Kubeflow Pipeline Using YoloV3 TF2 Model

This repository contains python scripts for creating Kubeflow pipeline configuration file using YoloV3 TF2 model.

Usage

Install kfp

pip install kfp

Create components and connect them into a pipeline

python3 run.py

Upload created pipeline configuration file to Kubeflow

Find the pipeline.yaml file inside pipeline-files-yaml directory and upload it to Kubeflow.

Provide necessary pipeline parameters

train_dataset_url: Google Drive url to the tfrecord file for train dataset
val_dataset_url: Google Drive url to the tfrecord file for val dataset
checkpoint_url: Google Drive url to the pretrained checkpoint directory
checkpoint_name: name of the checkpoint file inside the checkpoint directory
test_img_url: Google Drive url to the image to be used for the test step
model_size: size of the YoloV3 model
num_classes: number of the classes of the labels
num_epochs: number of epochs for training
class_names: list of class labels

References

• yolov3_minimal