Updated compile/install instructions for python bindings.

python_examples/compile_dlib_python_module.bat

-mkdir build
-cd build
-cmake ../../tools/python
-cmake --build . --config Release --target install
-cd ..

python_examples/correlation_tracker.py

@@ -14,13 +14,22 @@
 # and someone is waving the camera around.  The task is to track the position of
 # the juice box as the camera moves around.
 #
-# COMPILING THE DLIB PYTHON INTERFACE
-#   Dlib comes with a compiled python interface for python 2.7 on MS Windows. If
-#   you are using another python version or operating system then you need to
-#   compile the dlib python interface before you can use this file.  To do this,
-#   run compile_dlib_python_module.bat.  This should work on any operating
-#   system so long as you have CMake and boost-python installed.
-#   On Ubuntu, this can be done easily by running the command:
+#
+# COMPILING/INSTALLING THE DLIB PYTHON INTERFACE
+#   You can install dlib using the command:
+#       pip install dlib
+#
+#   Alternatively, if you want to compile dlib yourself then go into the dlib
+#   root folder and run:
+#       python setup.py install
+#   or
+#       python setup.py install --yes USE_AVX_INSTRUCTIONS
+#   if you have a CPU that supports AVX instructions, since this makes some
+#   things run faster.  
+#
+#   Compiling dlib should work on any operating system so long as you have
+#   CMake and boost-python installed.  On Ubuntu, this can be done easily by
+#   running the command:
 #       sudo apt-get install libboost-python-dev cmake
 #
 #   Also note that this example requires scikit-image which can be installed

python_examples/face_detector.py

@@ -20,13 +20,21 @@
 #   program.  
 #
 #
-# COMPILING THE DLIB PYTHON INTERFACE
-#   Dlib comes with a compiled python interface for python 2.7 on MS Windows. If
-#   you are using another python version or operating system then you need to
-#   compile the dlib python interface before you can use this file.  To do this,
-#   run compile_dlib_python_module.bat.  This should work on any operating
-#   system so long as you have CMake and boost-python installed.
-#   On Ubuntu, this can be done easily by running the command:
+# COMPILING/INSTALLING THE DLIB PYTHON INTERFACE
+#   You can install dlib using the command:
+#       pip install dlib
+#
+#   Alternatively, if you want to compile dlib yourself then go into the dlib
+#   root folder and run:
+#       python setup.py install
+#   or
+#       python setup.py install --yes USE_AVX_INSTRUCTIONS
+#   if you have a CPU that supports AVX instructions, since this makes some
+#   things run faster.  
+#
+#   Compiling dlib should work on any operating system so long as you have
+#   CMake and boost-python installed.  On Ubuntu, this can be done easily by
+#   running the command:
 #       sudo apt-get install libboost-python-dev cmake
 #
 #   Also note that this example requires scikit-image which can be installed

python_examples/face_landmark_detection.py

@@ -20,13 +20,21 @@
 #   You can get the shape_predictor_68_face_landmarks.dat file from:
 #   http://sourceforge.net/projects/dclib/files/dlib/v18.10/shape_predictor_68_face_landmarks.dat.bz2
 #
-# COMPILING THE DLIB PYTHON INTERFACE
-#   Dlib comes with a compiled python interface for python 2.7 on MS Windows. If
-#   you are using another python version or operating system then you need to
-#   compile the dlib python interface before you can use this file.  To do this,
-#   run compile_dlib_python_module.bat.  This should work on any operating
-#   system so long as you have CMake and boost-python installed.
-#   On Ubuntu, this can be done easily by running the command:
+# COMPILING/INSTALLING THE DLIB PYTHON INTERFACE
+#   You can install dlib using the command:
+#       pip install dlib
+#
+#   Alternatively, if you want to compile dlib yourself then go into the dlib
+#   root folder and run:
+#       python setup.py install
+#   or
+#       python setup.py install --yes USE_AVX_INSTRUCTIONS
+#   if you have a CPU that supports AVX instructions, since this makes some
+#   things run faster.  
+#
+#   Compiling dlib should work on any operating system so long as you have
+#   CMake and boost-python installed.  On Ubuntu, this can be done easily by
+#   running the command:
 #       sudo apt-get install libboost-python-dev cmake
 #
 #   Also note that this example requires scikit-image which can be installed

