 mismatch for %s and downloads disabled" % model_path)
+                    LOGGER.warning(corrupt_msg)
+                    os.remove(model_path)
+                    LOGGER.warning('Re-downloading the recognition model, please wait. '
+                                   'This may take several minutes depending upon your network connection.')
+                    download_and_unzip(model_url[model_file][0], model_file, self.model_storage_directory)
+                    assert calculate_md5(model_path) == model_url[model_file][1], corrupt_msg
+                    LOGGER.info('Download complete')
 
         self.lang_char = []
         for lang in lang_list:
diff --git a/releasenotes.md b/releasenotes.md
@@ -1,3 +1,9 @@
+- 5 January 2021 - Version 1.2.2
+    - Add `optimal_num_chars` to `detect` method. If specified, bounding boxes with estimated number of characters near this value are returned first. (thanks [@adamfrees](https://github.com/adamfrees))
+    - Add `rotation_info` to `readtext` method. Allow EasyOCR to rotate each text box and return the one with the best confident score. Eligible values are 90, 180 and 270. For example, try [90, 180 ,270] for all possible text orientations. (thanks [@mijoo308](https://github.com/mijoo308))
+    - Update [documentation](https://www.jaided.ai/easyocr/documentation).
+- 24 November 2020 - Version 1.2.1
+    - Preparation for user-created models
 - 17 November 2020 - Version 1.2
     - New language supports for Telugu and Kannada. These are experimental lite recognition models. Their file sizes are only around 7% of other models and they are ~6x faster at inference with CPU.
 - 12 October 2020 - Version 1.1.10
diff --git a/setup.py b/setup.py
@@ -17,7 +17,7 @@ def readme():
     name='easyocr',
     packages=['easyocr'],
     include_package_data=True,
-    version='1.2.1',
+    version='1.2.2',
     install_requires=requirements,
     entry_points={"console_scripts": ["easyocr= easyocr.cli:main"]},
     license='Apache License 2.0',

Original file line number	Diff line number	Diff line change
`@@ -1,3 +1,3 @@`
`1`	`1`	`from .easyocr import Reader`
`2`	`2`
`3`		`-__version__ = '1.2.1'`
	`3`	`+__version__ = '1.2.2'`