![]() For more information on configuration options, Mode, display names locale, max number of results, confidence threshold,Ĭategory allow list, and deny list. TheĬreate_from_options function accepts configuration options including running ![]() Use the create_from_options function to create the task. Specify the path of the model within the Model Name parameter, as shown below: base_options = BaseOptions(model_asset_path=model_path) model_path = '/absolute/path/to/efficientnet_lite0_int8_2.tflite' Select and download a model, and then store it in a local directory. For more information on available trained models for Image Classifier, see The MediaPipe Image Classifier task requires a trained model that is compatible with this Import the following classes to access the Image Classifier task functions: import mediapipe as mpįrom import vision With the following: $ python -m pip install mediapipe The Image Classifier task the mediapipe pip package. Attention: This MediaPipe Solutions Preview is an early release. Setting up your development environment for using MediaPipe tasks, including ![]() This section describes key steps for setting up your development environment andĬode projects specifically to use Image Classifier. Image Classifier example code using just your web browser. Started on building your own image classifier. This code helps you test this task and get The example code for Image Classifier provides a complete implementation of this You can see this task in action by viewing the Web demo.įor more information about the capabilities, models, and configuration options These instructions show you how to use the Image Classifier You can use this task to identify what an image represents among a set of categories defined at training time. The MediaPipe Image Classifier task lets you perform classification on images.
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