Python Bindings Reference - Stable

Version 0.32.13387

• Alpha

• Beta

• Stable

Getting Started

Start by downloading the correct version of the python bindings library. Note, the CPU python bindings library contains the static SDK library (so you do not need to download libtf.a library separately). If using the GPU python bindings library, then you will require both the python bindings library as well as libtf.so (both are packaged in the download zip). Ensure that libtf.so is in your LD_LIBRARY_PATH. You can confirm this by running ldd on the bindings library and ensuring that all dependencies are met.

The SDK must first be configured to your desired settings. Consult the general section for the various configuration options.

Python Bindings (Stable) - Contents:

• General
  • Deprecated
• License Validation
• Input Image
• Face Detection
• 1 to 1 Face Recognition
• 1 to N Identification
  • Overview
  • Using Multiple SDK Instances in a Single Process
  • Database Management Systems and Collection Synchronization
  • Memory Requirements and Workarounds
  • Selecting the Best Enrollment Image
• Object Detection
• Spoof Detection
  • Active Spoof
  • Passive Spoof
• Body Pose Estimation
• Liveness
• Mask Detection
• Eye glasses Detection
• Environment Variables
• Frequently Asked Questions
  • How many threads does the SDK use for inference?
  • How can I reduce the number of threads used by the SDK?
  • How can I run inference with multiple instances of the SDK on a single CPU?
  • How can I increase throughput?
  • Is the SDK threadsafe?
  • What architecture should I use when I have multiple camera streams producing lots of data?
  • What is the difference between the static library and the dynamic library?
  • What hardware does the GPU library support?
  • Why is my license key not working with the GPU library?
  • Why does the first call to an inference function take much longer than the subsequent calls?
  • How do I use the python bindings for the SDK?
  • How do I choose a similarity threshold for face recognition?
  • What are the differences between the face recognition models?
  • Are Faceprints compatible between models?
  • How can I upgrade my collection if is filled with Faceprints from a deprecated model?
  • What is the difference between similarity score and match probability?
  • There are many face detection and recognition functions. Which should I use?
  • How do createDatabaseConnection and createLoadCollection work?
  • Why are no faces being detected in my large images?
  • How can I speed up face detection?
  • What does the frVectorCompression flag do? When should I use it?
• Changelog
  • v0.32: October 15, 2021
  • v0.31: October 15, 2021
  • v0.30: September 24, 2021
  • v0.29: September 13, 2021
  • v0.28: August 18, 2021
  • v0.27: August 2, 2021
  • v0.26: July 6, 2021
  • v0.25: June 22, 2021
  • v0.24: June 8, 2021
  • v0.23: May 27, 2021
  • v0.22: May 12, 2021
  • v0.21: May 4, 2021
  • v0.20: April 26, 2021
  • v0.19: April 14, 2021
  • v0.18: March 29, 2021
  • v0.17: March 11, 2021
  • v0.16: February 25, 2021
  • v0.15: February 16, 2021
  • v0.14: January 25, 2021
  • v0.13: January 15, 2021
  • v0.12: January 4, 2021
  • v0.11: December 23, 2020
  • v0.10: December 11, 2020
  • v0.9: November 20, 2020
  • v0.8: November 9, 2020
  • v0.7: August 14, 2020
  • v0.6: July 7, 2020
• Previous Stable Releases
  • 0.32.13359
  • 0.32.13313
  • 0.30.12706
  • 0.29.12214
  • 0.29.12111
  • 0.28.11386
  • 0.27.10876
  • 0.26.10390
  • 0.25.10099
  • 0.24.9786
  • 0.24.9740
  • 0.23.9508
  • 0.23.9476
  • 0.22.9292
  • 0.22.9196
  • 0.21.8922
  • 0.20.8553
  • 0.19.8416
  • 0.18.7976
  • 0.17.7745
  • 0.17.7722
  • 0.16.7561
  • 0.16.7542
  • 0.15.7233
  • 0.15.7198
  • 0.15.7184
  • 0.14.6743
  • 0.14.6732
  • 0.14.6709
  • 0.14.6699
  • 0.13.6676
  • 0.13.6670
  • 0.13.6500
  • 0.12.6330
  • 0.12.6300
  • 0.11.6229
  • 0.10.5855
  • 0.10.5732
  • 0.9.5131
  • 0.8.4786
  • 0.7.3005

• Index