{"product_id":"kit-pi-5-tensorflow-object-counter","title":"Pi 5 TensorFlow Object Counter Kit with Raspberry Pi 5 + Camera","description":"\u003ch1\u003eBuild a Real-Time Object Counter with Raspberry Pi 5 AI HAT+ and TensorFlow\u003c\/h1\u003e\n\n\u003cp class=\"value-summary\"\u003eEvery part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.\u003c\/p\u003e\n\n\u003cdiv class=\"specs-strip\"\u003e\n  \u003cspan\u003e\u003cstrong\u003eDifficulty:\u003c\/strong\u003e Advanced\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eBuild Time:\u003c\/strong\u003e 5-6 hours\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eAge:\u003c\/strong\u003e 18-21\u003c\/span\u003e\n  \u003cspan\u003e\u003cstrong\u003eSkill:\u003c\/strong\u003e Edge AI Deployment\u003c\/span\u003e\n\u003c\/div\u003e\n\n\u003cp\u003eImagine a camera feed that automatically counts people entering a room or products passing a conveyor. This kit turns a Raspberry Pi 5 and AI HAT+ into a smart object counter that does exactly that—train a TensorFlow model and trigger an LED each time something crosses your line.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Build\u003c\/h2\u003e\n\u003cp\u003eYou'll assemble a complete edge AI system that counts objects crossing a line. The Pi Camera Module 3 feeds live video; the AI HAT+ runs a TensorFlow Lite model to detect objects, and an LED flashes for each crossing. Extend it to count vehicles, people, or inventory in real time.\u003c\/p\u003e\n\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cul\u003e\n  \u003cli\u003eDeploy a quantized TensorFlow model on the Raspberry Pi AI HAT+ coprocessor\u003c\/li\u003e\n  \u003cli\u003eConfigure and optimize the Pi Camera Module 3 for high‑speed inference\u003c\/li\u003e\n  \u003cli\u003eWrite Python code that draws lines and tracks object centroids in the video stream\u003c\/li\u003e\n  \u003cli\u003eExtend the base project to handle custom object classes using transfer learning\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eKit Contents\u003c\/h2\u003e\n\u003ctable\u003e\n  \u003cthead\u003e\u003ctr\u003e\n\u003cth\u003eComponent\u003c\/th\u003e\n\u003cth\u003eQuantity\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n  \u003ctbody\u003e\n    \u003ctr\u003e\n\u003ctd\u003eRaspberry Pi 5 4GB\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eRaspberry Pi AI HAT+\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003ePi Camera Module 3\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e5mm LED\u003c\/td\u003e\n\u003ctd\u003e3\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003e220Ω Resistors\u003c\/td\u003e\n\u003ctd\u003e5\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eM-F Wires\u003c\/td\u003e\n\u003ctd\u003e10\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eMicroSD Card 32GB\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eUSB-C PSU\u003c\/td\u003e\n\u003ctd\u003e1\u003c\/td\u003e\n\u003c\/tr\u003e\n  \u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eWhy Buy This Kit Instead of Sourcing Parts Separately\u003c\/h2\u003e\n\u003ctable\u003e\n  \u003cthead\u003e\u003ctr\u003e\n\u003cth\u003eFactor\u003c\/th\u003e\n\u003cth\u003eSourcing Separately\u003c\/th\u003e\n\u003cth\u003eCompoden Kit\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n  \u003ctbody\u003e\n    \u003ctr\u003e\n\u003ctd\u003eCompatibility checks\u003c\/td\u003e\n\u003ctd\u003eYou verify every part\u003c\/td\u003e\n\u003ctd\u003ePre-tested as a system\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eBuild support\u003c\/td\u003e\n\u003ctd\u003eForums and scattered tutorials\u003c\/td\u003e\n\u003ctd\u003eAI companion trained on this exact project\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eTime to first working build\u003c\/td\u003e\n\u003ctd\u003eDays of debugging\u003c\/td\u003e\n\u003ctd\u003eHours, with step-by-step guidance\u003c\/td\u003e\n\u003c\/tr\u003e\n    \u003ctr\u003e\n\u003ctd\u003eShipping coordination\u003c\/td\u003e\n\u003ctd\u003eMultiple sellers, multiple delays\u003c\/td\u003e\n\u003ctd\u003eOne shipment from Bengaluru in 3-5 days\u003c\/td\u003e\n\u003c\/tr\u003e\n  \u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eWho This Kit Is For\u003c\/h2\u003e\n\u003cp\u003eDesigned for advanced makers and engineering students (CBSE Class 11‑12 with AI specialization, B.Tech ECE\/EEE\/CSE, and participants of Smart India Hackathon) who want to move beyond basic robotics and build a real‑world computer vision system. It’s also well‑suited for ATL Tinkering Lab coaches and NIT\/IIT\/VIT\/BITS students undertaking capstone projects that require edge AI.