A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
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Updated
May 3, 2024 - Python
A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
A generator help you spawn key word for AI drawing
IntelliP (Intelligent Photos) is a Windows photo gallery that intelligently organizes the pictures in your computer into 12 unique and related categories.
Simple whatsapp chatbot for send and receive response from openai.
Action-Net is a dataset containing images of 16 different human actions.
🤖 Autonomous Drone DJI Tello with OpenCv and ImageAI
Complete proof of concept combining artificial intelligence, machine learning, and thousands of publicly available traffic cameras to place an entire city under surveillance with inference bots watching for a stolen car every single moment.
A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities.
This project offers two Flask applications that utilize ImageAI's image prediction algorithms and object detection models. These apps enable users to upload images and videos for object recognition, detection and analysis, providing accurate prediction results, confidence scores, raw data of detected objects at frame-level, and object insights.
An application which can run object detection tasks from device cameras and IP cameras in real time.
Code for creation of a prototype model of a social robot 🔌 by integrating different domains like Android📱, ML💡, Image Processing🌁 etc
Object Detection simple web app using Flask, ImageAI and Tenserflow
imageai物体识别,小demo,封装成pyqt5界面,采用mvc模型,简单实用。
Python image recognition libraries process the image sent with the api and look at the object, classification, intense colors of the image and whether the image is safe or not.
Object Detection via pre-trained YOLOv3 is used to detect vehicles from an image. Transfer learning on ResNet-50 outer layers with a two-class dataset trains for 50 epochs. 81% accuracy.
Telegram bot is able to recognize the image in the picture (In my case, the bot is able to recognize four brands of cars)
🐵 SurveyMonkey’s API Challenge Winner @ Hack the North: Automation of survey responses using Machine Learning
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