Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Paper • 1802.02611 • Published
How to use geekyrakshit/DeepLabV3-Plus with Keras:
# Available backend options are: "jax", "torch", "tensorflow".
import os
os.environ["KERAS_BACKEND"] = "jax"
import keras
model = keras.saving.load_model("hf://geekyrakshit/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