A collection of interactive machine-learning experiments: 🏋️models training + 🎨models demo

Overview

🤖 Interactive Machine Learning Experiments

This is a collection of interactive machine-learning experiments. Each experiment consists of 🏋️ Jupyter/Colab notebook (to see how a model was trained) and 🎨 demo page (to see a model in action right in your browser).


⚠️ This repository contains machine learning experiments and not a production ready, reusable, optimised and fine-tuned code and models. This is rather a sandbox or a playground for learning and trying different machine learning approaches, algorithms and data-sets. Models might not perform well and there is a place for overfitting/underfitting.

Experiments

Most of the models in these experiments were trained using TensorFlow 2 with Keras support.

Supervised Machine Learning

Supervised learning is when you have input variables X and an output variable Y and you use an algorithm to learn the mapping function from the input to the output: Y = f(X). The goal is to approximate the mapping function so well that when you have new input data X that you can predict the output variables Y for that data. It is called supervised learning because the process of an algorithm learning from the training dataset can be thought of as a teacher supervising the learning process.

Multilayer Perceptron (MLP) or simple Neural Network (NN)

A multilayer perceptron (MLP) is a class of feedforward artificial neural network (ANN). Multilayer perceptrons are sometimes referred to as "vanilla" neural networks (composed of multiple layers of perceptrons), especially when they have a single hidden layer. It can distinguish data that is not linearly separable.

Experiment Model demo & training Tags Dataset
Handwritten digits recognition (MLP) Handwritten Digits Recognition (MLP) Launch demo Open in Binder Open in Colab MLP MNIST
Handwritten sketch recognition (MLP) Handwritten Sketch Recognition (MLP) Launch demo Open in Binder Open in Colab MLP QuickDraw

Convolutional Neural Networks (CNN)

A convolutional neural network (CNN, or ConvNet) is a class of deep neural networks, most commonly applied to analyzing visual imagery (photos, videos). They are used for detecting and classifying objects on photos and videos, style transfer, face recognition, pose estimation etc.

Experiment Model demo & training Tags Dataset
Handwritten digits recognition (CNN) Handwritten Digits Recognition (CNN) Launch demo Open in Binder Open in Colab CNN MNIST
Handwritten sketch recognition (CNN) Handwritten Sketch Recognition (CNN) Launch demo Open in Binder Open in Colab CNN QuickDraw
Rock Paper Scissors Rock Paper Scissors (CNN) Launch demo Open in Binder Open in Colab CNN RPS
Rock Paper Scissors Rock Paper Scissors (MobilenetV2) Launch demo Open in Binder Open in Colab MobileNetV2, Transfer learning, CNN RPS , ImageNet
Objects detection Objects Detection (MobileNetV2) Launch demo Open in Binder Open in Colab MobileNetV2, SSDLite, CNN COCO
Objects detection Image Classification (MobileNetV2) Launch demo Open in Binder Open in Colab MobileNetV2, CNN ImageNet

Recurrent Neural Networks (RNN)

A recurrent neural network (RNN) is a class of deep neural networks, most commonly applied to sequence-based data like speech, voice, text or music. They are used for machine translation, speech recognition, voice synthesis etc.

Experiment Model demo & training Tags Dataset
Numbers summation (RNN) Numbers Summation (RNN) Launch demo Open in Binder Open in Colab LSTM, Sequence-to-sequence Auto-generated
Shakespeare Text Generation (RNN) Shakespeare Text Generation (RNN) Launch demo Open in Binder Open in Colab LSTM, Character-based RNN Shakespeare
Wikipedia Text Generation (RNN) Wikipedia Text Generation (RNN) Launch demo Open in Binder Open in Colab LSTM, Character-based RNN Wikipedia
Recipe Generation (RNN) Recipe Generation (RNN) Launch demo Open in Binder Open in Colab LSTM, Character-based RNN Recipe box

Unsupervised Machine Learning

Unsupervised learning is when you only have input data X and no corresponding output variables. The goal for unsupervised learning is to model the underlying structure or distribution in the data in order to learn more about the data. These are called unsupervised learning because unlike supervised learning above there is no correct answers and there is no teacher. Algorithms are left to their own to discover and present the interesting structure in the data.

