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Welcome to part 5 of the TensorFlow Object Detection API tutorial series. In this part and few in future, we're going to cover how we can track and detect our own custom objects with this API.
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[YouTube](https://www.youtube.com/watch?v=bYqvx_DM45U "TensorFlow object detection tutorial how to grab a screen")
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[YouTube](https://www.youtube.com/watch?v=bYqvx_DM45U "TensorFlow object detection tutorial")
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[![TensorFlow object detection tutorial](https://img.youtube.com/vi/bYqvx_DM45U/0.jpg)](https://www.youtube.com/watch?v=bYqvx_DM45U "TensorFlow object detection tutorial")
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I am doing this by using the pre-built model to add custom detection objects to it. That’s a decent jump from my findings, and it’s quite hard to locate any full step-by-step tutorials, so hopefully I can help you with that. Once you finish this tutorial you will have the ability to train for any custom object you can think of (and create data for) - that’s an awesome skill to have in my opinion.
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