![]() See Create and train a custom model and go to the section on selecting/importing a COCO file-you can follow the guide from there to the end. Once your COCO file is verified, you're ready to import it to your model customization project. Purpose = Purpose.TRAINING # or Purpose.EVALUATIONĬheck_coco_annotation_file(json.loads(coco_file_path.read_text()), annotation_kind, purpose) from cognitive_service_vision_model_customization_python_samples import check_coco_annotation_file, AnnotationKind, PurposeĬoco_file_path = pathlib.Path("")Īnnotation_kind = AnnotationKind.MULTICLASS_CLASSIFICATION # or AnnotationKind.OBJECT_DETECTION The installation Untitled0420 uses fishing lines as its major component, which is related to the philosophy writing that I developed in my senior project. You can either enter this code in a Python script, or run the Jupyter Notebook on a compatible platform. Then, run the following python code to check the file's format. ![]() First, install the python samples package from the command line: pip install cognitive-service-vision-model-customization-python-samples This notebook demonstrates how to check if the format of your annotation file is correct.
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