A python-image-classification web application project, written in Python and served through the Flask Microframework. This Project implements the VGG16 covolutional neural network, through Keras and Tensorflow wrappers, to make predictions on uploaded images.

Last update: Dec 12, 2022

Related tags

Overview

Image Classification in Python

Implementing image classification in Flask using Keras.

The VGG16 is a convolution neural network model architecture that is the best classifier for images till today. This project implements the classifier through Keras. This appplication was written in Python. It also utilizes the Flask Microframework, as the server to render a template, and pass the submitted file to the prediction model. It also uses Keras modules to perform image classification.

Requirements

Python 3.5+
Pip (For installing modules)
Flask Download
Tensorflow
Keras Modules

Installation

(Plain Set Up)

Go ahead an clone this specific repository. You could do this through the command below:

> git clone https://github.com/grayoj/Python-Image-Classification.git

Then navigate to the directory. If you use VSCode, you could avoid interacting with the terminal.

Run the following commands in the directory:

> pythom -m flask run

(Full Set Up)

Go ahead an clone this specific repository. You could do this through the command below:

> git clone https://github.com/grayoj/Python-Image-Classification.git

To install Python, download here. If you already have Python 3.5 installed, you may proceed to the next steps below:

You will notice this line of code in the app.py file:

To ensure the modules would be imported on your system, into the project, run the following command:

> pip install flask

That would install flask on your local machine. Next step is to install the Keras Modules, and packages required. Run the following command:

> pip install keras

If you use Pylance, it should validate the imports above in the app.py. i.e show no errors, of modules missing. Modules being installed:

You would have to install Tensorflow as well.

> pip install tensorflow

You are set. Now let's dial in to a localhost port.

> python -m flask run

Viola, the application should load sucessfully. If there are any errors, ensure you installed the modules properly.

Http://127.0.0.1:5000

Don't worry if you notice a sudden download process. Tensorflow would begin to download dependencies for the VGG16 Covolutional Neural network model.

Prediction in action

Now, the fun part. This should have loaded open:

Let's see whether our model can predict what this animal is: The picture used is in the repository. You could use other images, and have fun.

Now let's input it

Click on predict

Our model predicted a tiger cat! Epic.

More Information

Reach out to me if you have questions or suggestions. Would love to connect.

Twitter: @geraldabuchi

Python-Image-Classification

Flask, Keras, Tensorflow, VGG16

Using python and scikit-learn to make stock predictions

MachineLearningStocks in python: a starter project and guide EDIT as of Feb 2021: MachineLearningStocks is no longer actively maintained MachineLearni

1.3k Dec 29, 2022

🔮 Execution time predictions for deep neural network training iterations across different GPUs.

Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Habitat is a tool that predicts a deep neural network's

44 Dec 27, 2022

Framework that uses artificial intelligence applied to mathematical models to make predictions

LiconIA Framework that uses artificial intelligence applied to mathematical models to make predictions Interface Overview Table of contents [TOC] 1 Ar

4 Jun 20, 2021

Some code of the implements of Geological Modeling Using 3D Pixel-Adaptive and Deformable Convolutional Neural Network

3D-GMPDCNN Geological Modeling Using 3D Pixel-Adaptive and Deformable Convolutional Neural Network PyTorch implementation of "Geological Modeling Usin

5 Nov 21, 2022

This framework implements the data poisoning method found in the paper Adversarial Examples Make Strong Poisons

Adversarial poison generation and evaluation. This framework implements the data poisoning method found in the paper Adversarial Examples Make Strong

31 Nov 1, 2022

A tensorflow/keras implementation of StyleGAN to generate images of new Pokemon.

