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Before we get into the task, we just wanted to rewind a few days.

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We're fresh off 4 incredible events at ETHDenver.

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The Perle Labs team was on the ground at ETHDenver last week. Here's where we showed up:

• Multichain Day: Our Chief Commercial Officer, Arthur Ding, spoke on "AI Infra Onchain: Compute, Data, and the Coordination Layer" alongside 0G Labs, Kite AI, and Pi Squared.
• RoboCon: Ahmed Rashad, our Founder and CEO, spoke on coordinating human intelligence for AI, alongside Sentient AGI and PrismaX.
• Proof of AI — Builder & Influencer Night: The team joined discussions on autonomous agents, open-source innovation, and scaling human-in-the-loop AI. Packed room, strong turnout, and plenty of swag.
• Open AGI Summit by Sentient AGI: Ahmed delivered a keynote — "Trust is the New Compute: Why Sovereign Data Wins the AI Race"  and the team ran a booth all day for meetups and community engagement. One of the most talked-about AI rooms of the week.

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1M Annotators. 1B+ Points. BSCN broke the news: Perle Labs has officially crossed 1 million annotators and over 1 billion points distributed across the platform. The data layer for AI is scaling — powered by real people doing real work.

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‍Task 2.0:

Object detection models power everything from autonomous systems to accessibility tools. But before a model can recognize a pet's face, it needs to learn where to look, and that requires precise human annotation.

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Drawing a bounding box seems simple, but consistency and accuracy are what make the difference between a reliable model and a guessing one. Your annotations set the standard.

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The Pet Bounding Box Quest is now live on Perle Labs! Visit app.perle.xyz to start earning points.

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What This Task Is

The Pet Bounding Box Quest is a set of 20 image annotation tasks. Each prompt presents a pet image from the Oxford-IIIT Pets Dataset. Your job is to draw a tight bounding box around the pet's head, not the full body.

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These annotations train object detection models, so precision and consistency matter. High-quality bounding boxes create high-quality AI.

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What You'll Do

Step 1: Look at the pet image carefully.

Step 2: Identify the pet's head within the image.

Step 3: Draw a tight bounding box that captures the visible head — not the body, not the background.

Step 4: Submit your annotation and move to the next task.

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Focus on consistency. The box should be as tight as possible while fully containing the head.

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Why It Matters

By contributing to this task, you are:

• Teaching AI to accurately locate and identify objects in images
• Building enterprise-grade datasets for computer vision and object detection systems
• Improving how AI processes visual information for real-world applications
• Contributing to the sovereign data layer that enterprises and institutions require

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This is precision work that AI cannot learn alone, the human layer that makes vision systems reliable.

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Task Details

• Points per question: 100
• Number of tasks: 20
• Total points available: 2,000
• Project eligibility: 1,000 points

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Visit the app today to start earning points!

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Ready to Get Started?

The Pet Bounding Box Quest is now live on your Perle Labs dashboard: http://app.perle.xyz

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Each annotation you submit helps build auditable AI infrastructure for vision systems where accuracy isn't optional; not black-box pipelines, but human-verified data with a clear chain of custody.

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Stay Connected

Join the Perle Labs community on X, Discord, and Telegram to stay connected and catch the next drop of insights from across the ecosystem.

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Human-verified. Auditable. Sovereign. Start contributing.

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Author: Drew Mailen