Benchmarks

Modes:

• Create a Configuration File
• Detection
• Processing
• 1:1 Recognition Test
• 1:N Recognition Test
• Search Speed Test

Create a Dataset Configuration File

• Dataset Configuration File is a text file with 3 lines per each image (<person_id> <image_id> <path_to_image>).

Example:

person0_id
image0_id
path_to_image0
person0_id
image1_id
path_to_image1
...

Example of creating an image dataset configuration file

Collect a list of image files

find -type f | sort > ../lfw_simple_format.txt

• lfw_simple_format.txt is a text file with the lines in the following format: <path/to/person/dir/image_file>. Images with the same path/to/person/dir belong to the same person. Images for one person must be in a row.

Example:

person1_dir/image1
person1_dir/image2
person2_dir/image1
...

The paths in the configuration files must be relative to the directory passed through the dataset_root_dir parameter.

Convert a list to a Configuration File

In this mode the program converts the config file from list format to dataset format (used in other modes):

Launch parameters:

• mode – program mode (convert_config_format)
• result_dataset_config – config file of the image dataset
• FILE – one file that contains a list of image files

Example of launch:

./test_sdk \
    --mode convert_config_format \
    --result_dataset_config dataset_config.txt \
    lfw_simple_format.txt

The conversion result is a config file of the image dataset.

Detection

In this mode the program detects faces in images with the id in the range of [begin_image_id, end_image_id). Each image should contain only one person. The images, containing more than one person detected, will be discarded.
Note: when using a GPU, it is recommended to run no more than one of any test at the same time.

ATTENTION

Before starting the program, you need to get the database file with images (see Create a Configuration File)

Launch parameters:

• mode – program mode (detection)
• dll_path – path to the libfacerec.so or facerec.dll library file
• sdk_config_dir – path to the conf/facerec directory
• dataset_config – config file of the image dataset (see Create a Configuration File)
• capturer_config – capturer config file name
• dataset_root_dir – path to the dataset directory
• detection_result_file – file for storing the detection results
• [begin_image_id] – index of the image, from which the detection begins (the default setting is 0)
• [end_image_id] – index of the image, to which detection is performed (by default, the processing is performed to the end of the file)
• [use_cpu_cores_count] – number of cores used for detection (the default setting is 1)

Example of launch from the bin directory:

./test_sdk \
    --mode detection \
    --dll_path ../lib/libfacerec.so \
    --sdk_config_dir ../conf/facerec \
    --capturer_config common_capturer4_lbf.xml \
    --dataset_config dataset_config.txt \
    --dataset_root_dir /path/to/data \
    --detection_result_file \
    detection_result.bin

The detection result is a text file with the lines in the following format: <image_id> <points_count> <points>

Processing

In this mode the program creates templates from the faces detected in the images with the id in the range of [begin_image_id, end_image_id).

ATTENTION

Before starting the program, you need to get the detections file for the recognizer under test (see Detection)

Launch parameters:

• mode – program mode (processing)
• dll_path – path to the libfacerec.so or facerec.dll library file
• sdk_config_dir – path to the conf/facerec directory
• dataset_config – config file of the image dataset (see Create a Configuration File)
• dataset_root_dir – path to the dataset directory
• recognizer_config – recognizer config file name
• processing_result_file – file for storing the resulting templates
• [begin_image_id] – index of the image, from which processing starts (the default setting is 0)
• [end_image_id] – index of the image, to which processing is performed (by default, the processing is performed at the end of the file)
• [use_cpu_cores_count] – number of cores used for processing (the default setting is 1)
• FILES – file(s) with the detection results

Note: a trial license allows to run the test only when [use_cpu_cores_count] is set to 1.

Example of launch from the bin directory:

./test_sdk \
    --mode processing \
    --dll_path ../lib/libfacerec.so \
    --sdk_config_dir ../conf/facerec \
    --dataset_config dataset_config.txt \
    --dataset_root_dir /path/to/data \
    --recognizer_config method6v7_recognizer.xml \
    --processing_result_file ./templates_6v7.bin \
    detection_result.bin

The processing result is a binary file, which contains one record per each generated template. Each record is a 64-bit unsigned integer (image_id) followed by a serialized template.

1:1 Recognition Test

In this mode the program performs the 1:1 recognition test using the templates generated from the images with the id in the range of [begin_image_id, end_image_id).

ATTENTION

Before running the test, it is necessary to calculate the template file for the recognizer under test (see Processing)

Launch parameters:

• mode – program mode (recognition_test_11)
• dll_path – path to the libfacerec.so or facerec.dll library file
• sdk_config_dir – path to the conf/facerec directory
• dataset_config – config file of the image dataset (see Create a Configuration File)
• recognizer_config – recognizer config file name
• result_roc_file – file to save the ROC curve
• result_closest_mismatches_file – result file with the closest mismatches
• [begin_image_id] – index of the first image used in the test (the default setting is 0)
• [end_image_id] – index of the first image after begin_image_id not used in the test (by default use all from begin_image_id to the end of the file)
• [use_cpu_cores_count] – number of cores used for matching (the default setting is 1)
• FILES – file(s) with the processing results

Note: a trial license allows to run the test only when [use_cpu_cores_count] is set to 1.

Example of launch from the bin directory:

./test_sdk \
    --mode recognition_test_11 \
    --dll_path ../lib/libfacerec.so \
    --sdk_config_dir ../conf/facerec \
    --dataset_config dataset_config.txt \
    --recognizer_config method6v7_recognizer.xml \
    --result_roc_file ./roc11_6v7.txt \
    --result_closest_mismatches_file ./closest_mismatches_file.txt \
    templates_6v7.bin

1:1 Recognition of test results:

• A text file, which contains a ROC curve; the file line describes the curve point in the following format: <far> <tar> <distance>.
• A text file with the lines in the following format: <distance> <image_id1> <image_id2> <path_to_image1> <path_to_image2>. This file contains pairs of images marked as belonging to different people, but having a minimum distance between the templates. We recommend you to generate this file using the best method and view the images from the top of it to check the errors of the dataset annotation.

