aws-samples/zero-shot-learning-object-detection-and-segmentation

Zero Shot Learning Object Detection and Segmentation

This repository contains code and resources for performing zero-shot object detection and segmentation using deep learning techniques. Zero-shot learning enables the model to detect and segment objects from classes that were not seen during training, by leveraging semantic information and transferring knowledge from seen classes.

AWS Architecture:

AWS CloudFormation Stack Creation

The AWS CloudFormation Stack can be created using 2 methods: (1) Using Template or (2) Using AWS CDK. Both the methods are described as follows:

1. [WIP] Create Stack using AWS CloudFormation:

   • Choose Launch Stack and (if prompted) log into your AWS account:
   • Select a unique Stack Name, ackowledge creation of IAM resources, create the stack and wait for a few minutes for it to be successfully deployed

2. Using AWS CLI:

   • If AWS CLI is installed, use it to create the CloudFormation Stack:

   $ git clone https://github.com/aws-samples/zero-shot-learning-object-detection-and-segmentation
   $ cd zero-shot-learning-object-detection-and-segmentation
   $ aws cloudformation create-stack \
       --stack-name ZSL-STACK \
       --template-body file://zsl-cdk.yaml \
       --capabilities CAPABILITY_IAM
   

Steps to run:

1. Once the Stack is created, navigate to SageMaker in AWS Console
2. From SageMaker -> Notebooks -> Open ZSL Notebook
3. Follow the steps in the Notebook

Security

See CONTRIBUTING for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file.

Contributors

• Fabian Benitez-Quiroz
• Junjie Tang
• Romil Shah