Hire the Best Pattern Recognition Specialists

𝗜 𝗯𝘂𝗶𝗹𝗱 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗿𝗲𝗮𝗱𝘆 𝗔𝗜 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝘁𝗵𝗮𝘁 𝗽𝗮𝘆 𝗳𝗼𝗿 𝘁𝗵𝗲𝗺𝘀𝗲𝗹𝘃𝗲𝘀: I saved a fintech client €𝟰𝟬,𝟬𝟬𝟬 𝗽𝗲𝗿 𝘆𝗲𝗮𝗿 by automating their KYC pipeline (𝟵𝟵%+ 𝗲𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆) and cut clinical documentation time by 𝟲𝟬% with an AI medical scribe inside a live EMR platform. If you have messy documents, manual workflows, or an agent or chatbot idea that needs to actually work in production, not just in a demo, I can ship it fast without sacrificing accuracy or scalability. 𝗪𝗛𝗔𝗧 𝗜 𝗕𝗨𝗜𝗟𝗗 🔹 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 & 𝗠𝘂𝗹𝘁𝗶 𝗔𝗴𝗲𝗻𝘁 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: autonomous, decision making agents with LangChain, LangGraph and CrewAI that automate real backend processes: document review, support, lead handling, internal ops. 🔹 𝗥𝗔𝗚 𝗖𝗵𝗮𝘁𝗯𝗼𝘁𝘀 & 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁𝘀: retrieval augmented generation chatbots over your PDFs, docs and databases. Hybrid GraphRAG (Neo4j) plus vector search for grounded, accurate answers with strict guardrails against hallucination. 🔹 𝗢𝗖𝗥 & 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗔𝗜: invoice, ID and form data extraction with PaddleOCR, AWS Textract, YOLO and LayoutLM. 𝟵𝟵%+ 𝗲𝘅𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆 on IDs, invoices, tables and unstructured documents. 🔹 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗔𝗜 & 𝗘𝗠𝗥 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: HIPAA compliant medical scribes (Whisper speech to text, speaker diarization, auto generated SOAP notes and ICD 10 codes), wound analysis computer vision, clinical RAG with PII redaction. 🔹 𝗞𝗬𝗖 & 𝗜𝗱𝗲𝗻𝘁𝗶𝘁𝘆 𝗩𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻: document localization, MRZ parsing, ArcFace biometric matching, liveness detection, real time transaction risk engines. 𝗥𝗘𝗦𝗨𝗟𝗧𝗦 𝗖𝗟𝗜𝗘𝗡𝗧𝗦 𝗣𝗔𝗜𝗗 𝗙𝗢𝗥 €𝟰𝟬𝗞 𝗽𝗲𝗿 𝘆𝗲𝗮𝗿 𝘀𝗮𝘃𝗲𝗱: automated fintech KYC pipeline (OCR plus face match plus verification agents) 𝟲𝟬% 𝗹𝗲𝘀𝘀 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝘁𝗶𝗺𝗲: AI medical scribe running in a production EMR 𝟰𝟬% 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆 𝘂𝗽𝗹𝗶𝗳𝘁: hybrid GraphRAG retrieval for complex financial