Live Reviews:
⭐️5 / 5
Rating
🙌4
Ratings
📼7 scs
Content
📦w/o updates
Updates frequency
🗣❌ unsupported
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All Versions of Neural Object Detector

1.5

June 25, 2022

Minor performance improvements, and updated the app name for better reach.
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1.2.3

October 21, 2021

Critical Bug Fix & Significant Performance Improvements. In addition to the those, this update also sets foundation for exciting new features and optimisations coming in the near future.
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1.2.1

November 20, 2020

Critical Fix: Addressed an issue where temp files were not deleted as intended.
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1.2

September 16, 2020

Neural Vision says hello to iOS 14. It is now better, accurate, and fast. In addition to live object detection, Neural now allows you to import photos to detect objects. Annotations are more accurate than before. You can toggle between Object Detection and Image Classification in the live view mode by simply tapping a button. This update also brings the ability to export the performance log as a JSON under Settings menu. Thank you for using Neural Vision.
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1.1

April 19, 2020

This update significantly improves the app's performance, and contains bug fixes.
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1.0.1

April 10, 2020

Neural now supports Image Classification in addition to Object Detection. You can easily switch back and forth between the two modes under the settings page. This update also contains bug fixes and improvements. If you have any questions please feel free to email me at neural@hariharanm.com.
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1.0

April 7, 2020

Price History of Neural Object Detector

Description of Neural Object Detector

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: FAQ

Can Neural Object Detector support iPad devices?

Yes, Neural Object Detector is available for iPad users.
Hariharan Murugesan developed the Neural Object Detector app.
The minimum iOS requirement: 13.0.
The overall user rating of the Neural Object Detector app is 5.0.
Neural Object Detector Relates To The Developer Tools App Genre.
The latest version of the Neural Object Detector app is 1.5.
July 4, 2024 is the date of the latest update of the Neural Object Detector app.
Neural Object Detector officially launched on February 5, 2023.
{{ name}} is considered child-appropriate and rated Hariharan Murugesan.
The following list of languages is supported by the Neural Object Detector app: American English.
No, Neural Object Detector is not on Apple Arcade.
No, Neural Object Detector does not support in-app purchases.
No, Neural Object Detector does not provide support for Apple Vision Pro.

Screenshots of Neural Object Detector

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Reviews of Neural Object Detector

  • Works perfectly and effectively.

    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...

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

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