Generative Adversarial Networks (GANs)

A generative adversarial network (GAN) is a class of machine learning frameworks where two neural networks contest with each other in a game. Two models are trained simultaneously by an adversarial process. For example a generator ("the artist") learns to create images that look real, while a discriminator ("the art critic") learns to tell real images apart from fakes.

Experiment Model demo & training Tags Dataset
Clothes Generation (DCGAN) Clothes Generation (DCGAN) Launch demo Open in Binder Open in Colab DCGAN Fashion MNIST

How to use this repository locally

Setup virtual environment for Experiments

# Create "experiments" environment (from the project root folder).
python3 -m venv .virtualenvs/experiments

# Activate environment.
source .virtualenvs/experiments/bin/activate
# or if you use Fish...
source .virtualenvs/experiments/bin/activate.fish

To quit an environment run deactivate.

Install dependencies

# Upgrade pip and setuptools to the latest versions.
pip install --upgrade pip setuptools

# Install packages
pip install -r requirements.txt

To install new packages run pip install package-name. To add new packages to the requirements run pip freeze > requirements.txt.

Launch Jupyter locally

In order to play around with Jupyter notebooks and see how models were trained you need to launch a Jupyter Notebook server.

# Launch Jupyter server.
jupyter notebook

Jupyter will be available locally at http://localhost:8888/. Notebooks with experiments may be found in experiments folder.

Launch demos locally

Demo application is made on React by means of create-react-app.

# Switch to demos folder from project root.
cd demos

# Install all dependencies.
yarn install

# Start demo server on http. 
yarn start

# Or start demo server on https (for camera access in browser to work on localhost).
yarn start-https

Demos will be available locally at http://localhost:3000/ or at https://localhost:3000/.

Convert models

The converter environment is used to convert the models that were trained during the experiments from .h5 Keras format to Javascript understandable formats (tfjs_layers_model or tfjs_graph_model formats with .json and .bin files) for further usage with TensorFlow.js in Demo application.

# Create "converter" environment (from the project root folder).
python3 -m venv .virtualenvs/converter

# Activate "converter" environment.
source .virtualenvs/converter/bin/activate
# or if you use Fish...
source .virtualenvs/converter/bin/activate.fish

# Install converter requirements.
pip install -r requirements.converter.txt

The conversion of keras models to tfjs_layers_model/tfjs_graph_model formats is done by tfjs-converter:

For example:

tensorflowjs_converter --input_format keras \
  ./experiments/digits_recognition_mlp/digits_recognition_mlp.h5 \
  ./demos/public/models/digits_recognition_mlp

⚠️ Converting the models to JS understandable formats and loading them to the browser directly might not be a good practice since in this case the user might need to load tens or hundreds of megabytes of data to the browser which is not efficient. Normally the model is being served from the back-end (i.e. TensorFlow Extended) and instead of loading it all to the browser the user will do a lightweight HTTP request to do a prediction. But since the Demo App is just an experiment and not a production-ready app and for the sake of simplicity (to avoid having an up and running back-end) we're converting the models to JS understandable formats and loading them directly into the browser.

Requirements

Recommended versions:

  • Python: > 3.7.3.
  • Node: >= 12.4.0.
  • Yarn: >= 1.13.0.

In case if you have Python version 3.7.3 you might experience RuntimeError: dictionary changed size during iteration error when trying to import tensorflow (see the issue).

You might also be interested in

Articles

Supporting the project

You may support this project via ❤️ GitHub or ❤️ Patreon.

Comments
  • Bump lodash from 4.17.15 to 4.17.21 in /demos

    Bump lodash from 4.17.15 to 4.17.21 in /demos

    Bumps lodash from 4.17.15 to 4.17.21.

