Neural Object Detector

Veröffentlicht von: Hariharan Murugesan

Beschreibung

Neural Object Detector was designed to be used by both developers and people who are enthusiastic about Machine Learning, Computer Vision, and Object Detection / Image Classification using the combination of both. Neural Object Detector, by default is bundled with YOLOv3 model, which is a neural network for fast object detection that detects 80 different classes of objects. In addition to that, the app allows the users to import any custom machine learning model designed for object detection or image classification, with a single tap, the downloaded model can be imported via the Files app import window which is available within the app by simply pressing the plus icon on the models view so users do not have to leave the app. The app, based on the model selected, draws a rounded rectangle over the detected objects, the annotated image can be rendered and saved to photos or shared if the user chooses to share it directly from the app. To meet every users needs a handful of settings for computer vision algorithm and camera resolution can be changed. Users have the option to enable CPU only mode, which helps test their models under that specific condition.
In addition to Object Detection, Neural also supports Image Classification, by default, Neural is bundled with Resnet50 Image Classification Model.
Core ML* models which are a type of "Pipeline" in the format of *.mlmodel is supported by this app for Object Detection. No other model format is supported as of now.
Core ML Supported Tools, Services, and Converters:
• Turi Create* - https://github.com/apple/turicreate
• IBM Watson Services* - https://developer.apple.com/ibm/
• Core ML Tools* - https://pypi.org/project/coremltools/
• Apache MXNet* - https://github.com/apache/incubator-mxnet/tree/master/tools/coreml
• TensorFlow* - https://github.com/tf-coreml/tf-coreml
• ONNX* - https://github.com/onnx/onnx-coreml
* Turi Create, IBM Watson Services, Core ML, Apache MXNet, TensorFlow, ONNX might be registered trademarks of their respected owners / proprietors. Neural Object Detector nor the developer is not affiliated with any of the above services or companies.
YOLOv3 Model bundled with the is app is free, open source model. More info: https://github.com/pjreddie/darknet
Resnet50 Model bundled with this app for Image Classification is free, and open source model.
More info: https://github.com/fchollet/deep-learning-models/blob/master/LICENSE
Visit https://hariharanm.com/neural/acknowledgements/ for Acknowledgments.
The machine learning aspects are all proceed on device so nothing leaves the device. No cloud services are involved. No private analytics services. If, a user decides to contact app support a handful of data will be complied into a log file and attached to the mail composer, these data include app version, app configuration, device model, battery info, device software version, CPU utilised my the app. If the user decided not share, they can simply delete it and continue with the composing the support mail. No data is that is individually identifiable is collected.
https://hariharanm.com/
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Neural Object Detector Häufige Fragen

  • Ist Neural Object Detector kostenlos?

    Ja, Neural Object Detector ist komplett kostenlos und enthält keine In-App-Käufe oder Abonnements.

  • Ist Neural Object Detector seriös?

    Nicht genügend Bewertungen, um eine zuverlässige Einschätzung vorzunehmen. Die App benötigt mehr Nutzerfeedback.

    Danke für die Stimme

  • Wie viel kostet Neural Object Detector?

    Neural Object Detector ist kostenlos.

  • Wie hoch ist der Umsatz von Neural Object Detector?

    Um geschätzte Einnahmen der Neural Object Detector-App und weitere AppStore-Einblicke zu erhalten, können Sie sich bei der AppTail Mobile Analytics Platform anmelden.

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Die App ist in Portugal noch nicht bewertet.
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Neural Object Detector Bewertungen

Works perfectly and effectively.

RaptorsaClaw76 on

Vereinigte Staaten

No this isn't a fake review, even though that's a controversial claim. But this app works a charm, would be nice if I could access the vector charts from a network though. But only one question, what file type does this need for object models, as that's not stated in the app.

Cool, but...

i just picked a random name on

Vereinigte Staaten

It would be nice if there was a setting to completely disable photos, other than that it’s great! :)

Update: it works

ajsloniewsky on

Vereinigte Staaten

Amazing for test your own ML Models with need to use your Mac :D

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