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computer-vision, concept-aware segmentation, Detection, gradio app, hugging face transformers, multi-object tracking, object tracking, pytorch, SAM3, segmentation, single-click tracking, streaming inference, text-prompt tracking, Tracking, tutorial, video segmentation, video tracking, webcam segmentation

SAM 3 for Video: Concept-Aware Segmentation and Object Tracking

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Table of Contents SAM 3 for Video: Concept-Aware Segmentation and Object Tracking Configuring Your Development Environment Setup and Imports Text-Prompt Video Tracking Load the SAM3 Video Model Helper Function: Visualizing Video Segmentation Masks, Bounding Boxes, and Tracking IDs Main Pipeline:…

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AI & Machine Learning, approximate nearest neighbor, citation support, embeddings, faiss, hnsw, llm grounding, llmops, local llm, Natural Language Processing, ollama, python, RAG, retrieval augmented generation, semantic-search, sentence transformers, tutorial, Vector Databases, vector-search

Vector Search Using Ollama for Retrieval-Augmented Generation (RAG)

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Table of Contents Vector Search Using Ollama for Retrieval-Augmented Generation (RAG) How Vector Search Powers Retrieval-Augmented Generation (RAG) From Search to Context The Flow of Meaning Putting It All Together What Is Retrieval-Augmented Generation (RAG)? The Retrieve-Read-Generate Architecture Explained Why…

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ann, approximate nearest neighbor, cosine similarity, deep-learning, embeddings, faiss, flat index, hnsw, ivf, RAG, recall at k, retrieval augmented generation, semantic-search, tutorial, vector database, Vector Databases, vector-search

Vector Search with FAISS: Approximate Nearest Neighbor (ANN) Explained

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Table of Contents Vector Search with FAISS: Approximate Nearest Neighbor (ANN) Explained From Exact to Approximate: Why Indexing Matters The Trouble with Brute-Force Search The Curse of Dimensionality Enter the Approximate Nearest Neighbor (ANN) Accuracy vs. Latency: The Core Trade-Off…

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cosine similarity, embeddings, Machine Learning, nlp, RAG, semantic-search, sentence transformers, tf-idf, tutorial, Vector Databases

TF-IDF vs. Embeddings: From Keywords to Semantic Search

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Table of Contents TF-IDF vs. Embeddings: From Keywords to Semantic Search Series Preamble: From Text to RAG What You’ll Build Across the Series Project Structure Why Start with Embeddings The Problem with Keyword Search When “Different Words” Mean the Same…

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bounding box prompts, computer-vision, Detection, Gradio, Interactive, interactive segmentation, multi-modal prompting, PCS, point prompts, Prompting, pytorch, sam 3, segment anything model, segmentation, text prompts, tutorial

Advanced SAM 3: Multi-Modal Prompting and Interactive Segmentation

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Table of Contents Advanced SAM 3: Multi-Modal Prompting and Interactive Segmentation Configuring Your Development Environment Setup and Imports Loading the SAM 3 Model Downloading a Few Images Multi-Text Prompts on a Single Image Batched Inference Using Multiple Text Prompts Across…

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computer-vision, deep-learning, image segmentation, Meta AI, open-vocabulary, PCS, promptable concept segmentation, promptable visual segmentation, Prompting, PVS, sam 3, segment anything, tutorial, vision transformers

SAM 3: Concept-Based Visual Understanding and Segmentation

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Table of Contents SAM 3: Concept-Based Visual Understanding and Segmentation The Evolution of Segment Anything: From Geometry to Concepts Core Model Architecture and Technical Components The Perception Encoder (PE) and Vision Backbone The Open-Vocabulary Text and Exemplar Encoders The DETR-Based…

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