    Commits
    • f299b52 Bump to v4.17.21
    • c4847eb Improve performance of toNumber, trim and trimEnd on large input strings
    • 3469357 Prevent command injection through _.template's variable option
    • ded9bc6 Bump to v4.17.20.
    • 63150ef Documentation fixes.
    • 00f0f62 test.js: Remove trailing comma.
    • 846e434 Temporarily use a custom fork of lodash-cli.
    • 5d046f3 Re-enable Travis tests on 4.17 branch.
    • aa816b3 Remove /npm-package.
    • d7fbc52 Bump to v4.17.19
    • Additional commits viewable in compare view
    Maintainer changes

    This version was pushed to npm by bnjmnt4n, a new releaser for lodash since your current version.


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    dependencies javascript 
    opened by dependabot[bot] 1
  • Bump ssri from 6.0.1 to 6.0.2 in /demos

    Bump ssri from 6.0.1 to 6.0.2 in /demos

    Bumps ssri from 6.0.1 to 6.0.2.

    Changelog

    Sourced from ssri's changelog.

    6.0.2 (2021-04-07)

    Bug Fixes

    • backport regex change from 8.0.1 (b30dfdb), closes #19

    Commits
    Maintainer changes

    This version was pushed to npm by nlf, a new releaser for ssri since your current version.


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    dependencies javascript 
    opened by dependabot[bot] 1
  • Bump lxml from 4.4.2 to 4.6.3

    Bump lxml from 4.4.2 to 4.6.3

    Bumps lxml from 4.4.2 to 4.6.3.

    Changelog

    Sourced from lxml's changelog.

    4.6.3 (2021-03-21)

    Bugs fixed

    • A vulnerability (CVE-2021-28957) was discovered in the HTML Cleaner by Kevin Chung, which allowed JavaScript to pass through. The cleaner now removes the HTML5 formaction attribute.

    4.6.2 (2020-11-26)

    Bugs fixed

    • A vulnerability (CVE-2020-27783) was discovered in the HTML Cleaner by Yaniv Nizry, which allowed JavaScript to pass through. The cleaner now removes more sneaky "style" content.

    4.6.1 (2020-10-18)

    Bugs fixed

    • A vulnerability was discovered in the HTML Cleaner by Yaniv Nizry, which allowed JavaScript to pass through. The cleaner now removes more sneaky "style" content.

    4.6.0 (2020-10-17)

    Features added

    • GH#310: lxml.html.InputGetter supports __len__() to count the number of input fields. Patch by Aidan Woolley.

    • lxml.html.InputGetter has a new .items() method to ease processing all input fields.

    • lxml.html.InputGetter.keys() now returns the field names in document order.

    • GH-309: The API documentation is now generated using sphinx-apidoc. Patch by Chris Mayo.

    Bugs fixed

    ... (truncated)

    Commits
    • a5f9cb5 Prepare release of lxml 4.6.3.
    • 2d01a1b Add HTML-5 "formaction" attribute to "defs.link_attrs" (GH-316)
    • e986a9c Fix reference in docs.
    • 4cb5736 Work around Py2's lack of "re.ASCII".
    • c30106f Prepare release of 4.6.2.
    • a105ab8 Prevent combinations of <math/svg> and <style> to sneak JavaScript through th...
    • c053dc1 Add a recipe for a look-ahead generator to allow modifications during tree it...
    • b083124 lxml actually works in Py3.9.
    • 0f80590 lxml actually works in Py3.9.
    • fd8893c Add a doc note that the .find() methods are usually faster than one might exp...
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    dependencies python 
    opened by dependabot[bot] 1
  • Bump pygments from 2.4.2 to 2.7.4

    Bump pygments from 2.4.2 to 2.7.4

    Bumps pygments from 2.4.2 to 2.7.4.

    Release notes

    Sourced from pygments's releases.

    2.7.4

    • Updated lexers:

      • Apache configurations: Improve handling of malformed tags (#1656)

      • CSS: Add support for variables (#1633, #1666)

      • Crystal (#1650, #1670)

      • Coq (#1648)

      • Fortran: Add missing keywords (#1635, #1665)

      • Ini (#1624)

      • JavaScript and variants (#1647 -- missing regex flags, #1651)

      • Markdown (#1623, #1617)

      • Shell

        • Lex trailing whitespace as part of the prompt (#1645)
        • Add missing in keyword (#1652)
      • SQL - Fix keywords (#1668)

      • Typescript: Fix incorrect punctuation handling (#1510, #1511)

    • Fix infinite loop in SML lexer (#1625)

    • Fix backtracking string regexes in JavaScript/TypeScript, Modula2 and many other lexers (#1637)

    • Limit recursion with nesting Ruby heredocs (#1638)

    • Fix a few inefficient regexes for guessing lexers

    • Fix the raw token lexer handling of Unicode (#1616)

    • Revert a private API change in the HTML formatter (#1655) -- please note that private APIs remain subject to change!

