AutoML library for deep learning. Contribute to keras-team/autokeras development by creating an account on GitHub.

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autokeras.ImageClassifier(num_classes=None, multi_label=False, loss=None, metrics=None, project_name="image_classifier", max_trials=100, directory=None, objective="val_loss", tuner=None, overwrite=False, seed=None, max_model_size=None, **kwargs) AutoKeras image classification class. ImageClassifier is the Autokeras image classification class. To initialize, the max_trials parameter is set to 200, meaning 200 different Keras models will be tried (default value is 100). The The AutoKeras ImageClassifier is quite flexible for the data format. For the image, it accepts data formats both with and without the channel dimension. In the spirit of Keras, AutoKeras provides an easy-to-use interface for different tasks, such as image classification, structured data classification or regression, and more.

Autokeras image classification

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Se hela listan på autokeras.com autokeras. ImageClassifier (num_classes = None, multi_label = False, loss = None, metrics = None, project_name = "image_classifier", max_trials = 100, directory = None, objective = "val_loss", tuner = None, overwrite = False, seed = None, max_model_size = None, ** kwargs) ImageClassifier is the Autokeras image classification class.

Image classification is one of the most important applications of computer vision. Its applications ranges from classifying objects in self driving cars to identifying blood cells in healthcare industry, from identifying defective items in manufacturing industry to build a system that can classify persons wearing masks or not.

If you are dealing with multi-task or multi-modal dataset, you can refer to this tutorial for details. Customized Model. Follow this tutorial, to use AutoKeras building blocks to Image Classification Image Regression inputs Union[autokeras.Input, List[autokeras.Input]]: A list of Node instances. The input node(s) of the AutoModel. The AutoKeras ImageClassifier is quite flexible for the data format. For the image, it accepts data formats both with and without the channel dimension. Description AutoKeras image classification class.

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Autokeras image classification

Google’s AutoML is a new cloud software suite of Machine Learning tools. It ’ s based on Google’s state-of-the-art research in image recognition called Neural Architecture Search (NAS). NAS is basically an algorithm that, given your specific dataset, searches for the most optimal neural network to perform a certain task on that dataset. AutoML with AutoKeras. Neural networks to design neural networks.

This is an example of using AutoKeras on image classification issues.
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from autokeras.image.image_supervised import ImageClassifier As the ImageClassifier is the only working classifier for version 0.4, it is used here for all data 

AutoKeras only support Python 3. If Structured Data Classification. Structured Data Regression. Coming Soon: Time Series Forcasting, Object Detection, Image Segmentation. Multi-Task and Multi-Modal Data. If you are dealing with multi-task or multi-modal dataset, you can refer to this tutorial for details. Customized Model.

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If None, it will be inferred from the: data. multi_label: Boolean.