
How to Build a Real-Time Object Detection iOS App Using TensorFlow - austin_kodra
https://heartbeat.fritz.ai/https-heartbeat-fritz-ai-building-a-real-time-object-recognition-ios-app-that-detects-sushi-c4a3a2c32298
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gok
You're probably going to get much better performance if you convert your
TensorFlow model to CoreML (use tfcoreml). Also has the advantage of not
needing to compile TF for your phone yourself, and distribute it with your
app.

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Q6T46nT668w6i3m
If, and only if, it can be compiled to CoreML.

(I wrote and maintain Keras-RCNN. It does not compile to CoreML. Yet.)

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minimaxir
Out of curiosity, why does compiling to CoreML fail?

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asparagui
Not every op supported in generic Tensorflow (software) can be converted to
CoreML ops (hardware), which means a number of the more complicated models
can't be automagically converted. If you have specific domain knowledge you
can add substitute ops/roll your own, but this is beyond the scope of most
people trying to bring models over to mobile.

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tnolet
Reminds me of the “see/seafood” app pitched by Jian-Yang from Silicon Valley

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fartcannon
This is image classification, not object detection!

/pedant

Edit: /eats crow

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prashp
Actually, this is object detection because there is a bounding box which is
generated localizing the object(s). Classification would be if each frame
returned a class and class score without the bounding box.

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kahlonel
High-performance != Real-Time

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0x8BADF00D
Are they still using YOLO for object detection in TF?

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dizzy3gg
[https://github.com/tensorflow/models/blob/master/research/ob...](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md)

