Train Custom Image Classification Model using Google Inception API

The previous blog was shared with you on how to compile to use TensorFlow to classified Pre-trained images. Now I have tried to train custom images, and the results get look accurate!

1. Open Comand Prompt and then key in"git clone https://github.com/googlecodelabs/tensorflow-for-poets-2".
2. Create folder fruit inside"TensorFlow-for-poets-2\tf_files". Then create 2 different fruit folder, example:

3. Now can download dataset by google Image durian and durian belanda, then save into the related folder,
3. Open Command Prompt inside this folder "TensorFlow-for-poets-2".
4. Then start train the data set by key in: python scripts/retrain.py --output_graph=tf_files/retrained_graph.pb --output_labels=tf_files/retrained_labels.txt --image_dir=tf_files/fruit.

5. After model train complete. Then we can start test to verify our train model. So download another Durian image then put input Image: C:\Users\csheng\tensorflow-for-poets-2\d1.jpeg

6. Enter command "python scripts/label_image.py --image d1.JPG" to start verify.

7. Output correct results Result! Done

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Fixed issues:AttributeError: module 'tensorflow' has no attribute 'Session'

The previous blog, Train Custom Image Classification Model using Google Inception API was shared with you on how to train and prepare your data set. Some reader feedback that they are facing some issues with data set compilation. The issues mentioned were: AttributeError: module 'TensorFlow' has no attribute 'Session'. To fix these issues, you only need to reinstall tensorflow-gpu 1.15.0: pip3 install -- upgrade -- force - reinstall tensorflow - gpu == 1.15 . 0 more info: stack overflow hwerwerTrain Custom Image Classification Model using Google Inception API Train Custom Image Classification Model using Google Inception API

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