Machine Learning > Core ML Models

Detecting text using Vision built-in model in real-time.

Photo Assessment using Core ML and Metal.

Estimating human pose from a picture for mobile.

Detects the dominant objects present in an image.

Detects the scene of an image from 205 categories such as bedroom, forest, coast etc.

Detects the dominant objects present in an image.

Detects the dominant objects present in an image.

Detects the dominant objects present in an image.

Predict the brand & model of a car.

Recognize what the objects are inside a given image and where they are in the image.

Predict a person's emotion from one's portrait.

Predict handwritten (drawn) digits from images.

Predict positive or negative sentiments from images.

Predict the type of foods from images.

Detect the type of flowers from images.

Detect the artistic style of images.

Predict the location where a picture was taken.

Classifies an image either as NSFW (nude) or SFW (not nude)

Recognizing text using ML Kit built-in model in real-time.

Segment the pixels of a camera frame or image into a predefined set of classes.

Predict the depth from a single image.

Predict the depth from a single image.

Detect nested edges from a color image.

Process a bicubic-scaled anime-style artwork

Predict positive or negative sentiments from sentences.

Classify news articles into 1 of 5 categories.

Detect whether a message is spam.

Gender Classification using DecisionTreeClassifier

Predict personality based on user documents (sentences).

OpenAI GPT-2 Text generation (Core ML 3)

Predicts the exercise, when iPhone is worn on right upper arm.

Recommend an artist based on given location and genre.

Recommend an artist based on given location and genre.

Predicts the most likely next chord based on the entered Chord Progression.

Big list of models in Caffe format.

Another collection of TensorFlow Models.

Score the memorability of pictures.

The aesthetic evaluation of images.

Automatic colorization using deep neural networks.

Estimating a set of tags and extracting semantic feature vectors from given illustrations.

Detecting text in natural image.

Find semantically-meaningful dense correspondences between two input images.

Automatic spoken language identification.

Cloth detection from images.

The prediction of salient areas in images has been traditionally addressed with hand-crafted features.

Detect face from image.

Joint Face Detection and Alignment.

Single image horizon line estimation.