From ec83abf61943b9135810cc292e54d7b9766edf5a Mon Sep 17 00:00:00 2001 From: Davis King Date: Tue, 22 May 2018 07:01:09 -0400 Subject: [PATCH] Removed notes about using --yes USE_AVX_INSTRUCTIONS when building python interface since AVX availability is now detected automatically by cmake. --- README.md | 9 --------- python_examples/cnn_face_detector.py | 4 ---- python_examples/correlation_tracker.py | 4 ---- python_examples/face_alignment.py | 5 ----- python_examples/face_clustering.py | 5 ----- python_examples/face_detector.py | 4 ---- python_examples/face_jitter.py | 5 ----- python_examples/face_landmark_detection.py | 4 ---- python_examples/face_recognition.py | 5 ----- python_examples/find_candidate_object_locations.py | 4 ---- python_examples/max_cost_assignment.py | 4 ---- python_examples/opencv_webcam_face_detection.py | 6 +----- python_examples/sequence_segmenter.py | 4 ---- python_examples/svm_binary_classifier.py | 4 ---- python_examples/svm_rank.py | 4 ---- python_examples/svm_struct.py | 4 ---- python_examples/train_object_detector.py | 4 ---- python_examples/train_shape_predictor.py | 4 ---- 18 files changed, 1 insertion(+), 82 deletions(-) diff --git a/README.md b/README.md index d9103d757..349f6070a 100644 --- a/README.md +++ b/README.md @@ -38,15 +38,6 @@ Before you can run the Python example programs you must compile dlib. Type: 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 diff --git a/python_examples/cnn_face_detector.py b/python_examples/cnn_face_detector.py index b7037dab5..5748a7530 100755 --- a/python_examples/cnn_face_detector.py +++ b/python_examples/cnn_face_detector.py @@ -23,10 +23,6 @@ # 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 --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 # CMake installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/correlation_tracker.py b/python_examples/correlation_tracker.py index 8d902cc77..39a7f6ad8 100755 --- a/python_examples/correlation_tracker.py +++ b/python_examples/correlation_tracker.py @@ -22,10 +22,6 @@ # 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 installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/face_alignment.py b/python_examples/face_alignment.py index 8de2043d0..a1bf1f2df 100755 --- a/python_examples/face_alignment.py +++ b/python_examples/face_alignment.py @@ -10,11 +10,6 @@ # 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. 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 # CMake installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/face_clustering.py b/python_examples/face_clustering.py index f4769b11e..1f249c5b8 100755 --- a/python_examples/face_clustering.py +++ b/python_examples/face_clustering.py @@ -17,11 +17,6 @@ # 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. 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 # CMake installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/face_detector.py b/python_examples/face_detector.py index 0d48fb822..f27ef67df 100755 --- a/python_examples/face_detector.py +++ b/python_examples/face_detector.py @@ -27,10 +27,6 @@ # 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 installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/face_jitter.py b/python_examples/face_jitter.py index a729e7dda..c01cd8f14 100755 --- a/python_examples/face_jitter.py +++ b/python_examples/face_jitter.py @@ -14,11 +14,6 @@ # 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. 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 # CMake installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/face_landmark_detection.py b/python_examples/face_landmark_detection.py index e7bda3412..3a108656e 100755 --- a/python_examples/face_landmark_detection.py +++ b/python_examples/face_landmark_detection.py @@ -35,10 +35,6 @@ # 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 installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/face_recognition.py b/python_examples/face_recognition.py index c7f5437a7..5ddec74ad 100755 --- a/python_examples/face_recognition.py +++ b/python_examples/face_recognition.py @@ -29,11 +29,6 @@ # 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. 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 # CMake installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/find_candidate_object_locations.py b/python_examples/find_candidate_object_locations.py index aee46e356..5febb0805 100755 --- a/python_examples/find_candidate_object_locations.py +++ b/python_examples/find_candidate_object_locations.py @@ -21,10 +21,6 @@ # 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 installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/max_cost_assignment.py b/python_examples/max_cost_assignment.py index 8e284e6c8..8c18fbaef 100755 --- a/python_examples/max_cost_assignment.py +++ b/python_examples/max_cost_assignment.py @@ -12,10 +12,6 @@ # 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 installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/opencv_webcam_face_detection.py b/python_examples/opencv_webcam_face_detection.py index be0e322b8..ebd6f8dee 100755 --- a/python_examples/opencv_webcam_face_detection.py +++ b/python_examples/opencv_webcam_face_detection.py @@ -25,10 +25,6 @@ # 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 installed. On Ubuntu, this can be done easily by running the @@ -56,4 +52,4 @@ while True: cv2.imshow('my webcam', img) if cv2.waitKey(1) == 27: break # esc to quit -cv2.destroyAllWindows() \ No newline at end of file +cv2.destroyAllWindows() diff --git a/python_examples/sequence_segmenter.py b/python_examples/sequence_segmenter.py index 335e475f7..aca28db86 100755 --- a/python_examples/sequence_segmenter.py +++ b/python_examples/sequence_segmenter.py @@ -17,10 +17,6 @@ # 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 installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/svm_binary_classifier.py b/python_examples/svm_binary_classifier.py index d114c815a..0941662d1 100755 --- a/python_examples/svm_binary_classifier.py +++ b/python_examples/svm_binary_classifier.py @@ -14,10 +14,6 @@ # 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 installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/svm_rank.py b/python_examples/svm_rank.py index dad642274..01c555f0c 100755 --- a/python_examples/svm_rank.py +++ b/python_examples/svm_rank.py @@ -21,10 +21,6 @@ # 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 installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/svm_struct.py b/python_examples/svm_struct.py index 7f0004ccd..6b658b9d6 100755 --- a/python_examples/svm_struct.py +++ b/python_examples/svm_struct.py @@ -21,10 +21,6 @@ # 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 installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/train_object_detector.py b/python_examples/train_object_detector.py index c9f324fa6..570a08cca 100755 --- a/python_examples/train_object_detector.py +++ b/python_examples/train_object_detector.py @@ -15,10 +15,6 @@ # 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 installed. On Ubuntu, this can be done easily by running the diff --git a/python_examples/train_shape_predictor.py b/python_examples/train_shape_predictor.py index e07f8299a..822a901db 100755 --- a/python_examples/train_shape_predictor.py +++ b/python_examples/train_shape_predictor.py @@ -23,10 +23,6 @@ # 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 installed. On Ubuntu, this can be done easily by running the