Instructions to use keras/basnet_duts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/basnet_duts with KerasHub:
import keras_hub # Create a ImageSegmenter model task = keras_hub.models.ImageSegmenter.from_preset("hf://keras/basnet_duts")import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/basnet_duts") - Keras
How to use keras/basnet_duts 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/basnet_duts") - Notebooks
- Google Colab
- Kaggle
File size: 506 Bytes
2d94dbc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"module": "keras_hub.src.models.basnet.basnet_preprocessor",
"class_name": "BASNetPreprocessor",
"config": {
"name": "bas_net_preprocessor",
"trainable": true,
"dtype": {
"module": "keras",
"class_name": "DTypePolicy",
"config": {
"name": "float32"
},
"registered_name": null
},
"config_file": "preprocessor.json"
},
"registered_name": "keras_hub>BASNetPreprocessor"
} |