\u003c\/p\u003e\n\n\u003ch2\u003eBuilt and Backed by Compoden\u003c\/h2\u003e\n\u003cp\u003eEvery Compoden kit ships with an AI build companion trained on this exact project — accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.\u003c\/p\u003e\n\n\u003cdetails\u003e\u003csummary\u003eDo I need prior TensorFlow experience?\u003c\/summary\u003e\u003cp\u003eNo—the companion provides a step‑by‑step notebook for model conversion. If you’ve used Raspberry Pi before, you can follow along without deep ML knowledge.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eCan I use this kit for my college project submission?\u003c\/summary\u003e\u003cp\u003eYes, it fits B.Tech projects, Smart India Hackathon, and AI mini‑projects. Document your methodology easily and extend the code for your report.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eDoes the AI HAT+ support other models?\u003c\/summary\u003e\u003cp\u003eYes, test with SSD MobileNet, EfficientDet, or custom tflite models. The companion shows the minor code changes needed to swap detection models.\u003c\/p\u003e\u003c\/details\u003e\n\u003cdetails\u003e\u003csummary\u003eWhat if the object detection is too slow?\u003c\/summary\u003e\u003cp\u003ePi 5 with AI HAT+ handles 30+ fps for MobileNet‑SSD. The companion includes tuning tips like reducing resolution or switching model variants.\u003c\/p\u003e\u003c\/details\u003e\n\n\u003cdiv class=\"kit-description\"\u003e\n  \u003cp\u003ePi 5 AI HAT+ runs TensorFlow object detection model counting people or objects crossing a line in camera feed.\u003c\/p\u003e\n  \u003ch4\u003eWhat's in this kit\u003c\/h4\u003e\n  \u003cul\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/raspberry-pi-5-model-b-4gb-technical-specs-projects\"\u003eRaspberry Pi 5 4GB\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/industrial-ph-sensor-module-for-arduino-esp32-raspberry-pi\"\u003eRaspberry Pi AI HAT+\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/4-channel-relay-board-for-esp32-30-pin-5v-control\"\u003ePi Camera Module 3\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/inductive-proximity-sensor-5mm-npn-no-ceyone-compoden\"\u003e5mm LED\u003c\/a\u003e x3\u003c\/li\u003e\n    \u003cli\u003e\n\u003ca href=\"\/products\/resistor-variety-pack-100-pcs-10-values-14w-carbon-film\"\u003e220Ω Resistors\u003c\/a\u003e x5\u003c\/li\u003e\n    \u003cli\u003eM-F Wires x10\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/microsd-card-reader-spi-module-for-arduino\"\u003eMicroSD Card 32GB\u003c\/a\u003e\u003c\/li\u003e\n    \u003cli\u003e\u003ca href=\"\/products\/raspberry-pi-4-official-power-supply-5v-3a-usb-c-compoden\"\u003eUSB-C PSU\u003c\/a\u003e\u003c\/li\u003e\n  \u003c\/ul\u003e\n\u003c\/div\u003e\n\n\u003cscript type=\"application\/ld+json\"\u003e\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What is included in the Pi 5 TensorFlow Object Counter Kit with Raspberry Pi 5 + Camera?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The Pi 5 TensorFlow Object Counter Kit with Raspberry Pi 5 + Camera includes all components needed: Raspberry Pi 5 4GB, Raspberry Pi AI HAT+, Pi Camera Module 3, 5mm LED, 220Ω Resistors and more. Everything is pre-tested for compatibility and shipped from Bengaluru, India.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What skill level is required for the Pi 5 TensorFlow Object Counter Kit with Raspberry Pi 5 + Camera?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"This kit is designed for Advanced level makers, suitable for ages 18-21. Pi 5 AI HAT+ runs TensorFlow object detection model counting people or objects crossing a line in camera feed. Estimated build time is 5-6 hrs.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can I buy the Pi 5 TensorFlow Object Counter Kit with Raspberry Pi 5 + Camera online in India?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Yes, the Pi 5 TensorFlow Object Counter Kit with Raspberry Pi 5 + Camera is available online at Compoden (compoden.in), India's AI-powered electronics and robotics store. 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