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If you are looking for more exciting solutions for iOS and Android apps, you can also check out Fritz AI. It gives you flexibility in how much you want to be invested in ML model development ― you can train custom models in the Studio or use pre-trained models. In the program, you can create or import your own datasets, monitor the model’s performance, and re-train it. If you do Snapchat lens development, this tool will help you add no-code machine learning to your augmented reality filters.
Fritz AI is the machine learning platform for iOS, Android, and SnapML in Lens Studio. Use the model development Studio to train custom solutions, or jump right in with pre-trained models and projects.
Create Datasets
On-device Dataset Collection
Synthetic Data Generation
Dataset Import
Train
Performance Benchmarking
Model Retraining
Model Training
Deploy
Real-world Data Collection
Model Delivery Network
Model Protection
Improve
Real-world Performance Data
Model Delivery Network
Device Analytics
Improve
Create solution without coding
Datasets
Create ready-to-train image datasets with accurate labels to be used in the training of models for mobile deployment.
- Datset Generator – Synthetic data creation
- Dataset Collection System – Real-world device data
- Dataset Import – Upload and annotate images
Train
Train production-ready mobile machine learning models from datasets – without any code.
- Benchmark on-device model performance without deploying
- Deploy model versions to test devices while training
- Track training configurations and hyperparameters
Deploy
Deploy the right model to the right device. Convert and protect models across platforms, without losing accuracy or performance.
- Native cross-platform mobile SDKs
- Protect models from attackers and copycat apps
- Model Delivery Network – Live model updating and edge-caching
Improve
Improve deployed models running on-device. Collect real-world data, retrain models, and push improvements live.
- Dataset Collection System – Real-world device data
- Analyze performance by platform, device and processor
- Test and experiment with model versions
Available Models
Fritz AI Studio supports these model architectures for a wide range of solutions.
- Image Segmentation
- Object Detection
- Image Labeling
- Rigid 3D Pose Estimation
- Custom Pose Estimation
- Style Transfer
Avoiding network round-trips and data shuffling to the cloud results in brilliant performance.
Scalable
ML on-device performs consistently on a few devices or a few million, unlike cloud-based solutions.
High Value
Cloud-based providers of ML are expensive. Using local on-device processing saves money.
Secure
Personal and identifying information does not need to be sent to the cloud, ever.
Available Offline
All Fritz AI solutions work fully on-device and offline for maximum portability (even on airplane mode).
Local
From photos to current whereabouts, useful data can stay entirely local and never touch the cloud.
Image Labeling
Recognize people, places, and things with hundreds of labels.
Object Detection
Identify and track objects within an image or video.
Image Segmentation
Recognize people and objects to separate them from the background.
Style Transfer
Turn photos and videos into unique masterpieces based on real art.
https://www.fritz.ai/pricing/