"This notebook provides basic example code to create, build, and run [MoViNets (Mobile Video Networks)](https://arxiv.org/pdf/2103.11511.pdf). Models use TF Keras and support inference in TF 1 and TF 2. Pretrained models are provided by [TensorFlow Hub](https://tfhub.dev/google/collections/movinet/), trained on [Kinetics 600](https://deepmind.com/research/open-source/kinetics) for video action classification."
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"## Setup\n",
"\n",
"It is recommended to run the models using GPUs or TPUs.\n",
"\n",
"To select a GPU/TPU in Colab, select `Runtime \u003e Change runtime type \u003e Hardware accelerator` dropdown in the top menu.\n",
"\n",
"### Install the TensorFlow Model Garden pip package\n",
"\n",
"- tf-models-official is the stable Model Garden package. Note that it may not include the latest changes in the tensorflow_models github repo.\n",
"- To include latest changes, you may install tf-models-nightly, which is the nightly Model Garden package created daily automatically.\n",
"pip will install all models and dependencies automatically.\n",
"\n",
"Install the [mediapy](https://github.com/google/mediapy) package for visualizing images/videos."
"### Build MoViNet-A0-Base and Load Pretrained Weights"
]
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"Here we create a MoViNet model using the open source code provided in [tensorflow/models](https://github.com/tensorflow/models) and load the pretrained weights. Here we freeze the all layers except the final classifier head to speed up fine-tuning."
