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License: MIT License
Largest list of models for Core ML (for iOS 11+)
License: MIT License
Sorry that I don't conform to your issue guide but my issue is just to improve an already existing model in your collection.
I saw that you added images with the input types and the output types of each model to your README and I therefore wanted to tell you that I finally converted the Food101 CoreML model in a matter where it now accepts CVPixelBuffer
instead of MLMultiArray
as an input.
Just a little update :)
BSD-2
This model detects nudity and it's score from an image. The original dataset is Yahoo's OpenNSFW.
Since this is too big for Github I have a GoogleDrive link:
https://drive.google.com/open?id=0B5TjkH3njRqncDJpdDB1Tkl2S2s
https://github.com/ph1ps/Nudity-CoreML
Input: Output: SFW (100%), NSFW (0%)
Input: Image, Output: NSFW (80%), SFW(20%)
This gives you back both NSFW and SFW score in order to make people able to decide what their personal threshold is. Let's say there is a picture with NSFW - 70%, some people might consider this as safe but others not. Therefore they can say everything from 70% and down is SFW and everything from 71% to 100% is NSFW.
This model should detect and recognize live video traffic signs. If there is a speed limit fo example the app should detect and recognize this shield.
There is a lot of sources...
http://btsd.ethz.ch/shareddata/
http://benchmark.ini.rub.de/?section=gtsdb&subsection=news
MIT
Automatically learned quality assessment for images has recently become a hot topic due to its usefulness in a wide variety of applications such as evaluating image capture pipelines, storage techniques and sharing media. Despite the subjective nature of this problem, most existing methods only predict the mean opinion score provided by datasets such as AVA [1] and TID2013 [2]. Our approach differs from others in that we predict the distribution of human opinion scores using a convolutional neural network. Our architecture also has the advantage of being significantly simpler than other methods with comparable performance. Our proposed approach relies on the success (and retraining) of proven, state-of-the-art deep object recognition networks. Our resulting network can be used to not only score images reliably and with high correlation to human perception, but also to assist with adaptation and optimization of photo editing/enhancement algorithms in a photographic pipeline. All this is done without need for a "golden" reference image, consequently allowing for single-image, semantic- and perceptually-aware, no-reference quality assessment.
Input: Image[http://i1.hdslb.com/bfs/archive/9892e6f032425fc9e9831fa1ed855318c12702ad.jpg], Output: Double 10 vector [1.614268398952845e-06,0.0006238522473722696,0.02812075242400169,0.2070262581110001,0.3266536593437195,0.332121878862381,0.09285952150821686,0.01259173825383186,2.718873588491988e-07,4.697789393048879e-07]
My Code is MIT, though the model requires an agreement for commercial use
I implemented Fast Style Transfer in CoreML. This is similar to Fast Neural Style, but is TensorFlow.
My article explains the process.
https://github.com/lengstrom/fast-style-transfer
https://medium.com/@rambossa/diy-prisma-fast-style-transfer-app-with-coreml-and-tensorflow-817c3b90dacd
https://github.com/mdramos/fast-style-transfer-coreml
Here are some CoreML models I created in the process: https://drive.google.com/drive/folders/1CBSanBHbXC5-bJNTTk3-r1WSq56z0eKG?usp=sharing
-- just include these in the ios app before running
This is not an issue I just wanted to make sure this repo had seen this cool start up:
They claim to have lots of CoreML Models from that example page. No way to download from what I saw though.
Regardless, I signed up for their beta.
https://downforeveryoneorjustme.com/coreml.store
Is this project still alive?
This model is also included in an open-source framework that can be used for document classification.
MIT
Demo app is the NewsClassifier iOS app here
Screenshot from the demo app here
(not the author, just stumbled across this and seems it would fit in Text Analysis here)
MIT
A Demo application using CoreML framework for predicting gender from first names.
See Is it a boy or a girl? An introduction to Machine Learning
CoreML model was converted from Scikit-learn Pipeline using coremltools python package.
In demo README
Hello, I wrote a tool that can validate links in a README (or any file). It can be run when someone submits a pull request or pushes a commit to Awesome-CoreML-Models
.
This tool is currently being used by
More examples
If you are interested, connect this repo to https://travis-ci.org/ and add a .travis.yml
file to the project (you can also use CircleCI or other CI tools).
See https://github.com/dkhamsing/awesome_bot for options, more information ๐
Hi, I am trying to use CNNEmotions, but his size is too big.
Would it be possible to reduce its size?
Thanks!
I'm in the middle of trying to figure out how to map up the transformers and such. But not very experienced and running into headaches. Anyone want to tag team?
https://github.com/hollance/MobileNet-CoreML/raw/master/MobileNet.mlmodel
This doesn't seem to be the correct model linked up
Just need a model that can detect traffic lights and give me the color state of it. Thanks.
TextRecognition - Recognizing text using ML Kit built-in model in real-time.
Links to project that uses ML Kit (Google Firebase) and not CoreML (Apple) framework and model.
Do you have any mlmodels using activity classification for exercising? Like push ups and jumping jacks?
most of the links in readme are not opening
Apache License 2.0
edvardHua implements PoseEstimationForMobile estimating human pose from a picture for mobile. And I make demo for that on iOS.
Image[URL]
Heatmap[Array<Array<Array>>]
model | cpm | hourglass |
---|---|---|
output | [96, 96, 14] | [48, 48, 14] |
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