PokeGAN A tensorflow/keras implementation of StyleGAN to generate images of new Pokemon. Dataset The model has been trained on dataset that includes 8

19 Jul 26, 2022

An end-to-end machine learning web app to predict rugby scores (Pandas, SQLite, Keras, Flask, Docker)

Rugby score prediction An end-to-end machine learning web app to predict rugby scores Overview An demo project to provide a high-level overview of the

34 May 24, 2022

Digitalizing-Prescription-Image - PIRDS - Prescription Image Recognition and Digitalizing System is a OCR make with Tensorflow

Digitalizing-Prescription-Image PIRDS - Prescription Image Recognition and Digit

2 May 11, 2022

A real world application of a Recurrent Neural Network on a binary classification of time series data

What is this This is a real world application of a Recurrent Neural Network on a binary classification of time series data. This project includes data

2 Jan 30, 2022

Comments

Add CodeQL workflow for GitHub code scanning
Hi grayoj/image-classifier!

This is a one-off automatically generated pull request from LGTM.com :robot:. You might have heard that we’ve integrated LGTM’s underlying CodeQL analysis engine natively into GitHub. The result is GitHub code scanning!

With LGTM fully integrated into code scanning, we are focused on improving CodeQL within the native GitHub code scanning experience. In order to take advantage of current and future improvements to our analysis capabilities, we suggest you enable code scanning on your repository. Please take a look at our blog post for more information.

This pull request enables code scanning by adding an auto-generated codeql.yml workflow file for GitHub Actions to your repository — take a look! We tested it before opening this pull request, so all should be working :heavy_check_mark:. In fact, you might already have seen some alerts appear on this pull request!

Where needed and if possible, we’ve adjusted the configuration to the needs of your particular repository. But of course, you should feel free to tweak it further! Check this page for detailed documentation.

Questions? Check out the FAQ below!

FAQ

Click here to expand the FAQ section

How often will the code scanning analysis run?

By default, code scanning will trigger a scan with the CodeQL engine on the following events:

On every pull request — to flag up potential security problems for you to investigate before merging a PR.

On every push to your default branch and other protected branches — this keeps the analysis results on your repository’s Security tab up to date.

Once a week at a fixed time — to make sure you benefit from the latest updated security analysis even when no code was committed or PRs were opened.

What will this cost?

Nothing! The CodeQL engine will run inside GitHub Actions, making use of your unlimited free compute minutes for public repositories.

What types of problems does CodeQL find?

The CodeQL engine that powers GitHub code scanning is the exact same engine that powers LGTM.com. The exact set of rules has been tweaked slightly, but you should see almost exactly the same types of alerts as you were used to on LGTM.com: we’ve enabled the security-and-quality query suite for you.

How do I upgrade my CodeQL engine?

No need! New versions of the CodeQL analysis are constantly deployed on GitHub.com; your repository will automatically benefit from the most recently released version.

The analysis doesn’t seem to be working

If you get an error in GitHub Actions that indicates that CodeQL wasn’t able to analyze your code, please follow the instructions here to debug the analysis.

How do I disable LGTM.com?

If you have LGTM’s automatic pull request analysis enabled, then you can follow these steps to disable the LGTM pull request analysis. You don’t actually need to remove your repository from LGTM.com; it will automatically be removed in the next few months as part of the deprecation of LGTM.com (more info here).

Which source code hosting platforms does code scanning support?

GitHub code scanning is deeply integrated within GitHub itself. If you’d like to scan source code that is hosted elsewhere, we suggest that you create a mirror of that code on GitHub.

How do I know this PR is legitimate?

This PR is filed by the official LGTM.com GitHub App, in line with the deprecation timeline that was announced on the official GitHub Blog. The proposed GitHub Action workflow uses the official open source GitHub CodeQL Action. If you have any other questions or concerns, please join the discussion here in the official GitHub community!

I have another question / how do I get in touch?

Please join the discussion here to ask further questions and send us suggestions!
opened by lgtm-com[bot] 0

Releases(v1.0.0)

v1.0.0(Jul 25, 2022)

First release of the image-classifier.
Source code(tar.gz)
Source code(zip)

Owner

Gerald Maduabuchi

Computer Programmer. ML Enthusiast C++, Python, PHP and JavaScript

GitHub Repository

Image Segmentation Animation using Quadtree concepts.

