How to Train Object Detection Neural Network using TensorFlow 2.3 on Google Colab Free GPU

How to Train Object Detection Neural Network using TensorFlow 2.3 on Google Colab Free GPU

In this tensorflow tutorial, I have explained how to train tensorflow object detection api with your own data. I have used tensorflow latest version here. For

In this tensorflow tutorial, I have explained how to train tensorflow object detection api with your own data. I have used tensorflow latest version here. For

model training, I am using google colab free GPU. It means it’s a full-on tutorial on how to train object detection api with your own data or custom model on google colab. I have taken the example of playing card detection in this video and the model is taken from tensorflow model zoo.

-----Time links to each step in the video----- 3:24 Step 1. Install TensorFlow object detection api using powershell,Set up Object Detection directory and python virtual environment at once 6:30 Step 2. Gather and label pictures 13:51 Step 3. Generate training and testing dataset 16:39 Step 4. Create train tfrecord and test tfrecord files 20:23 Step 5. Create label map and configure training 28:55 Step 6. Setup google colab for object detection model training 33:20 Step 7. Start model training on colab 33:56 Step 8. Export inference graph 36:57 Step 9. Try out your object detector for images. 39:46 Step 10. Try out your object detector on live webcam.

Github ripo link : https://github.com/jakkcoder/widows-object-detection-setup

Subscribe : https://www.youtube.com/channel/UCoB1kaaQrQEkB-ud2QxmgUQ

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