Building a ROC curve

To draw a ROC curve, you need to run the draw_roc_curves utility (see Building a ROC curve)

1:N Recognition Test

In this mode the program performs the 1:N recognition test using the templates generated from the images with the id in the range of [begin_image_id, end_image_id).

ATTENTION

Before running the test, it is necessary to calculate the template file for the recognizer under test (see Processing)

Launch parameters:

• mode – program mode (recognition_test_1N)
• dll_path – path to the libfacerec.so or facerec.dll library file
• sdk_config_dir – path to the conf/facerec directory
• dataset_config – config file of the image dataset (see Create a Configuration File)
• recognizer_config – recognizer config file name
• result_roc_file – file to save the ROC curve.
• [begin_image_id] – index of the first image used in the test (the default setting is 0)
• [end_image_id] – index of the first image after begin_image_id not used in the test (by default use all from begin_image_id to the end of the file)
• [use_cpu_cores_count] – number of cores used for searching (the default setting is 1)
• [acceleration] – search acceleration type (the default setting is 0)
• 0 – search with pbio::Recognizer::search with the pbio::Recognizer::SearchAccelerationType::NO_SEARCH_ACCELERATION acceleration
• 1 – search with pbio::Recognizer::search with the pbio::Recognizer::SearchAccelerationType::SEARCH_ACCELERATION_1 acceleration -1 – search with pbio::Recognizer::verifyMatch in a single thread (independent of search_threads_count)
• FILES – file(s) with the processing results

Note: a trial license allows to run the test only when [use_cpu_cores_count] is set to 1. In addition, it may be needed to specify value for the [end_image_id] parameter so that "gallery_templates size" does not exceed 1000 (printed to the console after running the test).

Example of launch from the bin directory:

./test_sdk \
    --mode recognition_test_1N \
    --dll_path ../lib/libfacerec.so \
    --sdk_config_dir ../conf/facerec \
    --dataset_config dataset_config.txt \
    --recognizer_config method6v7_recognizer.xml \
    --result_roc_file ./roc1N_6v7.txt \
    --acceleration 1 \
    templates_6v7.bin

The result of the 1:N recognition test is a text file, which contains a ROC curve. The file line describes the curve point in the following format: <far> <tar> <distance>.

Building a ROC curve

To draw a ROC curve, you need to run the draw_roc_curves utility (see Building a ROC curve)

Search Speed Test

In this mode the program performs the search speed test using the templates generated in processing mode or using the utility (see Template Generator).

Launch parameters:

• mode – program mode (search_speed_test).
• dll_path – path to the libfacerec.so or facerec.dll library file
• sdk_config_dir – path to the conf/facerec directory
• recognizer_config – recognizer config file name
• [templates_count] – number of templates used (by default, processing is performed until the end of the file)
• [queries_count] – number of queries (the default setting is 1)
• [query_k_nearest] – number of the nearest templates for searching (the default setting is 1)
• [search_threads_count] – number of threads used for searching (the default setting is 1)
• [acceleration] – search acceleration type (the default setting is 0)
• 0 – search with pbio::Recognizer::search with the pbio::Recognizer::SearchAccelerationType::NO_SEARCH_ACCELERATION acceleration
• 1 – search with pbio::Recognizer::search with the pbio::Recognizer::SearchAccelerationType::SEARCH_ACCELERATION_1 acceleration
• -1 – search with pbio::Recognizer::verifyMatch in a single thread (independent of search_threads_count)
• FILES – file(s) obtained from the processing mode or by using the utility

Note: if a trial license is used, the value of [templates_count] cannot exceed 1000.

Example of launch from the bin directory:

./test_sdk \
    --mode search_speed_test \
    --dll_path ../lib/libfacerec.so \
    --sdk_config_dir ../conf/facerec \
    --recognizer_config method6v7_recognizer.xml \
    templates_6v7.bin

The result of the search speed test is a message with test results.

Utilities

Template Generator

A utility for creating random templates.

Launch parameters:

• recognizer_version – recognizer version (select one of [11v1000, 10v30, 10v100, 10v1000, 9v30, 9v300, 9v1000, 8v7, 8v6, 7v7, 7v6, 7v3, 7v2, 7, 6v7, 6v6, 6v5, 6v4, 6v3, 6v2, 6])
• templates_count – number of generated templates
• result_file – a result binary file, which contains the generated random templates

Example of launch:

./template_generator \
    6v7 \
    100000 \
    random_templates.bin

The template generator result is a binary file, which contains the generated random templates of the same format as in the processing mode.

Source code: examples/cpp/test_sdk

ROC-curve construction

A utility for constructing a ROC curve from a complete set of points.

WARNING

• Python 3 required to run the app
• Before running the program, you need to install the matplotlib package:

pip3 install matplotlib

Launch parameters:

• rocs_folder - path to the folder where the files with the calculated set of points for the ROC curve are stored
• roc_points_files – names of files for which it is necessary to build a curve (it is possible to specify several files). The file name will be displayed as the name of the ROC curve on the graph

Run example:

python3 ./draw_roc_curves.py\
    ./base_roc \
    roc11_11v1000.txt \
    roc11_10v100.txt \
    roc11_10v30.txt \
    roc11_9v300.txt

Source code: examples/python/draw_roc_curves.py