queries 𝟭𝟬𝘅 𝗳𝗮𝘀𝘁𝗲𝗿 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴: logistics and finance workflows 𝗦𝘂𝗯 𝟮𝟬𝟬𝗺𝘀 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗹𝗮𝘁𝗲𝗻𝗰𝘆: FastAPI microservices with Redis caching 𝗧𝗘𝗖𝗛 𝗦𝗧𝗔𝗖𝗞 Python, FastAPI, Docker, AWS, GCP | LangChain, LangGraph, CrewAI, OpenAI, Claude, Hugging Face | Pinecone, FAISS, Weaviate, Neo4j, MongoDB, Redis | OpenCV, YOLO, PaddleOCR, Tesseract, LayoutLM | PyTorch, TensorFlow 𝗛𝗢𝗪 𝗜 𝗪𝗢𝗥𝗞 Fast execution with production discipline: clear milestones, regular updates, clean documented code, containerized deployment. I use modern AI dev tooling (including Claude Code) to ship in days what normally takes weeks, without cutting corners on architecture. If you want an AI system that works in production, send me an invite or message and let's scope it in a quick call. 𝗞𝗲𝘆𝘄𝗼𝗿𝗱𝘀: AI Engineer, AI Agent Developer, AI Agents, Multi Agent Systems, RAG, Retrieval Augmented Generation, Chatbot Development, LLM Integration, GPT 4o, Claude, LangChain, LangGraph, CrewAI, OCR, Document AI, Data Extraction, Computer Vision, Healthcare AI, EMR Automation, KYC Automation, Identity Verification, NLP, Python, FastAPI

With 11 years of total industry experience I have contributed and managed projects related to Computer vision and Machine learning applications as listed below: 1.) Object detection: i.) Counting application(YOLO algorithm) ii.) Location mapping of person for Intrusion detection and same for vehicles for Vehicle speed detection 2.) Image segmentation: i.) Temperature detection from stickers used by healthcare professionals. ii.) Blood smear and Radiology images analysis for malaria type and lung health detection respectively. 3.) Inventory tracking and detecting pick/place activity using camera+RaspberryPI5 based solution. 4.) Demand forecasting for production planning in Agricultural & Dairy sector using Time series forecasting as a part of Inventory & Resources planning. 5.) Data extraction from PDFs', OCR for document data extraction. The business areas in which the projects were implemented are Healthcare, FMCG, Dairy & Heavy engineering. I am proficient in handling projects independently and completing with desired accuracy . My range of expertise are: 1.) Algorithms for Data Science: Investment portfolio optimization & Trading signals(buy&sell) from backtesting. 