uSense vs Tensor Camera

This app connects to our custom capacitive sensors via Bluetooth Low-Energy V5.0. For iPhone/iPad/Mac/Apple Watch, the visualization of the connected sensor's normal force, shear force, and proximity will be shown upon user's selection. For iPhone/iPad/Mac, the raw readings can be logged as a CSV file to iOS Files App or macOS Downloads folder. For any question, please contact the developer at gaojian@alumni.ubc.ca.

Introducing our innovative Tensor Camera App, designed to streamline the process of testing and evaluating newly trained models in real-world scenarios. Our app seamlessly integrates with Python servers, providing a user-friendly interface to send camera feeds for instant predictions. Real-time Camera Feed: Capture live camera feeds directly within the app for immediate processing by your Computer Vision models. Whether you're testing object detection, image classification, or any other task, our app delivers real-time results. Python Server Integration: Connect effortlessly with Python servers to leverage the power of your trained models. Our app sends captured images to the server for prediction, ensuring smooth communication and seamless testing. Prediction Display: Receive predictions in real-time, displayed within the app interface. Visualize the model's output directly on your device screen, allowing for quick validation and analysis of results. User-Friendly Interface: Enjoy a seamless user experience with our intuitive and easy-to-navigate interface. Whether you're a seasoned developer or new to Computer Vision testing, our app makes the process accessible to all skill levels. Steps to Use: -Download and install the app from the respective app store on your device. -Go to my GitHub Repository from the App and learn how to set up the server. -Launch the app and configure settings such as server connection details and model selection. -Position your camera to capture the desired scene or object for testing. -Initiate the camera feed within the app and observe real-time predictions generated by your Computer Vision model. -Analyze and evaluate the model's performance based on the displayed predictions. -Optionally, adjust settings or switch to a different model for further testing. Experience the future of Computer Vision testing with our cutting-edge app. Whether you're a researcher, developer, or enthusiast, our app empowers you to test and iterate on your models with ease and efficiency.