When I am using TensorFlow on my MacBook Air, I always get annoyed by the warnings comes from nowhere, so I followed the documentation below to build TensorFlow sources into a TensorFlow binary and installed it successfully. In theory, this will make the TF running faster on my machine.
Here is the document:
If you are a Mac user, you could download the TF binary from here:
Then, you could use conda to initialize an environment with Python=3.6 and install TF by typing:
sudo pip install tensorflow-1.8.0-py2-none-any.whl
Continue reading “MacOS X: Installing TensorFlow from Sources [TF Binary Attached]”
This is the 3rd post about my implementation of TensorFlow Apps on my Android Phone.
This time I fixed one small bug in the app of “TF Detect” so the object tracking function could work. The project is compiled by “cmake“ with NDK Archives in this version. You can download the new “apk files here: Tensorflow_Demo_Debug.apk.
“Once the app is installed it can be started via the “TF Classify”, “TF Detect”, “TF Stylize”, and “TF Speech” icons, which have the orange TensorFlow logo as their icon.
Continue reading “A Taste of TensorFlow on My Android Phone (III)”
This project is forked from zbar library, I added some modifications, so the webcam can be used as an image reader to detect QR and Barcodes.
Continue reading “QR Code Detector with Webcam (Python / OpenCV / Pyzbar)”
Python is a great general-purpose programming language on its own, but with the help of a few popular libraries (Numpy, SciPy, Matplotlib, TensorFlow) it becomes a powerful environment for scientific computing and data analysis.
I start sharing my notebooks on learning Python and TensorFlow, here is my GitHub repository: Data_Science_Python.
Continue reading “Sharing My Data Science Notebook (Python & TensorFlow) on GitHub”
Great news! PyTorch now is supporting Windows!
If you have a PC with suitable Nvidia graphics card and installed CUDA 9.0 and Anaconda, type the following commands;
conda install pytorch cuda90 -c pytorch
pip3 install torchvision
It is about 500 MB, so be patient!
Underline is the old post.
PyTorch is a deep learning framework that puts Python first. Currently, it only supports MacOS or Linux.
But, can we use it on WIN10 without changing the system/computer?
Yes, we can.
Continue reading “Install PyTorch on Window 10”
This post is a follow-up to my last post: A Taste of TensorFlow on My Android Phone.
You could download my compiled Apk file here and install on your android device (>Android 7.0) (22-May-2018).
Update: 25-May-2018, fixed the bug of object tracking function in TF Detect. PS: While running the activities, pressing the volume keys on your device will
toggle debug visualizations on/off, rendering additional info to the screen that
may be useful for development purposes.
Feel free to let me know if there are any bugs 🙂
In the last post, I just tried the TensorFlow for object classification (TF Classify). This time I installed all four demos of the TensorFlow Mobile for Android according to this tutorial: TensorFlow Lite Demo for Android. They are awesome 😛
Continue reading “A Taste of TensorFlow on My Android Phone (II)”
If you like Google’s open-source machine learning framework, TensorFlow,
do not miss this “TensorFlow For Poets
“. I went through the tutorial this afternoon and found it is super Awesome. See the photos below, I first tested it on the coffee mug from my Intern company, Aurecon Group.
I used the virtual device, Nexus 5X, from Android Studio 3.0.1 on MacBook Air 11′ (Do not do this unless you have enough SSD 😛 ).
Then, I successfully installed the compiled app (TF_Classify) on my XIAO MI – 4C
– Android 7.0) and tested it on my coffee mug at home.
You can download and install it on your own Android devices from the following link:
Continue reading “A Taste of TensorFlow on My Android Phone”