2.) Computer vision: Image processing, Segmentation, Object detection, Classification using tensorflow/pytorch framework. 3.) Data Analysis: Data aggregation, metrics evaluation and building insights from .csv/.xlsx data using pandas library. 4.) Database management: SQL & MongoDB 5.) Machine learning models: Decision trees, Regression based methods like ARIMA and Logistic Regression.

𝐏𝐫𝐞𝐦𝐢𝐮𝐦 𝐓𝐫𝐚𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐨𝐫 𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐃𝐞𝐬𝐢𝐠𝐧 & 𝐇𝐚𝐧𝐝-𝐈𝐥𝐥𝐮𝐬𝐭𝐫𝐚𝐭𝐞𝐝 𝐀𝐬𝐬𝐞𝐭𝐬 | 𝐄𝐱𝐩𝐞𝐫𝐭 𝐌𝐮𝐥𝐭𝐢𝐦𝐨𝐝𝐚𝐥 𝐋𝐋𝐌 𝐃𝐚𝐭𝐚 𝐀𝐧𝐧𝐨𝐭𝐚𝐭𝐨𝐫 ───────────────────────────────── ⋆⋅ ❤︎ ⋅⋆ ───────────────────────────────── If you need an elite, highly adaptive designer to craft premium brand identities and hand-drawn patterns, or an analytical specialist for high-stakes AI training data, I bring meticulous execution to every project. From designing the official exterior livery for a national air carrier to engineering complex training datasets for advanced language models, I turn challenging requirements into pixel-perfect reality, always on time and entirely aligned with your goals. 𝐖𝐡𝐲 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐂𝐡𝐨𝐨𝐬𝐞 𝐌𝐞 ─────── ⋆⋅ ❤︎ ⋅⋆ ─────── • Exceptional Creative Versatility: Expert across diverse mediums, creating everything from custom-crafted apparel graphics and repeat fabric patterns to commercial packaging. • Premium Brand Integrity: Trusted to maintain absolute visual consistency for high-profile clients featured on CNN and Good Morning America. • Multi-Domain AI Expertise: 2+ years of experience analyzing, evaluating, and labeling complex data structures across text, code, and multimodal/image models. • Optional Workflows: My artwork is grounded in traditional design principles, but I hold a certification in generative AI and have experience with tools like Adobe Firefly, LeonardoAi to optimize assets solely when requested. 𝐂𝐨𝐫𝐞 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 & 𝐒𝐤𝐢𝐥𝐥𝐬𝐞𝐭 ─────── ⋆⋅ ❤︎ ⋅⋆ ─────── • Graphic Design & Brand Identity: Corporate brand kits, commercial package design, marketing collateral, pitch decks, and custom garment/apparel graphics. • Educational Materials & Publishing: Custom workbooks, educational manuals, training materials, and interactive student worksheets. • Custom & Product Illustration: Hand-drawn repeat clothing patterns, children's coloring pages, scrapbooking stamps/stencils, and festival posters. • LLM Data Annotation & Evaluation: High-accuracy prompt engineering, response alignment, safety testing, and multi-format data labeling across text, code, and vision models. 