Core ML Models
Build intelligence into your apps using machine learning models from the research community designed for Core ML.
Models are in Core ML format and can be integrated into Xcode projects. You can select different versions of models to optimize for sizes and architectures.
Images
FastViT
Image Classification
A Fast Hybrid Vision Transformer architecture trained to classify the dominant object in a camera frame or image.
A Fast Hybrid Vision Transformer architecture trained to classify the dominant object in a camera frame or image.
Depth Anything V2
Depth Estimation
The Depth Anything model performs monocular depth estimation.
The Depth Anything model performs monocular depth estimation.
DETR Resnet50 Semantic Segmentation
Semantic Segmentation
The DEtection TRansformer (DETR) model, trained for object detection and panoptic segmentation, configured to return semantic segmentation masks.
The DEtection TRansformer (DETR) model, trained for object detection and panoptic segmentation, configured to return semantic segmentation masks.
MNIST
Drawing Classification
Classify a single handwritten digit (supports digits 0-9).
Classify a single handwritten digit (supports digits 0-9).
UpdatableDrawingClassifier
Drawing Classification
Drawing classifier that learns to recognize new drawings based on a K-Nearest Neighbors model (KNN).
Drawing classifier that learns to recognize new drawings based on a K-Nearest Neighbors model (KNN).
MobileNetV2
Image Classification
The MobileNetv2 architecture trained to classify the dominant object in a camera frame or image.
The MobileNetv2 architecture trained to classify the dominant object in a camera frame or image.
Resnet50
Image Classification
A Residual Neural Network that will classify the dominant object in a camera frame or image.
A Residual Neural Network that will classify the dominant object in a camera frame or image.
DeeplabV3
Image Segmentation
Segment the pixels of a camera frame or image into a predefined set of classes.
Segment the pixels of a camera frame or image into a predefined set of classes.
YOLOv3
Object Detection
Locate and classify 80 different types of objects present in a camera frame or image.
Locate and classify 80 different types of objects present in a camera frame or image.
YOLOv3-Tiny
Object Detection
Locate and classify 80 different types of objects present in a camera frame or image.
Locate and classify 80 different types of objects present in a camera frame or image.
Text
BERT-SQuAD
Question Answering
Find answers to questions about paragraphs of text.
Find answers to questions about paragraphs of text.