bonding_w_geimini

A Streamlit application utilizing the Gemini API for image object detection.

CommonProductImageImage ProcessingObject Detection

bonding_w_geimini is an image processing application developed on the Streamlit framework, allowing users to upload images for object detection via the Gemini API and draw bounding boxes directly on the images. This application leverages machine learning models to identify and locate objects within images, playing a significant role in fields like image analysis, data annotation, and automated image processing.

Supports uploading images in JPG
JPEG
and PNG formats
Detects objects via the Gemini API and returns bounding box coordinates
Visualizes detected bounding boxes on the images
allowing for custom labeling
Downloads images with bounding boxes included
Requires a Python 3.9 or higher runtime environment
Requires a valid Gemini API key

The target audience includes data scientists
image processing engineers
machine learning researchers
and individuals interested in automated image analysis. This product is particularly suited for users who need rapid and accurate image object detection and annotation
especially in scenarios requiring extensive image data labeling.

Automating the classification and annotation of product images for e-commerce websites
Assisting researchers in identifying specific cells or tissues in biomedical images
Real-time analysis of abnormal behaviors in video streams within security surveillance

Clone the repository locally: git clone https://github.com/AlexZhangji/bonding_w_geimini.git
Navigate to the project directory: cd bonding_w_geimini
Install the necessary Python packages
Run the Streamlit application: streamlit run bbox.py
Enter your Gemini API key in the sidebar

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bonding_w_geimini Visit Over Time

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503747431

Bounce Rate

37.31%

Page per Visit

5.7

Visit Duration

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