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 & 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐏𝐫𝐨𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 ────────── ⋆⋅ ❤︎ ⋅⋆ ────────── • Design & Layout: Adobe Creative Cloud (Illustrator, InDesign, Photoshop). • Vector Execution: Canva Pro expert—highly skilled at importing fully editable, custom vector assets built in Illustrator into collaborative client setups. • AI Evaluation: Advanced LLM evaluation environments and prompt alignment interfaces. 𝐍𝐨𝐭𝐚𝐛𝐥𝐞 𝐂𝐚𝐫𝐞𝐞𝐫 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬 ─────── ⋆⋅ ❤︎ ⋅⋆ ─────── • National Impact: Design selected for the official domestic aircraft livery for FlySafair, a South African national airline carrier. • Global Market Reach: Developed hand-illustrated children's apparel patterns and commercial compliance packaging currently active on the market. • Brand Design Training: Conducted full-day, deep-dive brand alignment course to maintain corporate media standards. 𝐖𝐡𝐚𝐭 𝐌𝐲 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐒𝐚𝐲 •───────•°•𖥸•°•───────• ❝𝘿𝙞𝙣𝙞𝙠𝙖 𝙞𝙨 𝙖𝙣 𝙖𝙗𝙨𝙤𝙡𝙪𝙩𝙚 𝙜𝙤𝙙-𝙨𝙚𝙣𝙙. 𝙏𝙝𝙤𝙧𝙤𝙪𝙜𝙝𝙡𝙮 𝙩𝙚𝙧𝙧𝙞𝙛𝙞𝙘 𝙩𝙤 𝙬𝙤𝙧𝙠 𝙬𝙞𝙩𝙝—𝙨𝙝𝙚 𝙬𝙞𝙡𝙡 𝙖𝙙𝙙 𝙩𝙝𝙖𝙩 𝙚𝙭𝙩𝙧𝙖 𝙨𝙥𝙖𝙧𝙠𝙡𝙚 𝙖𝙣𝙙 𝙘𝙤𝙣𝙛𝙞𝙙𝙚𝙣𝙘𝙚 𝙩𝙝𝙖𝙩 𝙚𝙫𝙚𝙧𝙮 𝙘𝙡𝙞𝙚𝙣𝙩 𝙬𝙖𝙣𝙩𝙨 𝙖𝙣𝙙 𝙣𝙚𝙚𝙙𝙨... 𝙬𝙝𝙚𝙩𝙝𝙚𝙧 𝙞𝙩𝙨 𝙜𝙧𝙖𝙥𝙝𝙞𝙘𝙨 𝙛𝙤𝙧 𝙜𝙖𝙧𝙢𝙚𝙣𝙩𝙨 𝙤𝙧 𝙤𝙩𝙝𝙚𝙧 - 𝙡𝙤𝙤𝙠 𝙣𝙤 𝙛𝙪𝙧𝙩𝙝𝙚𝙧!! 𝘿𝙞𝙣𝙞𝙠𝙖 𝙞𝙨 𝙮𝙤𝙪𝙧 𝙬𝙤𝙢𝙖𝙣!❞ ❝𝘿𝙞𝙣𝙞𝙠𝙖 𝙗𝙧𝙤𝙪𝙜𝙝𝙩 𝙘𝙧𝙚𝙖𝙩𝙞𝙫𝙞𝙩𝙮, 𝙛𝙡𝙚𝙭𝙞𝙗𝙞𝙡𝙞𝙩𝙮, 𝙖𝙣𝙙 𝙖 𝙥𝙤𝙨𝙞𝙩𝙞𝙫𝙚 𝙖𝙩𝙩𝙞𝙩𝙪𝙙𝙚 𝙩𝙤 𝙚𝙫𝙚𝙧𝙮 𝙖𝙨𝙥𝙚𝙘𝙩 𝙤𝙛 𝙩𝙝𝙚 𝙥𝙧𝙤𝙟𝙚𝙘𝙩. 𝙎𝙝𝙚 𝙠𝙚𝙥𝙩 𝙤𝙪𝙧 𝙙𝙚𝙖𝙙𝙡𝙞𝙣𝙚𝙨 𝙞𝙣 𝙢𝙞𝙣𝙙 𝙩𝙝𝙧𝙤𝙪𝙜𝙝𝙤𝙪𝙩 𝙖𝙣𝙙 𝙬𝙖𝙨 𝙚𝙭𝙩𝙧𝙚𝙢𝙚𝙡𝙮 𝙩𝙞𝙢𝙚𝙡𝙮 𝙬𝙞𝙩𝙝 𝙩𝙪𝙧𝙣𝙖𝙧𝙤𝙪𝙣𝙙. 𝙈𝙤𝙨𝙩 𝙞𝙢𝙥𝙤𝙧𝙩𝙖𝙣𝙩𝙡𝙮, 𝙨𝙝𝙚 𝙝𝙖𝙨 𝙚𝙭𝙘𝙚𝙡𝙡𝙚𝙣𝙩 𝙘𝙤𝙢𝙢𝙪𝙣𝙞𝙘𝙖𝙩𝙞𝙤𝙣 𝙨𝙠𝙞𝙡𝙡𝙨...❞ ❝𝙄'𝙫𝙚 𝙗𝙚𝙚𝙣 𝙬𝙤𝙧𝙠𝙞𝙣𝙜 𝙬𝙞𝙩𝙝 𝘿𝙞𝙣𝙞𝙠𝙖 𝙤𝙣 𝙖 𝙫𝙚𝙧𝙮 𝙝𝙖𝙧𝙙 𝙖𝙣𝙙 𝙩𝙞𝙢𝙚-𝙗𝙤𝙪𝙣𝙙𝙚𝙙 𝙙𝙚𝙨𝙞𝙜𝙣 𝙩𝙖𝙨𝙠, 𝙖𝙣𝙙 𝙨𝙝𝙚 𝙬𝙖𝙨 𝙖 𝙜𝙧𝙚𝙖𝙩 𝙘𝙤𝙢𝙢𝙪𝙣𝙞𝙘𝙖𝙩𝙤𝙧 𝙖𝙣𝙙 𝙖 𝙨𝙖𝙢𝙥𝙡𝙚 𝙛𝙤𝙧 𝙘𝙤𝙢𝙢𝙞𝙩𝙢𝙚𝙣𝙩 𝙩𝙤 𝙙𝙚𝙡𝙞𝙫𝙚𝙧 𝙖 𝙝𝙞𝙜𝙝 𝙦𝙪𝙖𝙡𝙞𝙩𝙮 𝙨𝙚𝙧𝙫𝙞𝙘𝙚𝙨...❞ •───────•°•𖥸•°•───────• I am a native English speaker with a 100% Job Success Score, available immediately, and completely open to adjusting to your team's preferred timelines. Let’s connect to discuss how I can bring value to your design or data operations!

