Instructions to use keras-io/monocular-depth-estimation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use keras-io/monocular-depth-estimation with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("keras-io/monocular-depth-estimation") - Notebooks
- Google Colab
- Kaggle
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library_name: keras
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## Model description
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Depth estimation is a crucial step towards inferring scene geometry from 2D images. The goal in monocular depth estimation is to predict the depth value of each pixel or inferring depth information, given only a single RGB image as input.
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## Dataset
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library_name: keras
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## Model description
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Full credits go to: [Vu Minh Chien](https://www.linkedin.com/in/vumichien/)
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Depth estimation is a crucial step towards inferring scene geometry from 2D images. The goal in monocular depth estimation is to predict the depth value of each pixel or inferring depth information, given only a single RGB image as input.
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## Dataset
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