Merge pull request #100 from Kohulan/development

Development

.gitattributes

@@ -0,0 +1,2 @@
+*.py text=auto eol=lf
+*.bat eol=crlf

DECIMER/__init__.py

@@ -1,29 +1,29 @@
-# -*- coding: utf-8 -*-
-"""DECIMER V2.6.0 Python Package. ============================
-
-This repository contains DECIMER-V2,Deep lEarning for Chemical ImagE Recognition) project
-was launched to address the OCSR problem with the latest computational intelligence methods
-to provide an automated open-source software solution.
-
-
-Typical usage example:
-
-from decimer import predict_SMILES
-
-# Chemical depiction to SMILES translation
-image_path = "path/to/imagefile"
-SMILES = predict_SMILES(image_path)
-print(SMILES)
-
-For comments, bug reports or feature ideas,
-please raise a issue on the Github repository.
-"""
-
-__version__ = "2.6.0"
-
-__all__ = [
-    "DECIMER",
-]
-
-
-from .decimer import predict_SMILES
+# -*- coding: utf-8 -*-
+"""DECIMER V2.6.0 Python Package. ============================
+
+This repository contains DECIMER-V2,Deep lEarning for Chemical ImagE Recognition) project
+was launched to address the OCSR problem with the latest computational intelligence methods
+to provide an automated open-source software solution.
+
+
+Typical usage example:
+
+from decimer import predict_SMILES
+
+# Chemical depiction to SMILES translation
+image_path = "path/to/imagefile"
+SMILES = predict_SMILES(image_path)
+print(SMILES)
+
+For comments, bug reports or feature ideas,
+please raise a issue on the Github repository.
+"""
+
+__version__ = "2.6.0"
+
+__all__ = [
+    "DECIMER",
+]
+
+
+from .decimer import predict_SMILES

DECIMER/decimer.py

@@ -117,7 +117,7 @@ def detokenize_output_add_confidence(
     decoded_prediction_with_confidence = list(
         [(utils.decoder(tok), conf) for tok, conf in prediction_with_confidence_]
     )
-    decoded_prediction_with_confidence.append(prediction_with_confidence_[-1])
+
     return decoded_prediction_with_confidence
 
 

DECIMER/utils.py

@@ -83,11 +83,10 @@ def ensure_models(default_path: str, model_urls: dict) -> dict:
     }
     for model_name, model_url in model_urls.items():
         model_path = os.path.join(default_path, f"{model_name}_model")
-        if (
-                os.path.exists(model_path)
-                and os.stat(os.path.join(model_path, "saved_model.pb")).st_size != model_sizes.get(model_name)
-        ):
-            print(f'Working with model {model_name}')
+        if os.path.exists(model_path) and os.stat(
+            os.path.join(model_path, "saved_model.pb")
+        ).st_size != model_sizes.get(model_name):
+            print(f"Working with model {model_name}")
             shutil.rmtree(model_path)
             config.download_trained_weights(model_url, default_path)
         elif not os.path.exists(model_path):

docs/make.bat

@@ -1,35 +1,35 @@
-@ECHO OFF
-
-pushd %~dp0
-
-REM Command file for Sphinx documentation
-
-if "%SPHINXBUILD%" == "" (
-	set SPHINXBUILD=sphinx-build
-)
-set SOURCEDIR=.
-set BUILDDIR=_build
-
-%SPHINXBUILD% >NUL 2>NUL
-if errorlevel 9009 (
-	echo.
-	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
-	echo.installed, then set the SPHINXBUILD environment variable to point
-	echo.to the full path of the 'sphinx-build' executable. Alternatively you
-	echo.may add the Sphinx directory to PATH.
-	echo.
-	echo.If you don't have Sphinx installed, grab it from
-	echo.https://www.sphinx-doc.org/
-	exit /b 1
-)
-
-if "%1" == "" goto help
-
-%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
-goto end
-
-:help
-%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
-
-:end
-popd
+@ECHO OFF
+
+pushd %~dp0
+
+REM Command file for Sphinx documentation
+
+if "%SPHINXBUILD%" == "" (
+	set SPHINXBUILD=sphinx-build
+)
+set SOURCEDIR=.
+set BUILDDIR=_build
+
+%SPHINXBUILD% >NUL 2>NUL
+if errorlevel 9009 (
+	echo.
+	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
+	echo.installed, then set the SPHINXBUILD environment variable to point
+	echo.to the full path of the 'sphinx-build' executable. Alternatively you
+	echo.may add the Sphinx directory to PATH.
+	echo.
+	echo.If you don't have Sphinx installed, grab it from
+	echo.https://www.sphinx-doc.org/
+	exit /b 1
+)
+
+if "%1" == "" goto help
+
+%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+goto end
+
+:help
+%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+
+:end
+popd

