Instructions to use keras/dfine_medium_obj2coco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/dfine_medium_obj2coco with KerasHub:
import keras_hub # Create a ObjectDetector model task = keras_hub.models.ObjectDetector.from_preset("hf://keras/dfine_medium_obj2coco")import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/dfine_medium_obj2coco") - Keras
How to use keras/dfine_medium_obj2coco with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://keras/dfine_medium_obj2coco") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c90839418001078df72dadd3d1ff63e88d97fed913f4ab4ea3df2b33c2417a2
- Size of remote file:
- 80.9 MB
- SHA256:
- a89658bd6d7fdc0292dbaa9863eaee9d711617830df007b72dbd32444ce99d73
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