BigML Release: Image Processing
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This new release brings Image Processing to the BigML platform, a feature that enhances our offering to solve image data-driven business problems with remarkable ease of use. Because BigML treats images as any other data type, this unique implementation allows you to easily use image data alongside text, categorical, numeric, date-time, and items data types as input to create any Machine Learning model available in our platform, both supervised and unsupervised. Now, it is easier than ever to solve a wide variety of computer vision and image classification use cases in a single platform: label your image data, train and evaluate your models, make predictions, and automate your end-to-end Machine Learning workflows. As with any other BigML feature, Image Processing is available from the BigML Dashboard, API, and WhizzML, and it can be applied to solve use cases such as medical image analysis, visual product search, security surveillance, and vehicle damage detection, among others.
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BigML Release: Image Processing
- 1. BigML Image Processing Release
- 2. BigML Release: Image Processing BigML, Inc 2 Image Processing Release Webinar Enter questions into chat box. We will answer some via chat and others at the end of the session. QUESTIONS info@bigml.com @bigmlcom Atakan Cetinsoy VP of Predictive Applications. MODERATOR Charles Parker Ph.D. VP of Machine Learning Algorithms. SPEAKER https://bigml.com/releases/image-processing RESOURCES
- 3. BigML Release: Image Processing BigML, Inc 3 BigML Image Processing • ALL the tasks for generating insights from image data ON A SINGLE PLATFORM: From labeling to inference, evaluation, and predictions. • Streamlined image dataset management with composite sources. • Comprehensive feature extraction options to feed any algorithm. • Pre-trained CNNs for classification and regression. • Automatic handling of infrastructure concerns. • Your choice: Code and no code. Solving image data-driven business problems with remarkable ease of use
- 4. IMAGE PROCESSING Dr. Charles Parker VP Algorithms, BigML, Inc
- 5. BigML Release: Image Processing BigML, Inc In This Webinar Some examples of full applications using image processing 1 2 3 4 A simple image classifier in BigML Image data management on the platform Some non-trivial examples of image processing problems 5
- 6. BigML Release: Image Processing BigML, Inc (A Few) Applications of Computer Vision • Ecological: Land use classification, ecosystem health management, animal identification. • Transportation: Tollway monitoring, anomalous event detection, automated billing. • Medical: Medical image classification, segmentation for disease identification. • Finance: Automated check reading, form classification, security, insurance claim estimation. 6
- 7. BigML Release: Image Processing BigML, Inc 7 Application #1 - License Plate Monitoring • Globalvia tollway monitoring: • Object detection to pull plate image from car. • Object detection for pulling characters / symbols from plate. • Classifier for deciding what state the plate is from. • The combination of all of the models with bespoke business rules lead to a successful system.
- 8. BigML Release: Image Processing BigML, Inc 8 Application #2 - Marksmanship Training • Accushoot Marksmanship Training Application: • Object detection: Target detection, gun detection. • Image Classification: Grip classification, gun classification, target classification, impact classification. • Other models: Classifier for shooting phases (drawing, shooting, holstering, reloading). • Again, making a great application with computer vision often takes more than one model.
- 9. BigML Release: Image Processing BigML, Inc 9 Beat The Machine!
- 10. BigML Release: Image Processing BigML, Inc 10 Beat The Machine!
- 11. BigML Release: Image Processing BigML, Inc 11 Pneumonia Normal Beat The Machine!
- 12. BigML Release: Image Processing BigML, Inc 12 The More Things Change . . . Training Dataset Test Dataset Zip fi le with Images Train Evaluate
- 13. BigML Release: Image Processing BigML, Inc Radiology Example 13
- 14. BigML Release: Image Processing BigML, Inc 14 How is BigML Different? • Most competitors that provide learning over images focus on a mapping of image -> class, but there’s so much more! • On the input side: • We can extract meaningful features rather than using the raw pixel data. • We can combine the image with other features (captions, geo-coordinates, etc.). • On the output side: • We can do regression. • We can do unsupervised learning. Image processing on BigML gives the user the flexibility, traceability, and scalability that they get with any other datatype.
