---
library_name: keras-hub
---
This is a [`DeepLabV3` model](https://keras.io/api/keras_hub/models/deep_lab_v3) uploaded using the KerasHub library and can be used with JAX, TensorFlow, and PyTorch backends.
This model is related to a `ImageSegmenter` task.

Model config:
* **name:** deep_lab_v3_backbone
* **trainable:** True
* **image_encoder:** {'module': 'keras_hub.src.models.resnet.resnet_backbone', 'class_name': 'ResNetBackbone', 'config': {'name': 'res_net_backbone', 'trainable': True, 'input_conv_filters': [64], 'input_conv_kernel_sizes': [7], 'stackwise_num_filters': [64, 128, 256, 512], 'stackwise_num_blocks': [3, 4, 6, 3], 'stackwise_num_strides': [1, 2, 2, 2], 'block_type': 'bottleneck_block', 'use_pre_activation': False, 'image_shape': [None, None, 3]}, 'registered_name': 'keras_hub>ResNetBackbone'}
* **projection_filters:** 48
* **dilation_rates:** [6, 12, 18]
* **upsampling_size:** 8
* **low_level_feature_key:** P2
* **spatial_pyramid_pooling_key:** P5
* **image_shape:** [None, None, 3]

This model card has been generated automatically and should be completed by the model author. See [Model Cards documentation](https://huggingface.co./docs/hub/model-cards) for more information.