automatic import of python-auto-face-recognition

3 files changed, 498 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..b4acfd1 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/auto_face_recognition-0.0.3.tar.gz
diff --git a/python-auto-face-recognition.spec b/python-auto-face-recognition.spec
new file mode 100644
index 0000000..0418361
--- /dev/null
+++ b/python-auto-face-recognition.spec
@@ -0,0 +1,496 @@
+%global _empty_manifest_terminate_build 0
+Name:		python-auto-face-recognition
+Version:	0.0.3
+Release:	1
+Summary:	auto_face_recognition is Tensorflow based python library for fast face recognition
+License:	MIT License
+URL:		https://github.com/Dipeshpal/auto_face_recognition
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/ce/80/b2bfb193f9adc38f8b60995d2c23f4746a72c2f46e33e153c31a37e5680a/auto_face_recognition-0.0.3.tar.gz
+BuildArch:	noarch
+
+Requires:	python3-numpy
+Requires:	python3-opencv-contrib-python
+Requires:	python3-tensorflow
+Requires:	python3-matplotlib
+
+%description
+
+# [auto_face_recognition](https://github.com/Dipeshpal/auto_face_recognition)
+
+***Last Upadted: 19 November, 2020***
+
+1. What is auto_face_recognition?
+ 2. Prerequisite
+ 3. Getting Started- How to use it?
+ 4. Future?
+
+## 1. What is auto_face_recognition?
+It is a python library for the Face Recognition. This library make face recognition easy and simple. This library uses Tensorflow 2.0+ for the face recognition and model training.
+
+## 2. Prerequisite-
+
+* To use it only Python (> 3.6) is required.
+* Recommended Python < 3.9
+
+## 3. Getting Started (How to use it)-
+
+ ### Install the latest version-
+ `pip install auto_face_recognition`
+
+It will install all the required package automatically, including Tensorflow Latest.
+
+
+### Usage and Features-
+
+After installing the library you can import the module-
+
+1. **Object Creation-**
+	```
+	import auto_face_recognition
+	obj = auto_face_recognition.AutoFaceRecognition()
+	```
+2. **Dataset Creation-**
+
+
+	    obj.datasetcreate(haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',  
+	    	    	                  eyecascade_path='haarcascade/haarcascade_eye.xml') 
+
+	***Note:*** You need to pass the '[haarcascade_frontalface_default.xml](https://github.com/opencv/opencv/blob/master/data/haarcascades/haarcascade_frontalface_default.xml)' and '[haarcascade_eye.xml](https://github.com/opencv/opencv/blob/master/data/haarcascades/haarcascade_eye.xml)' path.
+
+3. **Model Training-**
+
+		obj.face_recognition_train()		
+
+4. **Predict Faces-**
+
+	    # Real Time
+	    obj.predict_faces()
+	    # Single Face Recofnition
+	    obj.predict_face()
+
+**Parameters You Can Choose-**
+
+datasetcreate
+
+    datasetcreate(dataset_path='datasets', class_name='Demo',  
+                      haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',  
+                      eyecascade_path='haarcascade/haarcascade_eye.xml', eye_detect=False,  
+                      save_face_only=True, no_of_samples=100,  
+                      width=128, height=128, color_mode=False)
+    """"                  
+	Dataset Create by face detection  
+	:param dataset_path: str (example: 'folder_of_dataset')
+	:param class_name: str (example: 'folder_of_dataset')
+	:param haarcascade_path: str (example: 'haarcascade_frontalface_default.xml)
+	:param eyecascade_path: str (example: 'haarcascade_eye.xml):param eye_detect: bool (example:True)
+	:param save_face_only: bool (example:True)
+	:param no_of_samples: int (example: 100)
+	:param width: int (example: 128)
+	:param height: int (example: 128)
+	:param color_mode: bool (example:False):return: None
+	"""  
+face_recognition_train
+
+    face_recognition_train(data_dir='datasets', batch_size=32, img_height=128, img_width=128, epochs=10, model_path='model', pretrained=None, base_model_trainable=False):  
+     """  
+     Train TF Keras model according to dataset path  
+     :param data_dir: str (example: 'folder_of_dataset')  