I build real-time AI systems that detect threats, track objects, and turn video into actionable insights ready for real-world deployment. If you need a reliable Computer Vision solution (not just a demo), I can design, train, and deploy it end-to-end. 🎯 What I Do I specialize in building production-ready Computer Vision systems that work in real environments not just controlled demos. From surveillance and safety to traffic analytics and automation, I help businesses turn video data into practical, usable intelligence. 🔧 Solutions I Build ✔ Real-Time Object Detection (YOLOv8 / YOLO11) ✔ Multi-Object Tracking (ByteTrack, DeepSORT) ✔ Surveillance & Threat Detection Systems ✔ Fire & Smoke Detection ✔ PPE / Safety Compliance Monitoring ✔ Traffic Monitoring & Speed Estimation ✔ OCR & Document AI ✔ End-to-End AI Systems (Data → Training → Deployment) 🧠 Why Clients Choose Me Most freelancers stop at training a model. I go further — I build complete systems that actually work in production. ✔ Optimized for real-time performance (high FPS, low latency) ✔ Designed for real-world conditions (low light, fog, motion blur) ✔ Strong focus on data quality & annotation (where most projects fail) ✔ Clean, scalable, deployment-ready code 💡 Most Computer Vision models fail outside the lab — I make sure yours doesn’t. 📊 Selected Projects 🔫 Real-Time Weapon Detection & Tracking AI-powered surveillance system for detecting and tracking firearms in live video streams → Helps improve security response time and monitoring 🔥 Real-Time Fire & Smoke Detection (107 FPS) Early hazard detection system designed for fast response in critical environments → Detects fire/smoke in real-time to reduce risk and damage 🦺 Construction Safety Monitoring (PPE Detection) Helmet detection system with live violation alerts → Improves worker safety and compliance on-site 🚗 Vehicle Speed Estimation System Tracking-based system for real-time speed analysis from video → Useful for traffic monitoring and smart city solutions ⚙️ Tech Stack AI / Deep Learning: PyTorch, YOLO (v8, v11), TensorFlow Computer Vision: OpenCV, real-time video processing pipelines Tracking: ByteTrack, DeepSORT Deployment: FastAPI, Flask, Docker, GPU acceleration Language: Python 🎬 What You Can Expect ✔ Demo available before starting ✔ Clean, well-documented code ✔ Fast communication & regular updates ✔ Scalable solutions ready for deployment ✔ Support with real-world challenges (lighting, motion, noise) 💡 How I Work I follow a complete pipeline: Data Collection → Annotation → Training → Optimization → Deployment You don’t just get a model you get a working system ready to use. 📩 Let’s Build Something Real Have an idea or project in mind? 👉 Send me a message I’ll break down the best approach and can even share a quick demo or plan before you commit.