setup.py

@@ -1,55 +1,55 @@
-#!/usr/bin/env python
-import platform
-
-import setuptools
-
-if (
-    platform.processor() == "arm" or platform.processor() == "i386"
-) and platform.system() == "Darwin":
-    tensorflow_os = "tensorflow-macos>=2.10.0,<=2.15.0"
-else:
-    tensorflow_os = "tensorflow>=2.12.0,<=2.15.0"
-
-with open("README.md", "r") as fh:
-    long_description = fh.read()
-
-setuptools.setup(
-    name="decimer",
-    version="2.6.0",
-    author="Kohulan Rajan",
-    author_email="[email protected]",
-    maintainer="Kohulan Rajan, Otto Brinkhaus ",
-    maintainer_email="[email protected], [email protected]",
-    description="DECIMER 2.6.0: Deep Learning for Chemical Image Recognition using Efficient-Net V2 + Transformer",
-    long_description=long_description,
-    long_description_content_type="text/markdown",
-    entry_points={
-        "console_scripts": ["decimer = DECIMER.decimer:main"],
-    },
-    url="https://github.com/Kohulan/DECIMER-Image_Transformer",
-    packages=setuptools.find_packages(),
-    license="MIT",
-    install_requires=[
-        tensorflow_os,
-        "opencv-python",
-        "pystow",
-        "pillow-heif",
-        "efficientnet",
-        "selfies",
-        "pyyaml",
-    ],
-    package_data={"DECIMER": ["repack/*.*", "efficientnetv2/*.*", "Utils/*.*"]},
-    classifiers=[
-        "Programming Language :: Python :: 3",
-        "Programming Language :: Python :: 3.5",
-        "Programming Language :: Python :: 3.6",
-        "Programming Language :: Python :: 3.7",
-        "Programming Language :: Python :: 3.8",
-        "Programming Language :: Python :: 3.9",
-        "Programming Language :: Python :: 3.10",
-        "Programming Language :: Python :: 3 :: Only",
-        "License :: OSI Approved :: MIT License",
-        "Operating System :: OS Independent",
-    ],
-    python_requires=">=3.5",
-)
+#!/usr/bin/env python
+import platform
+
+import setuptools
+
+if (
+    platform.processor() == "arm" or platform.processor() == "i386"
+) and platform.system() == "Darwin":
+    tensorflow_os = "tensorflow-macos>=2.10.0,<=2.15.0"
+else:
+    tensorflow_os = "tensorflow>=2.12.0,<=2.15.0"
+
+with open("README.md", "r") as fh:
+    long_description = fh.read()
+
+setuptools.setup(
+    name="decimer",
+    version="2.6.0",
+    author="Kohulan Rajan",
+    author_email="[email protected]",
+    maintainer="Kohulan Rajan, Otto Brinkhaus ",
+    maintainer_email="[email protected], [email protected]",
+    description="DECIMER 2.6.0: Deep Learning for Chemical Image Recognition using Efficient-Net V2 + Transformer",
+    long_description=long_description,
+    long_description_content_type="text/markdown",
+    entry_points={
+        "console_scripts": ["decimer = DECIMER.decimer:main"],
+    },
+    url="https://github.com/Kohulan/DECIMER-Image_Transformer",
+    packages=setuptools.find_packages(),
+    license="MIT",
+    install_requires=[
+        tensorflow_os,
+        "opencv-python",
+        "pystow",
+        "pillow-heif",
+        "efficientnet",
+        "selfies",
+        "pyyaml",
+    ],
+    package_data={"DECIMER": ["repack/*.*", "efficientnetv2/*.*", "Utils/*.*"]},
+    classifiers=[
+        "Programming Language :: Python :: 3",
+        "Programming Language :: Python :: 3.5",
+        "Programming Language :: Python :: 3.6",
+        "Programming Language :: Python :: 3.7",
+        "Programming Language :: Python :: 3.8",
+        "Programming Language :: Python :: 3.9",
+        "Programming Language :: Python :: 3.10",
+        "Programming Language :: Python :: 3 :: Only",
+        "License :: OSI Approved :: MIT License",
+        "Operating System :: OS Independent",
+    ],
+    python_requires=">=3.5",
+)