dolg-tensorflow's Introduction

DOLG-TensorFlow

This is an unofficial implementation of Deep Orthogonal Fusion of Local and Global Features (DOLG) in TensorFlow 2 (Keras). Paper. In this repository, the following architechture has been implemented. Details here.

Prerequisites

TensorFlow 2.6 
TensorFlow Addons

Run

First, reset the config file, config.py

BATCH_SIZE  = 10
IMG_SIZE    = 768
CHANNELS    = 3
LR = 0.003
mixed_precision = False

Next, build the DOLG model with EfficientNetB5.

from config import IMG_SIZE, CHANNELS
from model.DOLG import DOLGNet 

print(model(tf.ones((1, IMG_SIZE, IMG_SIZE, CHANNELS)))[0].shape)
display(tf.keras.utils.plot_model(model.build_graph(), 
                                  show_shapes=True, 
                                  show_layer_names=True,
                                  expand_nested=False))

For better flexibility, please see the following code example section.

Code Example

The DOLG concept can be integrated into any computer vision models i.e. NFNet, ResNeSt, or EfficietNet. Here are some end-to-end code examples.

To Do

Implement Sub-center Arcface Head.
Fix GeM issue.
tf-keras-vis

Citations

@misc{yang2021dolg,
      title={DOLG: Single-Stage Image Retrieval with Deep Orthogonal 
                                         Fusion of Local and Global Features}, 
      author={Min Yang and Dongliang He and Miao Fan and Baorong Shi and 
                                        Xuetong Xue and Fu Li and Errui Ding and Jizhou Huang},
      year={2021},
      eprint={2108.02927},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

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