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Media and Gaming. Game server management service running on Google Kubernetes Engine. Open source render manager for visual effects and animation. Convert video files and package them for optimized delivery. App migration to the cloud for low-cost refresh cycles. Data import service for scheduling and moving data into BigQuery. Reference templates for Deployment Manager and Terraform.
Components for migrating VMs and physical servers to Compute Engine. Storage server for moving large volumes of data to Google Cloud. Data transfers from online and on-premises sources to Cloud Storage. Migrate and run your VMware workloads natively on Google Cloud. Security policies and defense against web and DDoS attacks.
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Connectivity options for VPN, peering, and enterprise needs. Connectivity management to help simplify and scale networks. Network monitoring, verification, and optimization platform. Cloud network options based on performance, availability, and cost. VPC flow logs for network monitoring, forensics, and security. Google Cloud audit, platform, and application logs management. Infrastructure and application health with rich metrics.
Application error identification and analysis. GKE app development and troubleshooting. Tracing system collecting latency data from applications. CPU and heap profiler for analyzing application performance. Real-time application state inspection and in-production debugging. Tools for easily optimizing performance, security, and cost. Permissions management system for Google Cloud resources. Compliance and security controls for sensitive workloads. Manage encryption keys on Google Cloud.
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Deploy low-latency, high-accuracy models optimized for edge devices. Integrate with ML Kit. Compare photos to images in your product catalog and return a ranked list of similar items. Use OCR and automatically identify language. Detect faces and facial attributes. Face recognition not supported. Automatically identify well-known landmarks and product logos. Detect general attributes and appropriate crop hints.
Find news events, logos, and similar images on the web. Detect explicit content adult, violent, etc. Identify celebrity faces in images limited access, see documentation. Train models to classify images via labels you choose. Our team can help annotate your images, videos, and text.
Whatever your Vision AI needs, we have pricing that works with you. Follow these links to learn more about pricing and trials for our Vision AI products.
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Generate instant insights from data at any scale with a serverless, fully managed analytics platform that significantly simplifies analytics. Introduction The AIY Vision Kit from Google lets you build your own intelligent camera that can see and recognize objects using machine learning.
Everything you need is provided in the kit, including the Raspberry Pi. Get the kit. Time required to build: 1. Check your kit version These instructions are for Vision Kit 1. Gather additional items. Choose the one that works best for you, based on what you have available: Option 1: Use the AIY Projects app Choose this option if you have access to an Android smartphone and a separate computer. Below are two different options. Take note that the Electrical Hardware bag is underneath the Mechanical Hardware bag.
Get the Latest System Image. Fold the internal frame. Open connector latch Start by finding your Raspberry Pi Camera v2 board and open the cable connector latch by pulling gently back on the black raised latch. Insert long flex into latch Grab your long flex cable.
Close connector latch Close the cable connector latch by pressing down. Orient the cardboard Take the internal frame cardboard and orient it as shown in the photo. Remove adhesive liner In the middle of the cardboard is a rectangular cutout labeled A.
Fold up flap A Fold the adhesive flap toward you, then against the frame. Flip it over Flip the frame over as shown in the photo. Insert piezo buzzer Find your piezo buzzer and stick it to the adhesive flap that you just folded. Add the camera Grab the camera you assembled earlier. The lens should be facing towards you. Flip to the other side Inspect the cardboard from the other side so that it matches the picture.
Fold down the top flap Fold the top flap over the camera board. Fold the left and right flaps Holding the top flap down, fold the flaps on the left and the right of the board toward you to hold the camera in place.
There are two small cardboard notches on each side that will loosely hold the flaps in place. Fold the bottom flap While holding those flaps in, fold the bottom flap of the inner frame upwards. The bottom of the assembly should look like a shelf. Thread the buzzer wire Thread the piezo buzzer wire through the circular opening next to the long flex.
Fold the long flex up Fold the long flex upwards and crease it by pressing gently. Fold the long flex to the left Then fold the long flex to the left at a degree angle. Thread the long flex There are three slits on the left flap of the frame.
Keep threading More threading This keeps the long flex in place. Set your internal frame aside for now. Connect the boards. Vision Bonnet The blue board is the Vision Bonnet, an accessory for the Raspberry Pi that lets you run machine learning programs to identify images from the camera.
It contains a special chip designed to run machine learning programs. Standoffs x2 Short flex cable The short flex is a flexible circuit board. Button harness. Orient your Raspberry Pi Orient your Raspberry Pi so that the pin header A header is a fancy electronics term for set of wire connectors.
Open the top cable connector Open the flex connector latch by pulling gently back on the black raised latch. Insert the short flex Find your short flex cable. Close the cable connector latch Close the cable connector latch by pressing down. Orient your Vision Bonnet Find your Vision Bonnet and orient it so the pin header connector is on the left and the white connector is on the bottom.