    • Fix several exponential/cubic-complexity regexes found by Ben Caller/Doyensec (#1675)

    • Fix incorrect MATLAB example (#1582)

    Thanks to Google's OSS-Fuzz project for finding many of these bugs.

    2.7.3

    ... (truncated)

    Changelog

    Sourced from pygments's changelog.

    Version 2.7.4

    (released January 12, 2021)

    • Updated lexers:

      • Apache configurations: Improve handling of malformed tags (#1656)

      • CSS: Add support for variables (#1633, #1666)

      • Crystal (#1650, #1670)

      • Coq (#1648)

      • Fortran: Add missing keywords (#1635, #1665)

      • Ini (#1624)

      • JavaScript and variants (#1647 -- missing regex flags, #1651)

      • Markdown (#1623, #1617)

      • Shell

        • Lex trailing whitespace as part of the prompt (#1645)
        • Add missing in keyword (#1652)
      • SQL - Fix keywords (#1668)

      • Typescript: Fix incorrect punctuation handling (#1510, #1511)

    • Fix infinite loop in SML lexer (#1625)

    • Fix backtracking string regexes in JavaScript/TypeScript, Modula2 and many other lexers (#1637)

    • Limit recursion with nesting Ruby heredocs (#1638)

    • Fix a few inefficient regexes for guessing lexers

    • Fix the raw token lexer handling of Unicode (#1616)

    • Revert a private API change in the HTML formatter (#1655) -- please note that private APIs remain subject to change!

    • Fix several exponential/cubic-complexity regexes found by Ben Caller/Doyensec (#1675)

    • Fix incorrect MATLAB example (#1582)

    Thanks to Google's OSS-Fuzz project for finding many of these bugs.

    Version 2.7.3

    (released December 6, 2020)

    ... (truncated)

    Commits
    • 4d555d0 Bump version to 2.7.4.
    • fc3b05d Update CHANGES.
    • ad21935 Revert "Added dracula theme style (#1636)"
    • e411506 Prepare for 2.7.4 release.
    • 275e34d doc: remove Perl 6 ref
    • 2e7e8c4 Fix several exponential/cubic complexity regexes found by Ben Caller/Doyensec
    • eb39c43 xquery: fix pop from empty stack
    • 2738778 fix coding style in test_analyzer_lexer
    • 02e0f09 Added 'ERROR STOP' to fortran.py keywords. (#1665)
    • c83fe48 support added for css variables (#1633)
    • Additional commits viewable in compare view

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    dependencies python 
    opened by dependabot[bot] 1
  • Bump pyyaml from 5.2 to 5.4

    Bump pyyaml from 5.2 to 5.4

    Bumps pyyaml from 5.2 to 5.4.

    Changelog

    Sourced from pyyaml's changelog.

    5.4 (2021-01-19)

    5.3.1 (2020-03-18)

    • yaml/pyyaml#386 -- Prevents arbitrary code execution during python/object/new constructor

    5.3 (2020-01-06)

    Commits
    • 58d0cb7 5.4 release
    • a60f7a1 Fix compatibility with Jython
    • ee98abd Run CI on PR base branch changes
    • ddf2033 constructor.timezone: _copy & deepcopy
    • fc914d5 Avoid repeatedly appending to yaml_implicit_resolvers
    • a001f27 Fix for CVE-2020-14343
    • fe15062 Add 3.9 to appveyor file for completeness sake
    • 1e1c7fb Add a newline character to end of pyproject.toml
    • 0b6b7d6 Start sentences and phrases for capital letters
    • c976915 Shell code improvements
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    dependencies python 
    opened by dependabot[bot] 1
  • Bump rsa from 4.0 to 4.1

    Bump rsa from 4.0 to 4.1

    Bumps rsa from 4.0 to 4.1.