I am a Machine Learning Engineer with four years of experience working across deep learning research, large scale AI systems, and production model deployment. Over the years, I have worked extensively in medical imaging, computer vision, NLP, signal processing, and large language models, building systems that range from experimental research pipelines to deployed real world AI applications. My day to day work primarily involves Python, PyTorch, TensorFlow, Keras, HuggingFace Transformers, sentence transformers, scikit learn, OpenCV, Pandas, and NumPy. I enjoy working deeply on both the research and engineering sides of machine learning, especially problems that require understanding model behavior rather than simply applying existing architectures blindly. A large part of my background is research driven. I have authored multiple peer reviewed publications in indexed journals and IEEE conferences, including publications in Neurocomputing, Healthcare Analytics, Engineering Applications of Artificial Intelligence, Telematics and Informatics Reports, and other Elsevier and IEEE venues. My research has focused heavily on explainable AI, healthcare AI, and advanced deep learning systems. Some of my published work includes CARDxnosis, an explainable knowledge driven framework for ECG diagnosis and clinical report generation, an explainable AI system for trustworthy arrhythmia detection, a CNN RNN Attention hybrid architecture for automatic modulation classification, ensemble deep learning approaches for lung cancer detection from CT scans, and SRGAN based white blood cell image generation and classification pipelines. Alongside published work, I am currently involved in research on brain tumor segmentation, ADHD and ASD classification from brain connectome graphs, epileptic seizure prediction from EEG signals, and interpretable tabular learning using graph neural networks combined with Kolmogorov Arnold Networks. Beyond research, I have substantial hands on experience building and deploying production grade AI systems. One of my major recent projects was LaborBERT v4, a domain adaptive transformer fine tuning system processing hundreds of thousands of records through a large scale training pipeline. The project involved multiple experimental setups including contrastive learning, masked language model pretraining, temporal contrastive learning, cross attention based fusion, multi task training, and Matryoshka Representation Learning. I have also built hybrid embeddings plus LLM systems for taxonomy mapping using OpenAI embeddings alongside locally hosted LLaMA and Mistral models through Ollama. In addition, I have worked on deployed clinical AI systems and a portable on device diagnostic AI solution with embedded deep learning models for point of care inference, which gave me valuable experience in optimization, deployment constraints, inference design, and production reliability. My broader project portfolio includes vehicle detection using Mask R CNN, human activity recognition on the Kinetics 700 dataset, facial keypoint detection with MultiRes UNet, semantic segmentation pipeline redesign, Stable Diffusion based image editing workflows, toxic comment classification, RASA based conversational AI systems, and large scale scraping and automation pipelines using Playwright and Selenium. I have also worked with Flask and Django based deployment pipelines and cloud hosted ML systems. From an engineering perspective, I care strongly about clean and maintainable systems. I follow disciplined workflows involving modular code design, Git based version control, reproducible experimentation, structured evaluation, bootstrap validated metrics, and detailed documentation. I am also comfortable preparing scientific reports, research papers, and journal submissions using both LaTeX and Word. What ties all of this together is that I genuinely enjoy solving difficult technical problems, especially the kind that require balancing research depth with practical engineering constraints. I am most motivated by projects where thoughtful experimentation, careful system design, and real world usability matter equally.

I have 5+ years of experience in Data Annotation, Data labeling and segmentation. Your large-scale dataset will be processed swiftly and effectively by my team of skilled annotators. essential Projects: -Marking 21 essential locations on human hand joints; -Camera synchronization project (Key points). Marking timestamps on video based on sensor data on visuals is an exercise application that synchronizes sensor data with video. Marking important spots on the face, arms, and legs is known as pose estimation. Ecart (Bounding box, Polygon): - Drawing polygons around hands and products. Drawing polygons around plastic bottles and cans is one way to recycle plastic bottles. Additionally, categorize cans and bottles according to their forms. Draw polygons around the stems and leaves of grape trees. Video Annotation for an Autonomous Checkout System:Draw a bounding box around items that have been captured and added to a video clip. Additionally, note how many products were taken and included in the video. P&G (Designs): -Mark 🔹 AI Data Annotation & Labeling ✔️ Image & Video: • Bounding Boxes · Polygon · Polyline · Cuboid · Ellipse · Brush • Semantic Segmentation · Instance Segmentation · Image Masking • Keypoint Annotation · Object Detection · Object Counting • Lane & Line Annotation · Satellite Image Annotation • Image Tagging & Classification ✔️Audio & Text: • Audio Segmentation · Timestamping · Speaker Labeling · Audio Cleaning • Named Entity Recognition (NER) · Text Classification • Sentiment Analysis · Search Relevance · Data & Content Moderation ✔️ Bat Call Analysis & Annotation via Spectrograms ✔️ LiDAR Annotation · 3D Cuboid Annotation · Point Cloud Labeling ✔️ COCO · YOLO · Pascal VOC · CSV