+     :param batch_size: int (example:32)  
+     :param img_height: int (example:128)  
+     :param img_width: int (example:128)  
+     :param epochs: int (example:10)  
+     :param model_path: str (example: 'model')  
+     :param pretrained: str (example: None, 'VGG16', 'ResNet50' or 'InceptionV3')
+     :param base_model_trainable: bool (example: False (Enable if you want to train the pretrained model's layer))
+     :return: None  
+     """
+
+   predict_faces
+
+    predict_faces(self, class_name=None, img_height=128, img_width=128,  
+                  haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',  
+                  eyecascade_path='haarcascade/haarcascade_eye.xml', model_path='model',  
+                  color_mode=False):  
+	 """  
+	 Predict Face  
+	 :param class_name: Type-List (example: ['class1', 'class2'] )  
+	 :param img_height: int (example:128)  
+	 :param img_width: int (example:128)  
+	 :param haarcascade_path: str (example: 'haarcascade_frontalface_default.xml)  
+	 :param eyecascade_path: str (example: 'haarcascade_eye.xml)  
+	 :param model_path: str (example: 'model')  
+	 :param color_mode: bool (example: False)  
+	 :return: None  
+	 """
+
+predict_face
+
+
+    predict_face(self, class_name=None, img_height=128, img_width=128,  
+                     haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',  
+                     eyecascade_path='haarcascade/haarcascade_eye.xml', model_path='model',  
+                     color_mode=False, image_path='tmp.png'):  
+      """  
+      Predict Face  
+     :param class_name: Type-List (example: ['class1', 'class2'] )  
+     :param img_height: int (example:128)  
+     :param img_width: int (example:128)  
+     :param haarcascade_path: str (example: 'haarcascade_frontalface_default.xml)  
+     :param eyecascade_path: str (example: 'haarcascade_eye.xml)  
+     :param model_path: str (example: 'model')  
+     :param color_mode: bool (example: False)  
+     :param image_path: str (example: 'src/image_predict.png'  
+     :return: None  
+     """
+
+## 4. Future?
+
+	Finetuning with Resnet and others.
+	You Suggest.
+
+### Like my work?
+
+Start the project and subscribe me on [YouTube](https://www.youtube.com/dipeshpal17).
+https://www.youtube.com/dipeshpal17
+
+
+
+
+%package -n python3-auto-face-recognition
+Summary:	auto_face_recognition is Tensorflow based python library for fast face recognition
+Provides:	python-auto-face-recognition
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-auto-face-recognition
+
+# [auto_face_recognition](https://github.com/Dipeshpal/auto_face_recognition)
+
+***Last Upadted: 19 November, 2020***
+
+1. What is auto_face_recognition?
+ 2. Prerequisite
+ 3. Getting Started- How to use it?
+ 4. Future?
+
+## 1. What is auto_face_recognition?
+It is a python library for the Face Recognition. This library make face recognition easy and simple. This library uses Tensorflow 2.0+ for the face recognition and model training.
+
+## 2. Prerequisite-
+
+* To use it only Python (> 3.6) is required.
+* Recommended Python < 3.9
+
+## 3. Getting Started (How to use it)-
+
+ ### Install the latest version-
+ `pip install auto_face_recognition`
+
+It will install all the required package automatically, including Tensorflow Latest.
+
+
+### Usage and Features-
+
+After installing the library you can import the module-
+
+1. **Object Creation-**
+	```
+	import auto_face_recognition
+	obj = auto_face_recognition.AutoFaceRecognition()
+	```
+2. **Dataset Creation-**
+
+
+	    obj.datasetcreate(haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',  
+	    	    	                  eyecascade_path='haarcascade/haarcascade_eye.xml') 
+
+	***Note:*** You need to pass the '[haarcascade_frontalface_default.xml](https://github.com/opencv/opencv/blob/master/data/haarcascades/haarcascade_frontalface_default.xml)' and '[haarcascade_eye.xml](https://github.com/opencv/opencv/blob/master/data/haarcascades/haarcascade_eye.xml)' path.
