python


AttributeError: module ‘html5lib.treebuilders’ has no attribute ‘_base’

Recently, we were receiving the above error on a GNU/Linux Ubuntu 20.04 LTS.

AttributeError: module 'html5lib.treebuilders' has no attribute '_base'

We had installed beautifulsoup4 and html5lib using pip. To solve the issue, we had to uninstall the html5lib that was installed by pip and install it through apt.

# Remove html5lib if you have installed it with pip3:
pip3 uninstall html5lib;

pip3 install --upgrade beautifulsoup4
sudo apt-get install python3-html5lib

How to check if PyTorch is using the GPU?

The following basic code, will import PyTorch into a project and test if GPU capabilities are enabled and available.

import torch

# Should produce "True"
torch.cuda.is_available()

# Should produce the number of available devices, if you have one device it should produce the value "1"
torch.cuda.device_count()

# If there is a device and it is the first one, it should produce the "0"
torch.cuda.current_device()

# Assuming that there is at least one device, with the following two commands we will get some information on the first available device

# Should produce something similar to "<torch.cuda.device object at 0x7f12b1a298d0>"
torch.cuda.device(0)

# Should produce something similar to "'GeForce GTX 1050 Ti'"
torch.cuda.get_device_name(0)

We are using Ubuntu 20.04 LTS and the NVidia drivers were installed automatically during installation.


Installing TensorFlow 2 Object detection on Ubuntu 18.04 LTS 1

Following are some rough notes on Installing TensorFlow 2 Object detection on Ubuntu 18.04 LTS.
We were following this guide (https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/install.html) so we will be skipping some steps.

We had conda installed already from an older attempt so the following steps worked just fine.

conda create -n tensorflow pip python=3.8;
conda activate tensorflow;

We got an error with the following command so we used pip3 instead of pip.

pip install --ignore-installed --upgrade tensorflow==2.2.0;
Command 'pip' not found, but there are 18 similar ones.
pip3 install --ignore-installed --upgrade tensorflow==2.2.0;

Executing the above gave us another error:

Collecting tensorflow==2.2.0
Could not find a version that satisfies the requirement tensorflow==2.2.0 (from versions: 0.12.1, 1.0.0, 1.0.1, 1.1.0rc0, 1.1.0rc1, 1.1.0rc2, 1.1.0, 1.2.0rc0, 1.2.0rc1, 1.2.0rc2, 1.2.0, 1.2.1, 1.3.0rc0, 1.3.0rc1, 1.3.0rc2, 1.3.0, 1.4.0rc0, 1.4.0rc1, 1.4.0, 1.4.1, 1.5.0rc0, 1.5.0rc1, 1.5.0, 1.5.1, 1.6.0rc0, 1.6.0rc1, 1.6.0, 1.7.0rc0, 1.7.0rc1, 1.7.0, 1.7.1, 1.8.0rc0, 1.8.0rc1, 1.8.0, 1.9.0rc0, 1.9.0rc1, 1.9.0rc2, 1.9.0, 1.10.0rc0, 1.10.0rc1, 1.10.0, 1.10.1, 1.11.0rc0, 1.11.0rc1, 1.11.0rc2, 1.11.0, 1.12.0rc0, 1.12.0rc1, 1.12.0rc2, 1.12.0, 1.12.2, 1.12.3, 1.13.0rc0, 1.13.0rc1, 1.13.0rc2, 1.13.1, 1.13.2, 1.14.0rc0, 1.14.0rc1, 1.14.0, 2.0.0a0, 2.0.0b0, 2.0.0b1)
No matching distribution found for tensorflow==2.2.0

To fix it we upgraded pip using the following command.

python3 -m pip install --upgrade pip;

Then we tried again, which installed most packets but gave a new error:

pip3 install --ignore-installed --upgrade tensorflow==2.2.0;
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
launchpadlib 1.10.6 requires testresources, which is not installed.
Successfully installed absl-py-0.11.0 astunparse-1.6.3 cachetools-4.2.1 certifi-2020.12.5 chardet-4.0.0 gast-0.3.3 google-auth-1.27.0 google-auth-oauthlib-0.4.2 google-pasta-0.2.0 grpcio-1.35.0 h5py-2.10.0 idna-2.10 importlib-metadata-3.4.0 keras-preprocessing-1.1.2 markdown-3.3.3 numpy-1.19.5 oauthlib-3.1.0 opt-einsum-3.3.0 protobuf-3.14.0 pyasn1-0.4.8 pyasn1-modules-0.2.8 requests-2.25.1 requests-oauthlib-1.3.0 rsa-4.7.1 scipy-1.4.1 setuptools-53.0.0 six-1.15.0 tensorboard-2.2.2 tensorboard-plugin-wit-1.8.0 tensorflow-2.2.0 tensorflow-estimator-2.2.0 termcolor-1.1.0 typing-extensions-3.7.4.3 urllib3-1.26.3 werkzeug-1.0.1 wheel-0.36.2 wrapt-1.12.1 zipp-3.4.0

To fix this error we used:

sudo apt install python3-testresources;

Then tried again the pip installation with success.

