couturemopa.blogg.se - 8 section classification folder

This tutorial uses a dataset of about 3,700 photos of flowers. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly. 02:27:15.406679: W tensorflow/compiler/tf2tensorrt/utils/py_:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. 02:27:15.406662: W tensorflow/compiler/xla/stream_executor/platform/default/dso_:64] Could not load dynamic library 'libnvinfer_plugin.so.7' dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory 02:27:15.406562: W tensorflow/compiler/xla/stream_executor/platform/default/dso_:64] Could not load dynamic library 'libnvinfer.so.7' dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory Import TensorFlow and other necessary libraries: import matplotlib.pyplot as pltįrom import Sequential In addition, the notebook demonstrates how to convert a saved model to a TensorFlow Lite model for on-device machine learning on mobile, embedded, and IoT devices.

Improve the model and repeat the process.

This tutorial follows a basic machine learning workflow:

Identifying overfitting and applying techniques to mitigate it, including data augmentation and dropout.

Efficiently loading a dataset off disk.

This tutorial shows how to classify images of flowers using a tf.keras.Sequential model and load data using tf._dataset_from_directory.