python_examples/find_candidate_object_locations.py

@@ -13,6 +13,24 @@
 # a few thousand rectangles it is much faster than scanning all possible
 # rectangles inside an image.
 #
+#
+# COMPILING/INSTALLING THE DLIB PYTHON INTERFACE
+#   You can install dlib using the command:
+#       pip install dlib
+#
+#   Alternatively, if you want to compile dlib yourself then go into the dlib
+#   root folder and run:
+#       python setup.py install
+#   or
+#       python setup.py install --yes USE_AVX_INSTRUCTIONS
+#   if you have a CPU that supports AVX instructions, since this makes some
+#   things run faster.  
+#
+#   Compiling dlib should work on any operating system so long as you have
+#   CMake and boost-python installed.  On Ubuntu, this can be done easily by
+#   running the command:
+#       sudo apt-get install libboost-python-dev cmake
+#
 #   Also note that this example requires scikit-image which can be installed
 #   via the command:
 #       pip install -U scikit-image

python_examples/max_cost_assignment.py

@@ -5,14 +5,24 @@
 # problem solver.  It is an implementation of the famous Hungarian algorithm
 # and is quite fast, operating in O(N^3) time.
 #
-# COMPILING THE DLIB PYTHON INTERFACE
-#   Dlib comes with a compiled python interface for python 2.7 on MS Windows. If
-#   you are using another python version or operating system then you need to
-#   compile the dlib python interface before you can use this file.  To do this,
-#   run compile_dlib_python_module.bat.  This should work on any operating
-#   system so long as you have CMake and boost-python installed.
-#   On Ubuntu, this can be done easily by running the command:
+# COMPILING/INSTALLING THE DLIB PYTHON INTERFACE
+#   You can install dlib using the command:
+#       pip install dlib
+#
+#   Alternatively, if you want to compile dlib yourself then go into the dlib
+#   root folder and run:
+#       python setup.py install
+#   or
+#       python setup.py install --yes USE_AVX_INSTRUCTIONS
+#   if you have a CPU that supports AVX instructions, since this makes some
+#   things run faster.  
+#
+#   Compiling dlib should work on any operating system so long as you have
+#   CMake and boost-python installed.  On Ubuntu, this can be done easily by
+#   running the command:
 #       sudo apt-get install libboost-python-dev cmake
+#
+
 import dlib
 
 # Let's imagine you need to assign N people to N jobs.  Additionally, each

python_examples/sequence_segmenter.py

@@ -10,14 +10,23 @@
 # will be to learn to identify person names.  Once we have our segmentation
 # model we can use it to find names in new sentences, as we will show.
 #
-# COMPILING THE DLIB PYTHON INTERFACE
-#   Dlib comes with a compiled python interface for python 2.7 on MS Windows. If
-#   you are using another python version or operating system then you need to
-#   compile the dlib python interface before you can use this file.  To do this,
-#   run compile_dlib_python_module.bat.  This should work on any operating
-#   system so long as you have CMake and boost-python installed.
-#   On Ubuntu, this can be done easily by running the command:
+# COMPILING/INSTALLING THE DLIB PYTHON INTERFACE
+#   You can install dlib using the command:
+#       pip install dlib
+#
+#   Alternatively, if you want to compile dlib yourself then go into the dlib
+#   root folder and run:
+#       python setup.py install
+#   or
+#       python setup.py install --yes USE_AVX_INSTRUCTIONS
+#   if you have a CPU that supports AVX instructions, since this makes some
+#   things run faster.  
+#
+#   Compiling dlib should work on any operating system so long as you have
+#   CMake and boost-python installed.  On Ubuntu, this can be done easily by
+#   running the command:
 #       sudo apt-get install libboost-python-dev cmake
+#
 import sys
 import dlib
 

python_examples/svm_rank.py

@@ -13,14 +13,25 @@
 # that you use this score to order the objects so that the most relevant objects
 # come to the top of the ranked list.
 #
-# COMPILING THE DLIB PYTHON INTERFACE
-#   Dlib comes with a compiled python interface for python 2.7 on MS Windows. If
-#   you are using another python version or operating system then you need to
-#   compile the dlib python interface before you can use this file.  To do this,
-#   run compile_dlib_python_module.bat.  This should work on any operating
-#   system so long as you have CMake and boost-python installed.
-#   On Ubuntu, this can be done easily by running the command:
+#
+# COMPILING/INSTALLING THE DLIB PYTHON INTERFACE
+#   You can install dlib using the command:
+#       pip install dlib
+#
+#   Alternatively, if you want to compile dlib yourself then go into the dlib
+#   root folder and run:
+#       python setup.py install
+#   or
+#       python setup.py install --yes USE_AVX_INSTRUCTIONS
+#   if you have a CPU that supports AVX instructions, since this makes some
+#   things run faster.  
+#
+#   Compiling dlib should work on any operating system so long as you have
+#   CMake and boost-python installed.  On Ubuntu, this can be done easily by
+#   running the command:
 #       sudo apt-get install libboost-python-dev cmake
+#
+
 import dlib
 