    Changelog

    Sourced from rsa's changelog.

    Version 4.1 - released 2020-06-10

    • Added support for Python 3.8.
    • Dropped support for Python 2 and 3.4.
    • Added type annotations to the source code. This will make Python-RSA easier to use in your IDE, and allows better type checking.
    • Added static type checking via MyPy.
    • Fix #129 Installing from source gives UnicodeDecodeError.
    • Switched to using Poetry for package management.
    • Added support for SHA3 hashing: SHA3-256, SHA3-384, SHA3-512. This is natively supported by Python 3.6+ and supported via a third-party library on Python 3.5.
    • Choose blinding factor relatively prime to N. Thanks Christian Heimes for pointing this out.
    • Reject cyphertexts (when decrypting) and signatures (when verifying) that have been modified by prepending zero bytes. This resolves CVE-2020-13757. Thanks Adelapie for pointing this out.
    Commits
    • c6731b1 Bumped version to 4.1
    • 80f0e9d Marked version 4.1 as released
    • 65ab5b5 Add support for Python 3.8
    • 9ecf340 Fixed credit for report
    • 93af6f2 Fix CVE-2020-13757: detect cyphertext modifications by prepending zero bytes
    • ae1a906 Add more type hints
    • 1473cb8 Drop character encoding markers for Python 2.x
    • 8ed5071 Choose blinding factor relatively prime to N
    • 1659432 Updated Code Climate badge in README.md
    • 96e13dd Configured CodeClimate
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    dependencies python 
    opened by dependabot[bot] 1
  • Bump jinja2 from 2.10.3 to 2.11.3

    Bump jinja2 from 2.10.3 to 2.11.3

    Bumps jinja2 from 2.10.3 to 2.11.3.

    Release notes

    Sourced from jinja2's releases.

    2.11.3

    This contains a fix for a speed issue with the urlize filter. urlize is likely to be called on untrusted user input. For certain inputs some of the regular expressions used to parse the text could take a very long time due to backtracking. As part of the fix, the email matching became slightly stricter. The various speedups apply to urlize in general, not just the specific input cases.

    2.11.2

    2.11.1

    This fixes an issue in async environment when indexing the result of an attribute lookup, like {{ data.items[1:] }}.

    2.11.0

    This is the last version to support Python 2.7 and 3.5. The next version will be Jinja 3.0 and will support Python 3.6 and newer.

    Changelog

    Sourced from jinja2's changelog.

    Version 2.11.3

    Released 2021-01-31

    • Improve the speed of the urlize filter by reducing regex backtracking. Email matching requires a word character at the start of the domain part, and only word characters in the TLD. :pr:1343

    Version 2.11.2

    Released 2020-04-13

    • Fix a bug that caused callable objects with __getattr__, like :class:~unittest.mock.Mock to be treated as a :func:contextfunction. :issue:1145
    • Update wordcount filter to trigger :class:Undefined methods by wrapping the input in :func:soft_str. :pr:1160
    • Fix a hang when displaying tracebacks on Python 32-bit. :issue:1162
    • Showing an undefined error for an object that raises AttributeError on access doesn't cause a recursion error. :issue:1177
    • Revert changes to :class:~loaders.PackageLoader from 2.10 which removed the dependency on setuptools and pkg_resources, and added limited support for namespace packages. The changes caused issues when using Pytest. Due to the difficulty in supporting Python 2 and :pep:451 simultaneously, the changes are reverted until 3.0. :pr:1182
    • Fix line numbers in error messages when newlines are stripped. :pr:1178
    • The special namespace() assignment object in templates works in async environments. :issue:1180
    • Fix whitespace being removed before tags in the middle of lines when lstrip_blocks is enabled. :issue:1138
    • :class:~nativetypes.NativeEnvironment doesn't evaluate intermediate strings during rendering. This prevents early evaluation which could change the value of an expression. :issue:1186

    Version 2.11.1

    Released 2020-01-30

    • Fix a bug that prevented looking up a key after an attribute ({{ data.items[1:] }}) in an async template. :issue:1141

    ... (truncated)

    Commits

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    dependencies python 
    opened by dependabot[bot] 1
  • Bump pillow from 7.0.0 to 8.1.1

    Bump pillow from 7.0.0 to 8.1.1

    Bumps pillow from 7.0.0 to 8.1.1.

