It also has Python scripts to test your classifier out on an image, video, or webcam feed. The tutorial describes how to replace these files with your own files to train a detection classifier for whatever your heart desires. The repository provides all the files needed to train a "Pinochle Deck" playing card detector that can accurately detect nines, tens, jacks, queens, kings, and aces. Testing and using your newly trained object detection classifier.Creating a label map and configuring training.Setting up the Object Detection directory structure and Anaconda Virtual Environment.This readme describes every step required to get going with your own object detection classifier: If there are differences between this written tutorial and the video, follow the written tutorial! Any discrepancies between the video and this written tutorial are due to updates required for using newer versions of TensorFlow. Korean translation (thanks Chinese translation (thanks Vietnamese translation (thanks also made a YouTube video that walks through this tutorial. ![]() If you would like to contribute a translation in another language, please feel free! You can add it as a pull request and I will merge it when I get the chance. Translated versions of this guide are listed below. (It will also work on Linux-based OSes with some minor changes.) It was originally written using TensorFlow version 1.5, but will also work for newer versions of TensorFlow. ![]() This repository is a tutorial for how to use TensorFlow's Object Detection API to train an object detection classifier for multiple objects on Windows 10, 8, or 7. How To Train an Object Detection Classifier for Multiple Objects Using TensorFlow (GPU) on Windows 10 Brief Summary
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