Lab 9&10 - PoojaShekhar/CS5543-Real-Time-Big-Data-Analytics--Lab-assignments GitHub Wiki

Development of a Distributed/Real-Time Image (or Audio or Video) Classification Application related to your project following the similar workflow shown in Tutorial 10.

  • Client: Image Feature Extraction & Recognition Application - Client/Kafka/MongoDB The url below shows mainframes extracted Extracted MainFrames

  • Spark: Image Classification (Training: Model Building & Evaluation) - Kafka/Spark/MongDB Features aster extraction from mainframes was sent to Spark engine ,Decision Model was built.It was parsed and then used as model in the Client end.

  • Storm: Real-time Image Recognition (Testing: Recognition) - Kafka/Storm/MongDB Below diagram shows kafkaSpout consuming messages from kafkaProducer.Each tuples were sent to the bolts Man,Home,Car.And decison of each tuple was sent to mongodb.The screenshot shows the same.After which the newly extracted mainframes were annotated using the model. KafkaSpout

Visualization of Storm Toplogy Topology

mLab

Annotated Car