    Release notes

    Sourced from pillow's releases.

    8.1.1

    https://pillow.readthedocs.io/en/stable/releasenotes/8.1.1.html

    8.1.0

    https://pillow.readthedocs.io/en/stable/releasenotes/8.1.0.html

    Changes

    Dependencies

    Deprecations

    ... (truncated)

    Changelog

    Sourced from pillow's changelog.

    8.1.1 (2021-03-01)

    • Use more specific regex chars to prevent ReDoS. CVE-2021-25292 [hugovk]

    • Fix OOB Read in TiffDecode.c, and check the tile validity before reading. CVE-2021-25291 [wiredfool]

    • Fix negative size read in TiffDecode.c. CVE-2021-25290 [wiredfool]

    • Fix OOB read in SgiRleDecode.c. CVE-2021-25293 [wiredfool]

    • Incorrect error code checking in TiffDecode.c. CVE-2021-25289 [wiredfool]

    • PyModule_AddObject fix for Python 3.10 #5194 [radarhere]

    8.1.0 (2021-01-02)

    • Fix TIFF OOB Write error. CVE-2020-35654 #5175 [wiredfool]

    • Fix for Read Overflow in PCX Decoding. CVE-2020-35653 #5174 [wiredfool, radarhere]

    • Fix for SGI Decode buffer overrun. CVE-2020-35655 #5173 [wiredfool, radarhere]

    • Fix OOB Read when saving GIF of xsize=1 #5149 [wiredfool]

    • Makefile updates #5159 [wiredfool, radarhere]

    • Add support for PySide6 #5161 [hugovk]

    • Use disposal settings from previous frame in APNG #5126 [radarhere]

    • Added exception explaining that repr_png saves to PNG #5139 [radarhere]

    • Use previous disposal method in GIF load_end #5125 [radarhere]

    ... (truncated)

    Commits
    • 741d874 8.1.1 version bump
    • 179cd1c Added 8.1.1 release notes to index
    • 7d29665 Update CHANGES.rst [ci skip]
    • d25036f Credits
    • 973a4c3 Release notes for 8.1.1
    • 521dab9 Use more specific regex chars to prevent ReDoS
    • 8b8076b Fix for CVE-2021-25291
    • e25be1e Fix negative size read in TiffDecode.c
    • f891baa Fix OOB read in SgiRleDecode.c
    • cbfdde7 Incorrect error code checking in TiffDecode.c
    • Additional commits viewable in compare view

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    dependencies python 
    opened by dependabot[bot] 1
  • Bump elliptic from 6.5.2 to 6.5.4 in /demos

    Bump elliptic from 6.5.2 to 6.5.4 in /demos

    Bumps elliptic from 6.5.2 to 6.5.4.

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    dependencies javascript 
    opened by dependabot[bot] 1
  • Bump bleach from 3.1.0 to 3.3.0

    Bump bleach from 3.1.0 to 3.3.0

    Bumps bleach from 3.1.0 to 3.3.0.

    Changelog

    Sourced from bleach's changelog.

    Version 3.3.0 (February 1st, 2021)

    Backwards incompatible changes

    • clean escapes HTML comments even when strip_comments=False

    Security fixes

    • Fix bug 1621692 / GHSA-m6xf-fq7q-8743. See the advisory for details.

    Features

    None

    Bug fixes

    None

    Version 3.2.3 (January 26th, 2021)

    Security fixes

    None

    Features

    None

    Bug fixes

    • fix clean and linkify raising ValueErrors for certain inputs. Thank you @Google-Autofuzz.

    Version 3.2.2 (January 20th, 2021)

    Security fixes

    None

    Features

    • Migrate CI to Github Actions. Thank you @hugovk.