+
+3. **Model Training-**
+
+		obj.face_recognition_train()		
+
+4. **Predict Faces-**
+
+	    # Real Time
+	    obj.predict_faces()
+	    # Single Face Recofnition
+	    obj.predict_face()
+
+**Parameters You Can Choose-**
+
+datasetcreate
+
+    datasetcreate(dataset_path='datasets', class_name='Demo',  
+                      haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',  
+                      eyecascade_path='haarcascade/haarcascade_eye.xml', eye_detect=False,  
+                      save_face_only=True, no_of_samples=100,  
+                      width=128, height=128, color_mode=False)
+    """"                  
+	Dataset Create by face detection  
+	:param dataset_path: str (example: 'folder_of_dataset')
+	:param class_name: str (example: 'folder_of_dataset')
+	:param haarcascade_path: str (example: 'haarcascade_frontalface_default.xml)
+	:param eyecascade_path: str (example: 'haarcascade_eye.xml):param eye_detect: bool (example:True)
+	:param save_face_only: bool (example:True)
+	:param no_of_samples: int (example: 100)
+	:param width: int (example: 128)
+	:param height: int (example: 128)
+	:param color_mode: bool (example:False):return: None
+	"""  
+face_recognition_train
+
+    face_recognition_train(data_dir='datasets', batch_size=32, img_height=128, img_width=128, epochs=10, model_path='model', pretrained=None, base_model_trainable=False):  
+     """  
+     Train TF Keras model according to dataset path  
+     :param data_dir: str (example: 'folder_of_dataset')  
+     :param batch_size: int (example:32)  
+     :param img_height: int (example:128)  
+     :param img_width: int (example:128)  
+     :param epochs: int (example:10)  
+     :param model_path: str (example: 'model')  
+     :param pretrained: str (example: None, 'VGG16', 'ResNet50' or 'InceptionV3')
+     :param base_model_trainable: bool (example: False (Enable if you want to train the pretrained model's layer))
+     :return: None  
+     """
+
+   predict_faces
+
+    predict_faces(self, class_name=None, img_height=128, img_width=128,  
+                  haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',  
+                  eyecascade_path='haarcascade/haarcascade_eye.xml', model_path='model',  
+                  color_mode=False):  
+	 """  
+	 Predict Face  
+	 :param class_name: Type-List (example: ['class1', 'class2'] )  
+	 :param img_height: int (example:128)  
+	 :param img_width: int (example:128)  
+	 :param haarcascade_path: str (example: 'haarcascade_frontalface_default.xml)  
+	 :param eyecascade_path: str (example: 'haarcascade_eye.xml)  
+	 :param model_path: str (example: 'model')  
+	 :param color_mode: bool (example: False)  
+	 :return: None  
+	 """
+
+predict_face
+
+
+    predict_face(self, class_name=None, img_height=128, img_width=128,  
+                     haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',  
+                     eyecascade_path='haarcascade/haarcascade_eye.xml', model_path='model',  
+                     color_mode=False, image_path='tmp.png'):  
+      """  
+      Predict Face  
+     :param class_name: Type-List (example: ['class1', 'class2'] )  
+     :param img_height: int (example:128)  
+     :param img_width: int (example:128)  
+     :param haarcascade_path: str (example: 'haarcascade_frontalface_default.xml)  
+     :param eyecascade_path: str (example: 'haarcascade_eye.xml)  
+     :param model_path: str (example: 'model')  
+     :param color_mode: bool (example: False)  
+     :param image_path: str (example: 'src/image_predict.png'  
+     :return: None  
+     """
+
+## 4. Future?
+
+	Finetuning with Resnet and others.
+	You Suggest.
+
+### Like my work?
+
+Start the project and subscribe me on [YouTube](https://www.youtube.com/dipeshpal17).
+https://www.youtube.com/dipeshpal17
+
+
+
+
+%package help
+Summary:	Development documents and examples for auto-face-recognition
+Provides:	python3-auto-face-recognition-doc
+%description help
+
+# [auto_face_recognition](https://github.com/Dipeshpal/auto_face_recognition)
+
+***Last Upadted: 19 November, 2020***
+
+1. What is auto_face_recognition?
+ 2. Prerequisite
+ 3. Getting Started- How to use it?
+ 4. Future?
+
+## 1. What is auto_face_recognition?
+It is a python library for the Face Recognition. This library make face recognition easy and simple. This library uses Tensorflow 2.0+ for the face recognition and model training.
+
+## 2. Prerequisite-
+
+* To use it only Python (> 3.6) is required.
+* Recommended Python < 3.9
+
+## 3. Getting Started (How to use it)-
+
+ ### Install the latest version-
+ `pip install auto_face_recognition`
+
+It will install all the required package automatically, including Tensorflow Latest.
+
+
+### Usage and Features-
+
+After installing the library you can import the module-
+
+1. **Object Creation-**
+	```
+	import auto_face_recognition
+	obj = auto_face_recognition.AutoFaceRecognition()
+	```
+2. **Dataset Creation-**
+
+
+	    obj.datasetcreate(haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',  
+	    	    	                  eyecascade_path='haarcascade/haarcascade_eye.xml') 
+
+	***Note:*** You need to pass the '[haarcascade_frontalface_default.xml](https://github.com/opencv/opencv/blob/master/data/haarcascades/haarcascade_frontalface_default.xml)' and '[haarcascade_eye.xml](https://github.com/opencv/opencv/blob/master/data/haarcascades/haarcascade_eye.xml)' path.
