How to test classic sample flowers

TensorFlow General Discussion
1

I new in TF, I tried the classic flowers recognition sample:

I replicate this in PyCharm and it works but I dont’ understand how to test this script passing some real flowers picture to test this in real world.

Thank in advance

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2

You can follow this tutorial to get an idea. Go through the particular section I linked and if there’s any doubt, let me know.

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3

If you want to play with this on your Android device camera you could try to follow this tutorial:

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Many thanks for info.
I’m trying to create a custom classification using my set of images but I’m getting lost in hundreds of examples all different each other. :grinning:

Regards

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Hi @Paolo_Pini You can try tf.keras.Model.predict as in name_of_your_model.predict(...) (be mindful of tensor shapes).

Examples:

  1. Image classification  |  TensorFlow Core

Predict on new data

Finally, let’s use our model to classify an image that wasn’t included in the training or validation sets.

…

sunflower_url = "https://storage.googleapis.com/download.tensorflow.org/example_images/592px-Red_sunflower.jpg"
sunflower_path = tf.keras.utils.get_file('Red_sunflower', origin=sunflower_url)

img = keras.preprocessing.image.load_img(
    sunflower_path, target_size=(img_height, img_width)
)
img_array = keras.preprocessing.image.img_to_array(img)
img_array = tf.expand_dims(img_array, 0) # Create a batch

predictions = model.predict(img_array)
...
  1. Writing your own callbacks  |  TensorFlow Core

Now, define a simple custom callback that logs:

  • When fit/evaluate/predict starts & ends
  • When each epoch starts & ends
  • When each training batch starts & ends
  • When each evaluation (test) batch starts & ends
  • When each inference (prediction) batch starts & ends
    …
class CustomCallback(keras.callbacks.Callback):
  ...
...
res = model.predict(x_test, batch_size=128, callbacks=[CustomCallback()])