- Trending Categories
- Data Structure
- Operating System
- C Programming
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
How can Tensorflow be used to run the classifier on a batch of images?
TensorFlow be used to run the classifier on a batch of images using the ‘classifier’ class, and ‘predict’ method.
A neural network that contains at least one layer is known as a convolutional layer. We can use the Convolutional Neural Network to build learning model.
The intuition behind transfer learning for image classification is, if a model is trained on a large and general dataset, this model can be used to effectively serve as a generic model for the visual world. It would have learned the feature maps, which means the user won’t have to start from scratch by training a large model on a large dataset.
TensorFlow Hub is a repository that contains pre-trained TensorFlow models. TensorFlow can be used to fine-tune learning models.
We will understand how to use models from TensorFlow Hub with tf.keras, use an image classification model from TensorFlow Hub. Once this is done, transfer learning can be performed to fine-tune a model for customized image classes. This is done by using a pretrained classifier model to take an image and predict what it is. This can be done without needing any training.
We are using the Google Colaboratory to run the below code. Google Colab or Colaboratory helps run Python code over the browser and requires zero configuration and free access to GPUs (Graphical Processing Units). Colaboratory has been built on top of Jupyter Notebook.
print("Classifier is run on batch of images") result_batch = classifier.predict(train_ds) predicted_class_names = imagenet_labels[np.argmax(result_batch, axis=-1)] print("The class names are predicted") print(predicted_class_names)
Classifier is run on batch of images The class names are predicted ["yellow lady's slipper" 'daisy' 'sea urchin' ... 'vault' 'bee' 'barn spider']
- The classifier is run on batch of image.
- The class names which are predicted are displayed on the console.
- How can Tensorflow be used for transfer learning with TF Hub, to download image net classifier?
- How can Tensorflow be used to add a batch dimension and pass the image to the model using Python?
- How can decision tree be used to construct a classifier in Python?
- How can Tensorflow be used to visualize the results of the model?
- How can Tensorflow be used to export the model so that it can be used later?
- How can Tensorflow be used to standardize the flower dataset?
- How can Tensorflow be used to get the variables in a layer?
- How can Tensorflow be used to implement custom layers?
- How can Tensorflow be used to add dense layers on top using Python?
- How can Tensorflow and pre-trained model be used to convert images from one dimension to another?
- How can Tensorflow and Tensorflow text be used to tokenize string data?
- How can Tensorflow be used to configure the dataset for performance?
- How can Tensorflow be used to visualize the data using Python?
- How can Tensorflow be used to standardize the data using Python?
- How can Tensorflow be used to compile the model using Python?