We employed the following software tools: Tensorflow 1.8 served as the basic framework for the entire system. Luminoth v0.2.0 is Tensorflow-based and provided the detection framework. The Hungarian algorithm was implemented in Scipy v1.1.0. The OpenCV 3.1.0 library was used to handle png/jpeg images. All experiments were run on a dual-socket server equipped with Intel Xeon CPUs, 128GB RAM, and two NVIDIA Tesla P100 cards.
Tesla p100 cards
Manufactured by NVIDIA
The Tesla P100 is a high-performance GPU designed for scientific and technical computing applications. It features the NVIDIA Pascal architecture, which provides advanced parallel processing capabilities. The Tesla P100 is equipped with 3,584 CUDA cores, 16GB of HBM2 memory, and a thermal design power (TDP) of 300W. It is intended to accelerate a wide range of scientific and technical workloads, such as deep learning, high-performance computing, and scientific simulations.
Automatically generated - may contain errors
Lab products found in correlation
2 protocols using tesla p100 cards
1
Object Detection with Tensorflow and OpenCV
2
Object Detection with Tensorflow and OpenCV
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