ISC NIRScan vs Visual Finder

The ISC NIRScan is now supporting the scanners of STD (900nm-1700nm), EXT (1350nm-2150nm) and PLUS (1600nm-2400nm) wavelength versions.

Visual Finder is an iPhone / iPad app for real-time object detection using the device camera. It lets you find objects in the camera preview, display detection results as bounding boxes or masks, review detected classes, positions, counts, confidence values, cropped object images, and session statistics directly on the device. Main Features * Real-time object detection using the device camera * Bounding box detection mode for fast object localization * Mask detection mode for object region visualization * Support for 81 object classes, including people, vehicles, animals, daily items, food, furniture, electronics, and more * Selection of specific detection targets * Search and filtering of detectable object classes * Live overlay of detected objects on the camera preview * Display of inference FPS, detection count, confidence, and detection status * Adjustable detection speed, confidence threshold, IoU threshold, and minimum object size * Camera switching between available device cameras * Support for compatible external cameras connected to iPad via USB-C * Cropped image preview of detected objects * Saving selected cropped detection images to the photo library * Session logging for detection results * Class-level detection statistics and charts * CSV export of session logs * Settings for logging, crop history, haptic feedback, and display language Visual Finder is designed for checking object detection behavior in real-world scenes, comparing bounding box and mask detection, adjusting detection parameters, and reviewing results after each session. During detection, the app shows where objects are found in the camera image and summarizes what classes appeared, how often they were detected, and how stable the results were during the session. Detected objects can be reviewed as cropped images. In mask mode, object crops can be generated along the detected object region, making it easier to inspect individual detection results or save visual samples for later review. Session logs include information such as the detection mode, selected detection targets, session start and end time, total detections, detected classes, class-level counts, detected frame count, appearance rate, average confidence, average detection area, and maximum detections per frame. Logs can be reviewed inside the app with charts and exported as CSV files for spreadsheet software, analysis tools, or development workflows. The app performs detection locally on the device. Camera frames, detection results, cropped images, and session logs are not uploaded to an external server by the app. Supported Devices * iPhone and iPad models with a supported built-in camera * iPad models that support compatible external cameras connected via USB-C * Devices capable of running the included Core ML object detection models Camera availability, external camera support, detection speed, supported modes, and performance vary depending on the device, connected camera, camera configuration, OS version, and model settings. Detection results are provided for reference, testing, and analysis purposes only. Results may vary depending on device performance, lighting, object size, camera angle, motion, occlusion, and other scene conditions. The app is not intended for medical, safety-critical, legal, surveillance, or identity verification use.