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Monitoring of the InvariMatch work on servers

As soon as we started providing our video recognition system to customers, it became necessary to monitor its stability. Without seeing the system parameters, it can be difficult to understand what is happening, and we had to make assumptions about the nature of the failure guided only by external signs. This was inconvenient and didn’t allow us to understand the cause of the problem and be able to respond to it fast enough. Therefore, we decided to install a monitoring system.

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Computer vision in self-driving cars. Part 3. Better than people

At the moment, self-driving cars can help drivers, but they only reach the third level of autonomy at best. That is why the Tesla manual states that a person has to keep their hands on the wheel while driving, so that they can take control of the car if necessary. The autonomous driving technology is not reliable enough as of now, and a failure in one of the cars subsystem may lead to an accident. But, even at this stage, the autopilot is able to predict and handle a number of dangerous situations much better than a person would.

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Adapting the InvariMatch system to work in a cluster

The InvariMatch system’s original architecture, where all video processing took place on one machine, worked well from the beginning. However, we understood that the system would fail under an increased load and thought about optimizing it. In 2016, one of our customers needed to install InvariMatch on a cluster of several machines. The system worked well at first, but after some time we faced several unexpected problems. We had to improve InvariMatch urgently, and these are the steps we took to achieve that.

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