TF Microcontroller Challenge: Droop, There It Is

Repo for this project here! A seasoned gardener can diagnose plant stress by visual inspection. For our entry to the Tensorflow Microcontroller Challenge, we chose to highlight the issue of water conservation while pushing the limits of computer vision applications. Our submission, dubbed “Droop, There It Is” builds on previous work to identify droopy, wilted plants. Drought stress in plants typically manifests as visually discernible drooping and wilting, also known as plasmolysis, indicating low turgidity or water pressure....

 · 5 min · Terry Rodriguez & Salma Mayorquin

Movie Trailer Similarity for Recommendation

Intro In a previous post, we discussed scraping a movie poster image corpus with genre labels from imdb and learning image similarity models using tensorflow. In this post, we extend this idea to recommend movie trailers based on audio-visual similarity. Data We started by scraping IMDB for movie trailers and their genre tags as labels. Using Scrapy, it is easy to build a text file of video links to then download with youtube-dl....

 · 4 min · Terry Rodriguez & Salma Mayorquin

Scraping Smarter with Content Filtering

Scrapy is a powerful web scraping framework and essential tool for building machine learning datasets. For sites with simple structure, scrapy makes it easy to curate a dataset after launching a spider. Check out the tutorials in scrapy’s documentation. To train a poster similarity model, we first gathered hundreds of thousands of movie posters. More concretely, when scraping IMDb.com, we may be interested in gathering posters from <img> tags under <div> tags with the class "poster"....

 · 3 min · Terry Rodriguez & Salma Mayorquin

Movie Poster Similarity for Recommendation

The use of streaming services has sharply increased over this past year. Many video streaming platforms prominently feature theatrical posters in content representation. As movie posters are designed to signal theme, genre and era, this representation strongly influences a user’s propensity to watch the title. Domain experts have remarked on how poster elements can convey an emotion or capture attention. Exploring this thesis, Netflix conducted a UX study, using eye tracking to find that 91% of titles are rejected after roughly 1 second of view time....

 · 4 min · Terry Rodriguez & Salma Mayorquin

TF-Recommenders & Kubernetes for flexible RecSys Model Development & Deployment

Introducing TF-Recommenders Recently, Google open sourced a Keras API for building recommender systems called TF-Recommenders. TF-Recommenders is flexible, making it easy to integrate heterogeneous signals like implicit ratings from user interactions, content embeddings, or real-time context info. This module also introduces losses specialized for ranking and retrieval which can be combined to benefit from multi-task learning. The developers emphasize the ease-of-use in research, as well as the robustness for deployment in web-scale applications....

 · 5 min · Terry Rodriguez & Salma Mayorquin