Pre-trained Deep Learning models and demos (high quality and extremely fast)
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Updated
Sep 26, 2024 - Python
Pre-trained Deep Learning models and demos (high quality and extremely fast)
image colorizer with OpenCV & Deep-Learning
The Flask-Python web app utilizes a pre-trained image colorization model based on Caffe. It allows users to upload black and white images and applies the colorization model to automatically generate colored versions. The app leverages the power of deep learning to provide an intuitive and interactive way to add color to grayscale images with ease.
An AI based application designed to protect visual privacy by anonymizing faces and obfuscating sensitive textual information (PII) in both images and videos
Dynamsoft Label Recognizer samples for the C/C++ edition
This system leverages computer vision techniques to detect mask usage on individuals at entry points, triggering alerts for non-compliance in real-time using OpenCV and PyQt5 for a user-friendly interface.
Dynamsoft Label Recognizer samples for the Java edition
Dynamsoft Label Recognizer samples for the .Net edition
Object Detection using MobileNet SSD caffe model
A Smart Attendance System using OpenCV for facial recognition to automate attendance tracking.
This is an iOS app that identifies the flower from its photo and also gives detailed information about it.
A video summarization algorithm detects essential events from the surveillance stream and can help index and efficiently retrieve required data from massive datasets.
A gender classification system capable of accurately predicting the gender of individuals from facial images, using pre-trained models
Final Project
Go package for computer vision using OpenCV 3+ and beyond.
This project combines pre-trained Caffe models and OpenCV for age and gender detection in images and videos. It uses OpenCV to load models, identify faces, predict age and gender, and display results visually. The stack includes OpenCV for computer vision and Caffe for deep learning, enabling real-time analysis for insights in market research
utilizing machine learning algorithms and database management techniques to provide students with a list of engineering colleges ranked according to their likelihood of admission.
Largest list of models for Core ML (for iOS 11+)
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