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

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#tensorflow #deep-learning