    Bug fixes

    • fix linkify raising an IndexError on certain inputs. Thank you @Google-Autofuzz.

    Version 3.2.1 (September 18th, 2020)

    ... (truncated)

    Commits
    • 79b7a3c Merge pull request from GHSA-vv2x-vrpj-qqpq
    • 842fcb4 Update for v3.3.0 release
    • 1334134 sanitizer: escape HTML comments
    • c045a8b Merge pull request #581 from mozilla/nit-fixes
    • 491abb0 fix typo s/vnedoring/vendoring/
    • 10b1c5d vendor: add html5lib-1.1.dist-info/REQUESTED
    • cd838c3 Merge pull request #579 from mozilla/validate-convert-entity-code-points
    • 612b808 Update for v3.2.3 release
    • 6879f6a html5lib_shim: validate unicode points for convert_entity
    • 90cb80b Update for v3.2.2 release
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    dependencies python 
    opened by dependabot[bot] 1
  • Bump lxml from 4.4.2 to 4.6.2

    Bump lxml from 4.4.2 to 4.6.2

    Bumps lxml from 4.4.2 to 4.6.2.

    Changelog

    Sourced from lxml's changelog.

    4.6.2 (2020-11-26)

    Bugs fixed

    • A vulnerability (CVE-2020-27783) was discovered in the HTML Cleaner by Yaniv Nizry, which allowed JavaScript to pass through. The cleaner now removes more sneaky "style" content.

    4.6.1 (2020-10-18)

    Bugs fixed

    • A vulnerability was discovered in the HTML Cleaner by Yaniv Nizry, which allowed JavaScript to pass through. The cleaner now removes more sneaky "style" content.

    4.6.0 (2020-10-17)

    Features added

    • GH#310: lxml.html.InputGetter supports __len__() to count the number of input fields. Patch by Aidan Woolley.

    • lxml.html.InputGetter has a new .items() method to ease processing all input fields.

    • lxml.html.InputGetter.keys() now returns the field names in document order.

    • GH-309: The API documentation is now generated using sphinx-apidoc. Patch by Chris Mayo.

    Bugs fixed

    • LP#1869455: C14N 2.0 serialisation failed for unprefixed attributes when a default namespace was defined.

    • TreeBuilder.close() raised AssertionError in some error cases where it should have raised XMLSyntaxError. It now raises a combined exception to keep up backwards compatibility, while switching to XMLSyntaxError as an interface.

    4.5.2 (2020-07-09)

    ... (truncated)

    Commits
    • 4cb5736 Work around Py2's lack of "re.ASCII".
    • c30106f Prepare release of 4.6.2.
    • a105ab8 Prevent combinations of <math/svg> and <style> to sneak JavaScript through th...
    • c053dc1 Add a recipe for a look-ahead generator to allow modifications during tree it...
    • b083124 lxml actually works in Py3.9.
    • 0f80590 lxml actually works in Py3.9.
    • fd8893c Add a doc note that the .find() methods are usually faster than one might exp...
    • eb6df27 Update release version on homepage.
    • 69b5c9b Automate the build artefact downloading from github and appveyor.
    • 61432a8 Prepare release of lxml 4.6.1.
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    dependencies python 
    opened by dependabot[bot] 1
  • Unable to generate legible recipes using colab notebook

    Unable to generate legible recipes using colab notebook

    Hi, not sure if this repo is still actively maintained. I was playing around with the recipe generation but after the colab was run the results were mostly gibberish. Super short illegible recipes with tons of end characters. Has anyone else experienced this?

    opened by andrewdingcanada8 0
  • Can't access camera MacOS 10.15.7 Chrome 91.0.4472.114

    Can't access camera MacOS 10.15.7 Chrome 91.0.4472.114

    Even though I am able to access my built-in camera using Chrome (e.g. https://webcamtests.com/) I cannot access the camera using the webapp at https://trekhleb.dev/ I tried both apps at https://trekhleb.dev/machine-learning-experiments/#/ I checked my Chrome settings and the site is allowed access to my camera.

    opened by dennisjkane 0
Owner
Oleksii Trekhleb
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Oleksii Trekhleb
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