Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Paper • 1802.02611 • Published
DeepLabV3-Plus
Keras implementation of the DeepLabV3+ model as proposed by the paper Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation(ECCV 2018).
The models were trained on the fine-annotations set of the Cityscapes dataset for creating presets for this PR on the keras-cv repository.
Weights & Biases Dashboard: https://wandb.ai/geekyrakshit/deeplabv3-keras-cv
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# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://geekyrakshit/DeepLabV3-Plus")