BMF: Frame extraction acceleration- video similarity search with Pinecone

• Bmf-Huggingface

  1 0 5.4 Jupyter Notebook

git clone https://github.com/Joshalphonse/Bmf-Huggingface.git

• examples

  7 390 6.8 Jupyter Notebook

  Analyze the unstructured data with Towhee, such as reverse image search, reverse video search, audio classification, question and answer systems, molecular search, etc. (by towhee-io)

  

! curl -L https://github.com/towhee-io/examples/releases/download/data/reverse_video_search.zip -O ! unzip -q -o reverse_video_search.zip

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• canopy

  16 907 9.7 Python

  Retrieval Augmented Generation (RAG) framework and context engine powered by Pinecone

  

So you might have seen in my last blog post that I showed you how to accelerate video frame extraction using GPU's and Babit multimedia framework. In this blog we are going to improve upon our video frame extractor and create a video similarity search(Reverse video search) utlizing different RAG(Retrival Augemented Gerneation) concepts with Pinecone, the vector database that will help us build knowledgeable AI. Pinecone is designed to perform vector searches effectively. You'll see throughout this blog how we extrapulate vectors from videos to make our search work like a charm. With Pinecone, you can quickly find items in a dataset that are most similar to a query vector, making it handy for tasks like recommendation engines, similar item search, or even detecting duplicate content. It's particularly well-suited for machine learning applications where you deal with high-dimensional data and need fast, accurate similarity search capabilities. Reverse video search works like reverse image search but uses a video to find other videos that are alike. Essentially, you use a video to look for matching ones. While handling videos is generally more complex and the accuracy might not be as good as with other models, the use of AI for video tasks is growing. Reverse video search is really good at finding videos that are connected and can make other video applications better. So why would you want to create a video similarity search app?

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