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dlib
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Code Issues Releases Wiki Activity

Removed notes about using --yes USE_AVX_INSTRUCTIONS when building python 

interface since AVX availability is now detected automatically by cmake.
This commit is contained in:
Davis King 2018-05-22 07:01:09 -04:00
parent 104ffddb4c
commit ec83abf619
18 changed files with 1 additions and 82 deletions
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9
README.md
View File

@ -38,15 +38,6 @@ Before you can run the Python example programs you must compile dlib. Type:
python setup.py install python setup.py install
``` ```
or type
```bash
python setup.py install --yes USE_AVX_INSTRUCTIONS
```
if you have a CPU that supports AVX instructions, since this makes some things run faster.
## Running the unit test suite ## Running the unit test suite

4
python_examples/cnn_face_detector.py
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@ -23,10 +23,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # python setup.py install
# or
# python setup.py install --yes USE_AVX_INSTRUCTIONS --yes DLIB_USE_CUDA
# if you have a CPU that supports AVX instructions, you have an Nvidia GPU
# and you have CUDA installed since this makes things run *much* faster.
# #
# Compiling dlib should work on any operating system so long as you have # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

4
python_examples/correlation_tracker.py
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@ -22,10 +22,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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 # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

5
python_examples/face_alignment.py
View File

@ -10,11 +10,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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. This code will also use CUDA if you have CUDA and cuDNN
# installed.
# #
# Compiling dlib should work on any operating system so long as you have # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

5
python_examples/face_clustering.py
View File

@ -17,11 +17,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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. This code will also use CUDA if you have CUDA and cuDNN
# installed.
# #
# Compiling dlib should work on any operating system so long as you have # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

4
python_examples/face_detector.py
View File

@ -27,10 +27,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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 # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

5
python_examples/face_jitter.py
View File

@ -14,11 +14,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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. This code will also use CUDA if you have CUDA and cuDNN
# installed.
# #
# Compiling dlib should work on any operating system so long as you have # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

4
python_examples/face_landmark_detection.py
View File

@ -35,10 +35,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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 # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

5
python_examples/face_recognition.py
View File

@ -29,11 +29,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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. This code will also use CUDA if you have CUDA and cuDNN
# installed.
# #
# Compiling dlib should work on any operating system so long as you have # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

4
python_examples/find_candidate_object_locations.py
View File

@ -21,10 +21,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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 # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

4
python_examples/max_cost_assignment.py
View File

@ -12,10 +12,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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 # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

4
python_examples/opencv_webcam_face_detection.py
View File

@ -25,10 +25,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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 # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

4
python_examples/sequence_segmenter.py
View File

@ -17,10 +17,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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 # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

4
python_examples/svm_binary_classifier.py
View File

@ -14,10 +14,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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 # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

4
python_examples/svm_rank.py
View File

@ -21,10 +21,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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 # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

4
python_examples/svm_struct.py
View File

@ -21,10 +21,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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 # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

4
python_examples/train_object_detector.py
View File

@ -15,10 +15,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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 # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the

4
python_examples/train_shape_predictor.py
View File

@ -23,10 +23,6 @@
# Alternatively, if you want to compile dlib yourself then go into the dlib # Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run: # root folder and run:
# python setup.py install # 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 # Compiling dlib should work on any operating system so long as you have
# CMake installed. On Ubuntu, this can be done easily by running the # CMake installed. On Ubuntu, this can be done easily by running the