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Comprehensive guide to using Salesforce's BLIP-2 for vision-language tasks with frozen image encoders and large language models.

Detect text, faces, barcodes, objects, and body poses in images and video using on-device computer vision. Patterns target iOS 26+ with Swift 6.3, backward-compatible where noted.

Apple Vision Framework for computer vision tasks: subject segmentation, pose detection, text recognition, barcode scanning, and document processing. \n \n Covers 13+ Vision APIs across subject lifting, hand/body pose, person segmentation, text OCR, barcode detection, and document scanning with decision trees for choosing the right tool \n Includes 15 production patterns: combining APIs to exclude hands from objects, real-time gesture recognition, multi-person segmentation, fitness action classif

Expert guidance for computer vision development using OpenCV, PyTorch, and deep learning techniques. \n \n Covers traditional image processing (filtering, edge detection, morphological operations, geometric transformations) and modern deep learning approaches (YOLO, Faster R-CNN, transfer learning with pre-trained models) \n Includes feature detection and matching (SIFT, ORB, FLANN), object detection with proper bounding box handling, and video processing with frame-by-frame pipelines and object

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