pip3 install --ignore-installed --upgrade tensorflow==2.2.0;
Successfully installed absl-py-0.11.0 astunparse-1.6.3 cachetools-4.2.1 certifi-2020.12.5 chardet-4.0.0 gast-0.3.3 google-auth-1.27.0 google-auth-oauthlib-0.4.2 google-pasta-0.2.0 grpcio-1.35.0 h5py-2.10.0 idna-2.10 importlib-metadata-3.4.0 keras-preprocessing-1.1.2 markdown-3.3.3 numpy-1.19.5 oauthlib-3.1.0 opt-einsum-3.3.0 protobuf-3.14.0 pyasn1-0.4.8 pyasn1-modules-0.2.8 requests-2.25.1 requests-oauthlib-1.3.0 rsa-4.7.1 scipy-1.4.1 setuptools-53.0.0 six-1.15.0 tensorboard-2.2.2 tensorboard-plugin-wit-1.8.0 tensorflow-2.2.0 tensorflow-estimator-2.2.0 termcolor-1.1.0 typing-extensions-3.7.4.3 urllib3-1.26.3 werkzeug-1.0.1 wheel-0.36.2 wrapt-1.12.1 zipp-3.4.0

We then executed the following to test the installation:

python3 -c "import tensorflow as tf;print(tf.reduce_sum(tf.random.normal([1000, 1000])))";

Then we proceeded to get the TensorFlow models:

mkdir ~/TensorFlow;
cd ~/TensorFlow;
git clone https://github.com/tensorflow/models;

We then downloaded protobufs and extracted them to our home directory.
To test the installation we did the following.

export PATH="/home/bob/protoc-3.14.0-linux-x86_64:$PATH";
cd /home/bob/TensorFlow/models/research;
protoc object_detection/protos/*.proto --python_out=.;

Then we proceeded to the COCO installation:

pip3 install cython;

The above will solve the problem of:

gcc: error: pycocotools/_mask.c: No such file or directory
cd ~;
git clone https://github.com/cocodataset/cocoapi.git;
cd cocoapi/PythonAPI;
make;
cp -r pycocotools ~/TensorFlow/models/research/;

Finally we proceeded to Install the Object Detection API.

cd ~/TensorFlow/models/research/;
cp object_detection/packages/tf2/setup.py .;
python3 -m pip install .;

To test the installation we executed the following:

python3 object_detection/builders/model_builder_tf2_test.py;

We then downloaded the samples and executed the camera sample with success!!

To check against a video instead of a camera, we changed the following line from:

cap = cv2.VideoCapture(0)

to

cap = cv2.VideoCapture('/home/bob/Desktop/a2/A01_20210210164306.mp4')

Programming Course Series [01 – Introductory course to python]

Computer programming is important today because so much of our world is automated. Humans need to be able to control the interaction between people and machines. Since computers and machines are able to do things so efficiently and accurately, we use computer programming to harness that computing power.

This is the first of hopefully many programming courses that can introduce technically inclined people to Python programming.


  Date and Time

Location

Information on our VPN service (instructions for iOS devices) will be provided to the registrants that cannot join us along with instructions on our BigBlueButton platform.

Hosts

Registration


  Speakers

George Michael

Topic:

Everybody can write a computer program (An introduction using Python)


Agenda

Introduction to programming and reasons to write programs?

These are the course-wide materials as well as Introductions’ first section where we discuss what writing programs mean. In the third part of the class, we will finish the Introduction and have the quiz and first task.

Installing and Using Python

We’re going to set up stuff so that you can write Python programs.

Introduction to programming and reasons to write programs? (continued)

We try to cover the “big picture” of programming so that you get a “table of contents” from what to expect to learn. Don’t worry if, the first time you hear it, not everything makes perfect sense. This part is very broad.

Variables and Expressions

We will explain how a program uses the memory of the machine to store, retrieve and process information in this section.

Conditional Code

We will move from sequential code in this section that simply runs one line of code after another to conditional code where some steps are skipped. It is a very basic idea – but it is how “choices” are made by computer software.

Functions

We are going to learn about what functions are and how we can use them. Functions will be an essential way for us to make sense of our code, as we move into more and more complicated programs.

Loops and Iteration

Our four fundamental programming patterns are completed by loops and iteration. Loops are the way we say Python over and over to do something. Loops are the manner in which we create programs that remain with a problem until the problem is solved.


Programming Course Series [beta]

Computer programming is important today because so much of our world is automated. Humans need to be able to control the interaction between people and machines. Since computers and machines are able to do things so efficiently and accurately, we use computer programming to harness that computing power.

This is the first of hopefully many programming courses that can introduce technically inclined people to Python programming.

Date and Time

Location

Information on our VPN service (instructions for iOS devices) will be provided to the registrants that cannot join us along with instructions on our BigBlueButton platform.

Hosts

Registration

 Speakers

George Michael

Topic:

Everybody can program (An introduction using Python)


Agenda

Introduction to programming and reasons to write programs?

These are the course-wide materials as well as Introductions’s first section where we discuss what writing programs mean. In the third part of the class, we will finish the Introduction and have the quiz and first task.

Installing and Using Python

We’re going to set up stuff so that you can write Python programs.

Introduction to programming and reasons to write programs? (continued)

We try to cover the “big picture” of programming so that you get a “table of contents” from what to expect to learn. Don’t worry if, the first time you hear it, not everything makes perfect sense. This part is very broad.

Variables and Expressions

We will explain how a program uses the memory of the machine to store, retrieve and process information in this section.

Conditional Code

We will move from sequential code in this section that simply runs one line of code after another to conditional code where some steps are skipped. It is a very basic idea – but it is how “choices” are made by computer software.

Functions

We are going to learn about what functions are and how we can use them. Functions will be an essential way for us to make sense of our code, as we move into more and more complicated programs.

Loops and Iteration

Our four fundamental programming patterns are completed by loops and iteration. Loops are the way we say Python over and over to do something. Loops are the manner in which we create programs that remain with a problem until the problem is solved.