+
+3. **Model Training-**
+
+		obj.face_recognition_train()		
+
+4. **Predict Faces-**
+
+	    # Real Time
+	    obj.predict_faces()
+	    # Single Face Recofnition
+	    obj.predict_face()
+
+**Parameters You Can Choose-**
+
+datasetcreate
+
+    datasetcreate(dataset_path='datasets', class_name='Demo',  
+                      haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',  
+                      eyecascade_path='haarcascade/haarcascade_eye.xml', eye_detect=False,  
+                      save_face_only=True, no_of_samples=100,  
+                      width=128, height=128, color_mode=False)
+    """"                  
+	Dataset Create by face detection  
+	:param dataset_path: str (example: 'folder_of_dataset')
+	:param class_name: str (example: 'folder_of_dataset')
+	:param haarcascade_path: str (example: 'haarcascade_frontalface_default.xml)
+	:param eyecascade_path: str (example: 'haarcascade_eye.xml):param eye_detect: bool (example:True)
+	:param save_face_only: bool (example:True)
+	:param no_of_samples: int (example: 100)
+	:param width: int (example: 128)
+	:param height: int (example: 128)
+	:param color_mode: bool (example:False):return: None
+	"""  
+face_recognition_train
+
+    face_recognition_train(data_dir='datasets', batch_size=32, img_height=128, img_width=128, epochs=10, model_path='model', pretrained=None, base_model_trainable=False):  
+     """  
+     Train TF Keras model according to dataset path  
+     :param data_dir: str (example: 'folder_of_dataset')  
+     :param batch_size: int (example:32)  
+     :param img_height: int (example:128)  
+     :param img_width: int (example:128)  
+     :param epochs: int (example:10)  
+     :param model_path: str (example: 'model')  
+     :param pretrained: str (example: None, 'VGG16', 'ResNet50' or 'InceptionV3')
+     :param base_model_trainable: bool (example: False (Enable if you want to train the pretrained model's layer))
+     :return: None  
+     """
+
+   predict_faces
+
+    predict_faces(self, class_name=None, img_height=128, img_width=128,  
+                  haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',  
+                  eyecascade_path='haarcascade/haarcascade_eye.xml', model_path='model',  
+                  color_mode=False):  
+	 """  
+	 Predict Face  
+	 :param class_name: Type-List (example: ['class1', 'class2'] )  
+	 :param img_height: int (example:128)  
+	 :param img_width: int (example:128)  
+	 :param haarcascade_path: str (example: 'haarcascade_frontalface_default.xml)  
+	 :param eyecascade_path: str (example: 'haarcascade_eye.xml)  
+	 :param model_path: str (example: 'model')  
+	 :param color_mode: bool (example: False)  
+	 :return: None  
+	 """
+
+predict_face
+
+
+    predict_face(self, class_name=None, img_height=128, img_width=128,  
+                     haarcascade_path='haarcascade/haarcascade_frontalface_default.xml',  
+                     eyecascade_path='haarcascade/haarcascade_eye.xml', model_path='model',  
+                     color_mode=False, image_path='tmp.png'):  
+      """  
+      Predict Face  
+     :param class_name: Type-List (example: ['class1', 'class2'] )  
+     :param img_height: int (example:128)  
+     :param img_width: int (example:128)  
+     :param haarcascade_path: str (example: 'haarcascade_frontalface_default.xml)  
+     :param eyecascade_path: str (example: 'haarcascade_eye.xml)  
+     :param model_path: str (example: 'model')  
+     :param color_mode: bool (example: False)  
+     :param image_path: str (example: 'src/image_predict.png'  
+     :return: None  
+     """
+
+## 4. Future?
+
+	Finetuning with Resnet and others.
+	You Suggest.
+
+### Like my work?
+
+Start the project and subscribe me on [YouTube](https://www.youtube.com/dipeshpal17).
+https://www.youtube.com/dipeshpal17
+
+
+
+
+%prep
+%autosetup -n auto-face-recognition-0.0.3
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+if [ -d usr/lib ]; then
+	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/lib64 ]; then
+	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/bin ]; then
+	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+if [ -d usr/sbin ]; then
+	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
+fi
+touch doclist.lst
+if [ -d usr/share/man ]; then
+	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
+fi
+popd
+mv %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-auto-face-recognition -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Thu May 18 2023 Python_Bot <Python_Bot@openeuler.org> - 0.0.3-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..5571d23
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+c9459a7fe4f0d4848d65a6bb870eb401  auto_face_recognition-0.0.3.tar.gz