cocoa-ai / Flowersvisiondemo
Licence: mit
πΈ iOS11 demo application for flower classification.
Stars: β 90
Projects that are alternatives of or similar to Flowersvisiondemo
CarLens-iOS
CarLens - Recognize and Collect Cars
Stars: β 124 (+37.78%)
Mutual labels: vision, coreml
Vision CoreML-App
This app predicts the age of a person from the picture input using camera or photos gallery. The app uses Core ML framework of iOS for the predictions. The Vision library of CoreML is used here. The trained model fed to the system is AgeNet.
Stars: β 15 (-83.33%)
Mutual labels: vision, coreml
CustomVisionMicrosoftToCoreMLDemoApp
This app recognises 3 hand signs - fist, high five and victory hand [ rock, paper, scissors basically :) ] with live feed camera. It uses a HandSigns.mlmodel which has been trained using Custom Vision from Microsoft.
Stars: β 25 (-72.22%)
Mutual labels: vision, coreml
Cocoaai
π€ The Cocoa Artificial Intelligence Lab
Stars: β 134 (+48.89%)
Mutual labels: coreml, vision
Liooon Not A Liooon Classifier
A troll app to check if an object seen by your camera is a lion. Uses iOS CoreML, Vision APIs
Stars: β 11 (-87.78%)
Mutual labels: coreml, vision
SentimentVisionDemo
π
iOS11 demo application for visual sentiment prediction.
Stars: β 34 (-62.22%)
Mutual labels: vision, coreml
Facesvisiondemo
π iOS11 demo application for age and gender classification of facial images.
Stars: β 273 (+203.33%)
Mutual labels: coreml, vision
Iowncode
A curated collection of iOS, ML, AR resources sprinkled with some UI additions
Stars: β 499 (+454.44%)
Mutual labels: coreml, vision
Ios 11 By Examples
π¨π»βπ» Examples of new iOS 11 APIs
Stars: β 3,327 (+3596.67%)
Mutual labels: coreml, vision
Chineseidcardocr
[Deprecated] π¨π³δΈε½δΊδ»£θΊ«δ»½θ―ε
ε¦θ―ε«
Stars: β 1,015 (+1027.78%)
Mutual labels: coreml, vision
Objectclassifier
An iOS swift app that detects objects using machine learning (CoreML, Vision)
Stars: β 12 (-86.67%)
Mutual labels: coreml, vision
Inceptionvisiondemo
π₯ iOS11 demo application for dominant objects detection.
Stars: β 48 (-46.67%)
Mutual labels: coreml, vision
Coreml Training
Source code for my blog post series "On-device training with Core ML"
Stars: β 77 (-14.44%)
Mutual labels: coreml
Testcoreml
A camera object recognition demo using the CoreML & AVCam framework. Required XCode 9 & iOS 11.
Stars: β 60 (-33.33%)
Mutual labels: coreml
Nlpswift
NSLinguisticTagger provides a uniform interface to a variety of natural language processing functionality with support for many different languages and scripts. One can use this class to segment natural language text into paragraphs , sentences, or words and tag information about those segments such as parts of speech, lexical class, lemma!
Stars: β 50 (-44.44%)
Mutual labels: coreml
Ios Coreml Mnist
Real-time Number Recognition using Apple's CoreML 2.0 and MNIST -
Stars: β 74 (-17.78%)
Mutual labels: coreml
Carposedemo
Real-time Mobile Car Pose Estimation with CoreML
Stars: β 49 (-45.56%)
Mutual labels: coreml
Face Marks
Detect facial landmarks with TensorFlow and CoreML on iPhone.
Stars: β 69 (-23.33%)
Mutual labels: coreml
Flowers Vision Demo
iOS11 demo application for flower classification using Vision
and CoreML
frameworks.
Model
This demo is based on Caffe CNNs for the Oxford 102 flower dataset, which was converted to CoreML model using coremltools python package.
Requirements
- Xcode 9
- iOS 11
Installation
git clone https://github.com/cocoa-ai/FlowersVisionDemo.git
cd FlowersVisionDemo
pod install
open Flowers.xcworkspace/
Download the CoreMl model and add the file to "Resources" folder in the project's directory.
Build the project and run it on a simulator or a device with iOS 11.
Conversion
cd Convert
./download.sh
python convert.py
Author
Vadym Markov, [email protected]
Credits
- Classifying images in the Oxford 102 flower dataset with CNNs
- Photo in the demo is taken from Flickr and is distributed under Attribution 2.0 Generic (CC BY 2.0) license
References
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].