 

python_examples/svm_struct.py

@@ -13,14 +13,25 @@
 # interface.  So consider using the C++ interface instead if you find that
 # running it in python is slow.
 #
-# COMPILING THE DLIB PYTHON INTERFACE
-#   Dlib comes with a compiled python interface for python 2.7 on MS Windows. If
-#   you are using another python version or operating system then you need to
-#   compile the dlib python interface before you can use this file.  To do this,
-#   run compile_dlib_python_module.bat.  This should work on any operating
-#   system so long as you have CMake and boost-python installed.
-#   On Ubuntu, this can be done easily by running the command:
+#
+# COMPILING/INSTALLING THE DLIB PYTHON INTERFACE
+#   You can install dlib using the command:
+#       pip install dlib
+#
+#   Alternatively, if you want to compile dlib yourself then go into the dlib
+#   root folder and run:
+#       python setup.py install
+#   or
+#       python setup.py install --yes USE_AVX_INSTRUCTIONS
+#   if you have a CPU that supports AVX instructions, since this makes some
+#   things run faster.  
+#
+#   Compiling dlib should work on any operating system so long as you have
+#   CMake and boost-python installed.  On Ubuntu, this can be done easily by
+#   running the command:
 #       sudo apt-get install libboost-python-dev cmake
+#
+
 import dlib
 
 

python_examples/train_object_detector.py

@@ -7,13 +7,22 @@
 #   window object detector first published by Dalal and Triggs in 2005 in the
 #   paper Histograms of Oriented Gradients for Human Detection.
 #
-# COMPILING THE DLIB PYTHON INTERFACE
-#   Dlib comes with a compiled python interface for python 2.7 on MS Windows. If
-#   you are using another python version or operating system then you need to
-#   compile the dlib python interface before you can use this file.  To do this,
-#   run compile_dlib_python_module.bat.  This should work on any operating
-#   system so long as you have CMake and boost-python installed.
-#   On Ubuntu, this can be done easily by running the command:
+#
+# COMPILING/INSTALLING THE DLIB PYTHON INTERFACE
+#   You can install dlib using the command:
+#       pip install dlib
+#
+#   Alternatively, if you want to compile dlib yourself then go into the dlib
+#   root folder and run:
+#       python setup.py install
+#   or
+#       python setup.py install --yes USE_AVX_INSTRUCTIONS
+#   if you have a CPU that supports AVX instructions, since this makes some
+#   things run faster.  
+#
+#   Compiling dlib should work on any operating system so long as you have
+#   CMake and boost-python installed.  On Ubuntu, this can be done easily by
+#   running the command:
 #       sudo apt-get install libboost-python-dev cmake
 #
 #   Also note that this example requires scikit-image which can be installed

python_examples/train_shape_predictor.py

@@ -16,13 +16,21 @@
 #   prediction tasks.  But here we demonstrate it only on a simple face
 #   landmarking task.
 #
-# COMPILING THE DLIB PYTHON INTERFACE
-#   Dlib comes with a compiled python interface for python 2.7 on MS Windows. If
-#   you are using another python version or operating system then you need to
-#   compile the dlib python interface before you can use this file.  To do this,
-#   run compile_dlib_python_module.bat.  This should work on any operating
-#   system so long as you have CMake and boost-python installed.
-#   On Ubuntu, this can be done easily by running the command:
+# COMPILING/INSTALLING THE DLIB PYTHON INTERFACE
+#   You can install dlib using the command:
+#       pip install dlib
+#
+#   Alternatively, if you want to compile dlib yourself then go into the dlib
+#   root folder and run:
+#       python setup.py install
+#   or
+#       python setup.py install --yes USE_AVX_INSTRUCTIONS
+#   if you have a CPU that supports AVX instructions, since this makes some
+#   things run faster.  
+#
+#   Compiling dlib should work on any operating system so long as you have
+#   CMake and boost-python installed.  On Ubuntu, this can be done easily by
+#   running the command:
 #       sudo apt-get install libboost-python-dev cmake
 #
 #   Also note that this example requires scikit-image which can be installed