https://github.com/zenklinov/image-recognition

This project is a simple image classification application built using PyTorch and Streamlit. It utilizes the pre-trained ResNet50 model to classify images and provides input options via file upload, URL input, or URL copied from the clipboard.
https://github.com/zenklinov/image-recognition

deep-learning image-classification streamlit

Last synced: about 1 month ago
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This project is a simple image classification application built using PyTorch and Streamlit. It utilizes the pre-trained ResNet50 model to classify images and provides input options via file upload, URL input, or URL copied from the clipboard.

• Host: GitHub
• URL: https://github.com/zenklinov/image-recognition
• Owner: zenklinov
• License: apache-2.0
• Created: 2024-05-29T04:36:43.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2025-02-24T11:47:07.000Z (over 1 year ago)
• Last Synced: 2025-02-24T12:35:31.973Z (over 1 year ago)
• Topics: deep-learning, image-classification, streamlit
• Language: Python
• Homepage: https://image-recognition-6jn7ljvtsbxod7zwpardzn.streamlit.app/
• Size: 15.6 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Image Classifier with ResNet50 and Streamlit

This project is a simple image classification application built using PyTorch and Streamlit. It utilizes the pre-trained ResNet50 model to classify images and provides input options via file upload, URL input, or URL copied from the clipboard.

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## Features

- **Upload Local Image File**: Supports formats such as JPEG, PNG, BMP, GIF, and TIFF.

- **Classify Image from URL**: Paste an image URL to classify.

- **Clipboard Integration**: Automatically retrieve and classify images from URLs copied to the clipboard.

- **Top-5 Predictions**: Displays the top-5 predicted classes with their probabilities.

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## Prerequisites

- Python 3.8 or later

- Install required libraries using `requirements.txt`.

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## To Use

Click to Link: https://image-recognition-6jn7ljvtsbxod7zwpardzn.streamlit.app/