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The pre-trained model I used: ssd_mobilenet_v1_fpn_640x640_coco17_tpu-8.
The code I used is below:
```
converter = tf.lite.TFLiteConverter.from_saved_model(model_dir)
converter.optimizations =…
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Hello, I ran the object_detection_cv in google collab and then tried to convert to tflite. The conversion succeeds but there are no signatures. Inference requires at least the default signature, which…
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I can't find useful information to convert these models to TF-Lite and run it at Linux environment.
Could someone give some hints?
Thanks!
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I get the error below, after importing the android folder to Android Studio, and trying to build the APK:
***
_import org.tensorflow.lite.examples.detection.tflite.TFLiteObjectDetectionAPIModel…
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Just creating this issue to document ongoing investigation.
```
DIM1
product: FAIL (1.52s)
✗ failed at test/nofib/Data/Array/Accelerate/Test/NoFib/Prelude/Fold.hs:84:3
…
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Is there a TensorFlow-Lite version of this? I notice that the pre-trained models are checkpoints, is there a way to freeze the models to a TF-Lite model, and use that model instead?
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### Xamarin.Android Version (eg: 6.0):
Android 13.0
### Operating System & Version (eg: Mac OSX 10.11):
Windows 10.
### Google Play Services Version
Xamarin.GooglePlayServices.Vision, 120.1.3…
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After TF Lite quantization the size of Yolov4 tiny model is reduced indeed. But the latency is increasing. For dynamic-range quantization up to 2-3 times. For int8 - up to 4-5 times. I tested it on de…
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TIDL documentation is bit confusing . I'm trying to do a custom object detection and classification, could you advise me
1) should I use pytorch?
2)if tf lite supports, could you provide some hints…
ghost updated
4 years ago
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Just a quick question. I want my final model to be full int8 instead of float32 for input and outputs. I want the training to be as accurate as possible. Do I train with quantised input and outputs? B…