Open the cable connector latch Look at the white cable connector from the side. Insert the short flex Insert the short flex into the Vision Bonnet the other side should be connected to the Raspberry Pi. Close the cable connector latch Close the cable connector latch on the Vision Bonnet by flipping the black latch back down parallel to the white base. Insert standoffs Insert the standoffs into the Raspberry Pi board in the holes opposite the pin header.
Push the short flex inward Push the short flex into the space between the two boards. Connect the boards and check connections Firmly push the boards together to snap the standoffs into place.
Add the boards to the frame. Connect the boards and frame Find your internal frame and the long flex that you threaded through the cardboard slits. Slide the boards into the frame Now that the boards are connected, slide the boards into the frame, with the Vision Bonnet the blue one on top.
The boards slide into a slot that looks like a mouth :o Lightly crease the twisted part of the long flex so that it lays closer against the cardboard. Check frame and cables Double-check that your internal frame assembly looks like the one pictured.
The lower tip of each white standoff should be on the outside of the internal frame walls. Plug in the button harness Find your button harness and plug it into the top of the Vision Bonnet board. Build the box. Fold A Fold each of the flaps labeled A upwards.
Fold B Now fold the two flaps labeled B toward you. Peel the adhesive liner off the flaps labeled A Fold D While applying pressure to the outer sides of the box, fold flap D over and onto both of the A flaps. Two sets of arrows should now line up.
Insert tripod nut Take the tripod nut and slide it, wider side face down, into the slot labeled tripod nut. Fold E Fold the flaps labeled E inward. Fold F Fold the flap labeled F inward, keeping the E flaps inside the box. Remove adhesive on E Remove the adhesive on the right-hand E flap.
Fold G Fold over the right hand flap labeled G, creasing it very close to the edge of panel B. The two arrows should now face each other.
Fold and secure the other side Repeat the previous two steps on the other side. Ensure that the arrows are aligned. Fold bottom flap Fold down the bottom retaining flap, and bend it in the center so the tip points toward you.
Your camera box is now built! But don't close it yet, because you'll now put the rest inside. Bring it together. Check the boards and wires Ensure that your Raspberry Pi and Vision Bonnet board are still sitting snugly in the internal frame and that your long flex cable is secure.
Install the LED. Install the LED bezel Flip your box to the front side. You will see three holes. Push the LED bezel into the top-left hole, above the camera aperture. Install privacy LED Turn the box around. Check other side Make sure the privacy LED is peeking out on the other side. Install the Hardware. Thread wires through nut Gather the piezo buzzer, privacy LED, and button harness cables. The wider side of the button nut should be facing upwards, toward the top of the box.
Thread the cables through the box Take those same cables and insert them through the hole on the top of the box. Plug wires into push button Get your push button. Insert push button Insert the push button into the hole. Secure button nut From the inside of the box, screw the button nut to secure the push button.
Make sure the wider, flanged side of the nut is facing upwards. Check your completed box The completed assembly should look like the image. Close the box Close the box and secure it with the tab. Feedback How did assembling the Vision Kit Hardware go? Very Bad. Very Good. Turn it on. When you decide to put away your kit, follow the steps to safely shut it down. Use the Joy Detector. Not working? Take a photo At any point while Joy Detector is running, you can snap a photo by pressing the button.
Select an option. Option 1: AIY Projects app. Follow app instructions Open the app and follow the onscreen instructions to pair with your Vision Kit. Make sure your Vision Kit is connected to a power supply. If you run into errors, quit the app and try again. Optional: Connect a monitor A monitor is not required to run these demos, but if you have one available, it can be useful so that you can see what your Vision Kit is seeing.
Open the Secure Shell Extension Once the extension is installed open it. Connect to the Raspberry Pi In the top field, type pi Give the extension permission Click Allow. You will only need to do this once when you add the extension into Chrome. Continue connecting At the prompt, type yes and press enter to confirm that the displayed host key The SSH extension is designed to be secure, and because of this goal, it needs to identify that the computer you're trying to connect to is actually the computer you expect.
Note Your IP address might be different than the one shown in the example. Feedback How did connecting to your Vision Kit go? Option 2: With monitor, mouse, and keyboard. Unplug your kit Before plugging in your peripherals, unplug your kit from power. Connect peripherals Plug your monitor into the HDMI port and your keyboard and mouse into the Data port on your Vision Kit using one of the adapters described in Meet your kit.
Open the terminal Open the terminal A terminal is a text window where you can issue commands to your Raspberry Pi. View an image on your Pi. Stop the Joy Detector. See which demos are available. Try image classification in the live camera.
Point the camera at stuff Point your Vision Kit at a few objects, such as some office supplies or fruit. Stop the image classification camera demo The image classification camera demo will run indefinitely until you interrupt it. Try face detection in the live camera. To start the face detection demo, type the following command and press enter:.
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