Giter Club home page Giter Club logo

tensorpy's Introduction

TensorPy

pypi GitHub stars Python version MIT License Join the chat at https://gitter.im/TensorPy/Lobby

Easy Image Classification with TensorFlow

TensorPy Tutorial

(Watch the 2-minute tutorial on YouTube)

Now runs much faster since video released!

You can use TensorPy to classify images by simply passing a URL on the command line, or by using TensorPy in your Python programs. TensorFlow does all the image-recognition work. TensorPy also simplifies TensorFlow installation by automating several setup steps into a single script (See install.sh for details).

(Read how_tensorpy_works for a detailed explanation of how TensorPy works.)

Setup Steps for Mac & Ubuntu/Linux

(Windows & Docker users: See the Docker ReadMe for running on a Docker machine. Windows requires Docker to run TensorFlow.)

Step 1: Create and activate a virtual environment named "tensorpy"

If you're not sure how to create a virtual environment, follow these instructions to learn how.

Step 2: Clone the TensorPy repo from GitHub

git clone https://github.com/TensorPy/TensorPy.git
cd TensorPy

Step 3: Install TensorPy, TensorFlow, and ImageNet/Inception

The install.sh script installs everything you need:

./install.sh

Step 4: Run the examples

Classify a single image from a URL:

classify "http://cdn2.hubspot.net/hubfs/100006/happy_animal.jpg"

Classify all images on a web page:

classify "https://github.com/TensorPy/TensorPy/tree/master/examples/images"

Classify a single image URL from a Python script: (See test_python_classify.py for details.)

python examples/test_python_classify.py

Classify an image from a local file path:

classify examples/images/cat_animal.jpg

Classify all images from a local folder:

classify examples/images/

Classify an image from a local file path using a Python script: (See test_python_file_classify.py for details.)

cd examples
python test_python_file_classify.py

Classify all images in a local folder using a Python script (Output = LIST): (See test_python_folder_classify.py for details.)

cd examples
python test_python_folder_classify.py

Classify all images in a local folder using a Python script (Output = DICTIONARY): (See test_python_folder_classify_dict.py for details.)

cd examples
python test_python_folder_classify_dict.py

Future Work:

Eventually, the headline will change from "Image Classification with TensorFlow made easy!" to "Machine Learning with TensorFlow made easy!" once I expand on TensorPy to make other features of TensorFlow easier too. Stay tuned for updates!

tensorpy's People

Contributors

mdmintz avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.