- 15. BigML Release: Image Processing BigML, Inc So Deep Learning, right? • That’s an important part of our offering, but not the only part. • Yes, if you do select a BigML deepnet and have image data, you’ll get a CNN. • We try several common architectures and select the best one. • Deep learning is great, and is very often the best thing available, but sometimes it isn’t. 15
- 16. BigML Release: Image Processing BigML, Inc 16 Main Advantages of BigML • User labeling and image dataset management with composite sources. • A variety of image feature extraction techniques that can be used to feed any BigML algorithm. • Full training of convolutional neural networks for classification and regression. • Handling of infrastructure concerns for image training (which is not trivial or cheap).
- 17. BigML Release: Image Processing BigML, Inc 17 Composing Image Datasets • Zip files are nice, but what if you need to compose an image dataset, and add to it incrementally? • For this we offer image labeling and composite sources: • A composite source is a source that contains a bunch of sub-sources (individual images). • While the composite source is open, you can add images, or labels to images, which preserves immutability.
- 18. BigML Release: Image Processing BigML, Inc Image Labeling 18
- 19. BigML Release: Image Processing BigML, Inc 19 Adding Metadata • What if there was other information? • GeoCoordinates where the photo was taken. • Approximate altitude. • Adding that information with BigML is as simple as editing the CSV. • The image is just some of the features in the instance.
- 20. BigML Release: Image Processing BigML, Inc Bird Image Dataset 20
- 21. BigML Release: Image Processing BigML, Inc $ Car image Features Regression model 21 Applications: Insurance Claim Estimate • Suppose you’re an auto insurance company. • Develop software where you have customer take a picture of the damage to estimate the severity of the claim. • Simple regression problem, image -> $
- 22. BigML Release: Image Processing BigML, Inc $ Front image Features Side image Features Brake pedal State Steering wheel Angle 22 • Now, what if you have them take both a front and side image? • What if you have telemetry data from the car? Applications: Insurance Claim Estimate
- 23. BigML Release: Image Processing BigML, Inc $ Word counts Accelerometer Screen on? Front image Features Side image Features Brake pedal State Steering wheel Angle 23 • How about the text of the police report? • User’s mobile phone activity in the moments before the crash? Applications: Insurance Claim Estimate
- 24. BigML Release: Image Processing BigML, Inc 24 Unsupervised Learning • How do you do anomaly detection or clustering with images? • Change each image to a (somewhat) short vector of numbers. • Treat each of these vectors as a set of numeric features for each instance. • These features can be combined with any other feature type. • Deepnets do this implicitly, but other ML algorithms require an explicit choice. • By default, we choose something that “often works”, but this is an opportunity to encode domain knowledge.
- 25. BigML Release: Image Processing BigML, Inc Anomaly Detection 25
- 26. BigML Release: Image Processing BigML, Inc Simple Model More Complex Most Complex Reject Pass Pass Accept 26 Model Cascade • Those features can feed supervised models, too, and may be much faster. • Use an increasingly accurate and increasingly expensive chain of models as “gates”: • Use a model that’s fast, has near-perfect recall, but poor precision. • If something passes the first model, pass it on to a fancier one with better precision. • Repeat as necessary. • In this way, only a few instances require the most time consuming prediction. Reject Reject
- 27. BigML Release: Image Processing BigML, Inc 27 Image Processing the BigML Way • Everything is immutable, traceable, and composable • All of your models are always available and never change • You can always see exactly the training data that generated the model • Everything is available via the API and downloadable • Image dataset creation and labeling can be done via the API • Models are live via API endpoint as soon as they are created • Models can be downloaded and run locally
- 28. BigML Release: Image Processing BigML, Inc 28 Okay, Images are A Little Bit Special • I’ve glossed over the fact that there are some problems that are specific to images: • Object detection • Image segmentation • Superresolution • Our initial release won’t support these functionalities immediately, but object detection is coming. • Accushoot, Globalvia, and several other customers are using the beta version of object detection right now.