I'm using PyTorch3D on google colab.
the colab showing this 154/2000 [03:22<40:44, 1.32s/it], I can't find this 's/it' means.
Someone answer would be really thanks!
Related
I have this problem of Semantic Segmentation data in Google Colab and Jupyter Notebook. Here's an example. This is the picture from Jupyter Notebook.
https://i.stack.imgur.com/slBeI.png
This is the picture from Google Colab.
https://i.stack.imgur.com/BNXOw.png
As you can see, the Segmentation map is different between these 2 pictures. Is there anyone has this problem related? And is there any solution for this type of problems? Thanks Ahead!
I am a beginner who just learned about TensorFlow using Google Colab.
As in the attached image file, numbers 10 to 13 are underlined in tensorflow.keras~, what is the problem?
It's probably a function that indicates a typo, but there's nothing wrong with running it.
enter image description here
This underline error was an ongoing issue earlier in Google Colab, which is resolved now. Please try again replicating the same code in Google colab what you mentioned in the screen shot and let us know if the issue still persists at your end.
Please check the code below: (I replicated the same in Google Colab with python 3.8.10 and TensorFlow 2.9.2)
from keras.preprocessing import Sequence will show the error as you are not giving proper alias to import the Sequence API which is provided correctly in next line (using tensorflow.keras.preprocessing prefix or tensorflow.keras.utils).
I just try code On-device recommendation with TensorFlow Lite in Google Colab. I get an error in Create TFLite interpreter. The error message is Could not open 'model/model_dir/export/export_m2/model.tflite'. Can anyone solve this?
Thank you.
Link for code: https://github.com/tensorflow/examples/blob/master/lite/examples/recommendation/ml/ondevice_recommendation.ipynb
If I try the code from the accepted answer in here, it works fine on my local Jupyter Lab but unfortunately not on Google Colab.
Any idea why is this?
Jupyter Lab:
Google Colab:
Thanks in advance,
I'm currently trying to get my SSDLite Network, which I trained with the Tensroflow Object-detection API working, with iOS.
So I'm using the Open Source Code of SSDMobileNet_CoreML.
The Graph allready works with some limitations. For running on iOS I had to extract the FeatureExtractor from my Graph and where unable to keep Preprocessor, Posprocessor and MutlipleGrindAnchorBox, same as they did in SSDMobileNet_CoreML.
Here you can see the Anchors they have used.
So cause my Anchors seem to be a little different I tried to undestand how they got this array.
So I found in an GitHub Issue an explenation, where the User who created the Anchors explains how he got them.
He says:
I just exported them out of the Tensorflow Graph from the import/MultipleGridAnchorGenerator/Identity tensor
I allready found the matching tensor in my Graph but I don't know how to export the Graph and retrive the correct Anchor encoding.
Can sombody explain this to me?
I allready figured it out. A little below quote was a link to a Python Notebook which explains everything in detail.