QuadTree Image Segmentation Animation using QuadTree concepts. Usage usage: quad.py [-h] [-fps FPS] [-i ITERATIONS] [-ws WRITESTART] [-b] [-img] [-s S

29 Dec 25, 2022

Which Style Makes Me Attractive? Interpretable Control Discovery and Counterfactual Explanation on StyleGAN

Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN Which Style Makes Me Attractive? Interpretable Control Discovery an

11 Dec 01, 2022

Code for the paper: Fighting Fake News: Image Splice Detection via Learned Self-Consistency

Fighting Fake News: Image Splice Detection via Learned Self-Consistency [paper] [website] Minyoung Huh *12, Andrew Liu *1, Andrew Owens1, Alexei A. Ef

174 Dec 09, 2022

On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks

On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks We provide the code (in PyTorch) and datasets for our paper "On Size-Orient

4 Jun 18, 2022

Flybirds - BDD-driven natural language automated testing framework, present by Trip Flight

Flybird | English Version 行为驱动开发（Behavior-driven development，缩写BDD），是一种软件过程的思想或者

706 Dec 30, 2022

An official repository for Paper "Uformer: A General U-Shaped Transformer for Image Restoration".

Uformer: A General U-Shaped Transformer for Image Restoration Zhendong Wang, Xiaodong Cun, Jianmin Bao and Jianzhuang Liu Paper: https://arxiv.org/abs

497 Dec 22, 2022

Multimodal Temporal Context Network (MTCN)

Multimodal Temporal Context Network (MTCN) This repository implements the model proposed in the paper: Evangelos Kazakos, Jaesung Huh, Arsha Nagrani,

13 Nov 24, 2022

Creating a Linear Program Solver by Implementing the Simplex Method in Python with NumPy

Creating a Linear Program Solver by Implementing the Simplex Method in Python with NumPy Simplex Algorithm is a popular algorithm for linear programmi

2 Oct 12, 2022

Deep Learning Head Pose Estimation using PyTorch.

Hopenet is an accurate and easy to use head pose estimation network. Models have been trained on the 300W-LP dataset and have been tested on real data with good qualitative performance.

1.3k Dec 26, 2022

Classifies galaxy morphology with Bayesian CNN

Zoobot Zoobot classifies galaxy morphology with deep learning. This code will let you: Reproduce and improve the Galaxy Zoo DECaLS automated classific

39 Dec 20, 2022

Very simple NCHW and NHWC conversion tool for ONNX. Change to the specified input order for each and every input OP. Also, change the channel order of RGB and BGR. Simple Channel Converter for ONNX.

scc4onnx Very simple NCHW and NHWC conversion tool for ONNX. Change to the specified input order for each and every input OP. Also, change the channel

16 Dec 22, 2022

Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation"

Medical-Transformer Pytorch Code for the paper "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" About this repo: This repo

615 Dec 25, 2022

Official repo for our 3DV 2021 paper "Monocular 3D Reconstruction of Interacting Hands via Collision-Aware Factorized Refinements".

Monocular 3D Reconstruction of Interacting Hands via Collision-Aware Factorized Refinements Yu Rong, Jingbo Wang, Ziwei Liu, Chen Change Loy Paper. Pr

41 Dec 13, 2022

Codebase for Image Classification Research, written in PyTorch.

pycls pycls is an image classification codebase, written in PyTorch. It was originally developed for the On Network Design Spaces for Visual Recogniti

2k Jan 01, 2023

Fast and simple implementation of RL algorithms, designed to run fully on GPU.

RSL RL Fast and simple implementation of RL algorithms, designed to run fully on GPU. This code is an evolution of rl-pytorch provided with NVIDIA's I

68 Dec 29, 2022

Unified API to facilitate usage of pre-trained "perceptor" models, a la CLIP

mmc installation git clone https://github.com/dmarx/Multi-Modal-Comparators cd 'Multi-Modal-Comparators' pip install poetry poetry build pip install d

37 Nov 25, 2022

Seach Losses of our paper 'Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search', accepted by ICLR 2021.

CSE-Autoloss Designing proper loss functions for vision tasks has been a long-standing research direction to advance the capability of existing models

54 Dec 17, 2022