image_classification_yolov8

Making an Image Classifier and deploying it to a webpage

https://github.com/eijilynx/image_classification_yolov8

Science Score: 44.0%

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CITATION.cff file
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codemeta.json file
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Scientific vocabulary similarity
Low similarity (11.3%) to scientific vocabulary

Last synced: 6 months ago · JSON representation ·

Repository

Making an Image Classifier and deploying it to a webpage

Basic Info

Host: GitHub
Owner: EijiLynx
Language: Python
Default Branch: main
Size: 8.46 MB

Statistics

Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 0

Created over 2 years ago · Last pushed over 2 years ago

Metadata Files

Readme Citation

Object Detection Annotation Tool

Welcome to the Object Detection Annotation Tool! This tool is designed to simplify the process of annotating images for object detection tasks using the YOLOv8 model.

Object Detection Annotation Tool

Introduction

Creating annotated datasets for custom object classification is a time-consuming and challenging task. This tool aims to automate and simplify the annotation process using the powerful YOLOv8 model. It provides a user-friendly web interface that allows users to upload images, automatically detect custom object classes, and obtain labels and annotations.

Features

Drag-and-drop or select image upload
Click to upload
Real-time object detection using YOLOv8
Display of detected objects and their labels
Download annotations in JSON format
Preview and download of annotated images

Getting Started

Install the required dependencies using pip install -r requirements.txt.
Run the application using python app.py.

Model Used

The project utilizes the YOLOv8 model from Ultralytics (version 8.0.0) for object detection. This model is known for its accuracy and real-time detection capabilities.

Custom Classes

The YOLOv8 model is trained to detect the following custom object classes:

Birds
Cats
Dogs
Person

Technologies Used

Flask: Web application framework
HTML, JavaScript, and Tailwind CSS: Frontend development
Ultralytics YOLOv8: Object detection model
Flask-Nav: Navigation extension for Flask

Usage

Access the web interface at http://localhost:5000 in your web browser.
Upload images using drag-and-drop or the file manager.
Click the "Upload and Classify" button to perform object detection.
View the detected objects and their labels on the results page.
Download annotations and annotated images.

Navigation

The web application includes the following sections:

Home: Landing page with project overview
Upload & Classify: Allows users to upload images and perform automatic classification
View Results: Displays annotated results and allows users to view images and annotations
Download: Provides the option to download annotated results in txt format

Images

Project Logo

Owner

Login: EijiLynx
Kind: user

Repositories: 1
Profile: https://github.com/EijiLynx

Citation (CITATION.cff)

cff-version: 1.2.0
preferred-citation:
  type: software
  message: If you use this software, please cite it as below.
  authors:
  - family-names: Jocher
    given-names: Glenn
    orcid: "https://orcid.org/0000-0001-5950-6979"
  - family-names: Chaurasia
    given-names: Ayush
    orcid: "https://orcid.org/0000-0002-7603-6750"
  - family-names: Qiu
    given-names: Jing
    orcid: "https://orcid.org/0000-0003-3783-7069"
  title: "YOLO by Ultralytics"
  version: 8.0.0
  # doi: 10.5281/zenodo.3908559  # TODO
  date-released: 2023-1-10
  license: AGPL-3.0
  url: "https://github.com/ultralytics/ultralytics"

GitHub Events

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Dependencies

package-lock.json npm

@alloc/quick-lru 5.2.0
@jridgewell/gen-mapping 0.3.3
@jridgewell/resolve-uri 3.1.0
@jridgewell/set-array 1.1.2
@jridgewell/sourcemap-codec 1.4.15
@jridgewell/sourcemap-codec 1.4.14
@jridgewell/trace-mapping 0.3.18
@nodelib/fs.scandir 2.1.5
@nodelib/fs.stat 2.0.5
@nodelib/fs.walk 1.2.8
any-promise 1.3.0
anymatch 3.1.3
arg 5.0.2
balanced-match 1.0.2
binary-extensions 2.2.0
brace-expansion 1.1.11
braces 3.0.2
camelcase-css 2.0.1
chokidar 3.5.3
commander 4.1.1
concat-map 0.0.1
cssesc 3.0.0
didyoumean 1.2.2
dlv 1.1.3
fast-glob 3.3.1
fastq 1.15.0
fill-range 7.0.1
fs.realpath 1.0.0
fsevents 2.3.2
function-bind 1.1.1
glob 7.1.6
glob-parent 5.1.2
glob-parent 6.0.2
has 1.0.3
inflight 1.0.6
inherits 2.0.4
is-binary-path 2.1.0
is-core-module 2.12.1
is-extglob 2.1.1
is-glob 4.0.3
is-number 7.0.0
jiti 1.19.1
lilconfig 2.1.0
lines-and-columns 1.2.4
merge2 1.4.1
micromatch 4.0.5
minimatch 3.1.2
mz 2.7.0
nanoid 3.3.6
normalize-path 3.0.0
object-assign 4.1.1
object-hash 3.0.0
once 1.4.0
path-is-absolute 1.0.1
path-parse 1.0.7
picocolors 1.0.0
picomatch 2.3.1
pify 2.3.0
pirates 4.0.6
postcss 8.4.27
postcss-import 15.1.0
postcss-js 4.0.1
postcss-load-config 4.0.1
postcss-nested 6.0.1
postcss-selector-parser 6.0.13
postcss-value-parser 4.2.0
queue-microtask 1.2.3
read-cache 1.0.0
readdirp 3.6.0
resolve 1.22.2
reusify 1.0.4
run-parallel 1.2.0
source-map-js 1.0.2
sucrase 3.34.0
supports-preserve-symlinks-flag 1.0.0
tailwindcss 3.3.3
thenify 3.3.1
thenify-all 1.6.0
to-regex-range 5.0.1
ts-interface-checker 0.1.13
util-deprecate 1.0.2
wrappy 1.0.2
yaml 2.3.1

package.json npm

tailwindcss ^3.1.8

requirements.txt pypi

Pillow >=7.1.2
PyYAML >=5.3.1
matplotlib >=3.2.2
opencv-python >=4.6.0
pandas >=1.1.4
psutil *
requests >=2.23.0
scipy >=1.4.1
seaborn >=0.11.0
torch >=1.7.0
torchvision >=0.8.1
tqdm >=4.64.0

setup.py pypi

ecosyste.ms

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