- This project has following features :
- AWS serverless architecture
- Lambda function integrated with Keras, Tensorflow and Python Libraries.
- User Interface for uploading an image and evaluate the result on different models.
- We created a pipeline using AWS components for an end-to-end application which has the advantage of the scalability and extendable to any deep learning model. Presently it is supported for Faster-RCNN and SSD.
- Important files to look for implementation:
- /lambda/frcnn
- frcnn-detection/lambda_function.py
- frcnn-lambda/service.py
- frcnn-preprocessing/lambda_function.py
- /lambda/ssd
- ssd-detection/lambda_function.py
- ssd-lambda/lambda_function.py
- ssd-preprocessing/lambda_function.py
- /lambda/frcnn
- Python 2.7
- Keras 1.2.1 and Keras 2.0.2
- Tensorflow 1.2.1
- OpenCv 3.1
- Numpy
- Scikit-image
- AWS DynamoDB
- AWS API Gateway
- AWS Lambda functions
- NodeJs 6.1.1