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Hire Image Taggers from Real People

Image tagging service from $0.05 per image. Real people open each image, apply your taxonomy, and submit their labels with a screenshot — you review every submission before paying.

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How It Works

How the Image Tagging Service Works

Define your taxonomy and image URLs. Real people apply your tags — you review every submission before paying.

01

Define Your Tag Taxonomy

List every allowed tag with a clear definition. Add examples when categories are easy to confuse.

02

Provide a Direct Image URL

One image per task. Use a public direct URL — private or login-gated images cannot be tagged.

03

Workers Apply Your Tags

Workers open the image, apply your taxonomy, and flag ambiguous items instead of guessing.

04

You Approve Tags and Proof

Workers submit tags plus a screenshot of the image. Reject wrong labels or empty submissions.

Image Tagging Use Cases

What Are You Tagging?

Product catalogs, ML training data, content safety, alt-text, scene classification, property photos — each dataset type calls for a different taxonomy and task brief.

Product Catalog Labeling

Problem
E-commerce catalogs with thousands of product images need structured attribute tags — category, color, material, condition — before items can be filtered, recommended, or fed into a search system. Manual tagging in-house does not scale when new inventory arrives daily.
With RapidWorkers
Workers open each product image and fill in your structured attribute fields from a fixed list. One image per task, one submission per approval. You build a clean, consistent product dataset at $0.05–$0.15 per image with no annotation platform contract required.

ML Training Data Collection

Problem
Supervised machine learning models require large volumes of human-labeled images to train. Labeling internally is slow and expensive; enterprise annotation platforms like Scale AI or Appen require contracts and minimum project sizes that exclude smaller teams.
With RapidWorkers
Workers classify and tag images from your dataset using your taxonomy. Pay per image approved — no contract, no minimum batch size. Post 50 images or 50,000 — the pricing per item is the same. Workers tag from your defined categories, not general intuition.

Content Safety Classification

Problem
Platforms that allow image uploads need each image categorized before it appears publicly — safe for all audiences, age-restricted, or policy-violating. Automated classifiers have high error rates on contextual and borderline images that require human judgment.
With RapidWorkers
Workers view each image and assign it to your safety categories (safe, age-restricted, remove, review required). Workers flag images they find ambiguous rather than guessing. You see the classification and the worker's note before approving payment.

Alt-Text and Caption Generation

Problem
Image accessibility compliance requires descriptive alt-text for every image on a website or app. Writing accurate alt-text at scale for a large media library is a task that resists automation — AI-generated captions are often generic or factually wrong about specific products and settings.
With RapidWorkers
Workers write a one-sentence description of each image based on a format you specify. You set the word count, the required elements (main subject, color, setting, action), and what to omit. Review each caption before paying — reject captions that describe the wrong thing or ignore your format.

Scene and Environment Tagging

Problem
Datasets for computer vision models that detect environments — indoor vs. outdoor, urban vs. rural, daytime vs. nighttime, specific location types — require scene-level labels that automated tools handle poorly without training data that already has those labels.
With RapidWorkers
Workers tag each image with your scene categories from a structured list. Define edge cases explicitly in your brief — "parking lot counts as outdoor urban, not indoor" — and workers apply your rule consistently. Build scene-labeled datasets for training, filtering, or content organization.

Real Estate and Property Tagging

Problem
Property listing platforms with large image libraries need each photo categorized by room type, property feature, or listing quality before images can be sorted into the correct gallery sections or scored for listing completeness.
With RapidWorkers
Workers classify each property image by room type (kitchen, bathroom, bedroom, living room, exterior, garden) and flag images that do not fit a category. Structured attribute fields can extend to image quality (well-lit, dark, blurry) if you need to filter low-quality photos from listings automatically.
Your Guarantee: Taxonomy-Driven Labels

Workers Tag from Your List, Not Their Own Judgment

Workers select from the tag set you define — not from general knowledge or personal interpretation. Every submission includes a screenshot confirming the correct image was tagged.

  • Your taxonomy, applied per image

    Workers use only the tags you define in your brief. If a category is not in your list, workers flag the image as unclear rather than inventing a label. Submissions that apply tags outside your taxonomy are rejected before payment

  • Screenshot confirms the correct image

    Every submission includes a screenshot of the image being tagged alongside the tag fields. You verify the worker opened and reviewed the correct image — not a placeholder or cached version — before releasing payment

  • Reject inconsistent labels without paying

    If a worker misclassifies an image or leaves required fields blank, reject the submission at no cost. For high-stakes datasets, require double tagging — two workers tag the same image and you compare their labels before approving either

Pricing

Image Tagging Pricing

Cost depends on the number of tag fields per image and whether workers need to write text or just select from a list. A single-label classification from a short list starts at $0.05 — multi-attribute extraction with a written caption costs more.

Minimum Reward

$0.05

per completed task

Example Task Rewards

TaskExample Reward
Single-label classification (one category from a list of ≤10 options)$0.05–$0.08
Multi-label tagging (select all applicable tags from a taxonomy list)$0.08–$0.12
Attribute extraction (fill in 3–5 structured fields per product image)$0.10–$0.15
Image caption (write a 1-sentence description of the image content)$0.12–$0.20

*These are examples, not fixed pricing tiers.

Calculate Your Cost

Estimate cost by tag field count per image. One image per task submission keeps your dataset trackable and your label quality consistent.

Example: 5,000 tasks × $0.08 reward = $400 estimated total

Image Tagging Task

Calculator
Tasks5,000
Reward Per Task$0.08
Estimated Total5,000 × $0.08
$400
Create Task

Require workers to submit a screenshot of the image alongside their completed tag fields — this confirms they viewed the correct image before tagging it.

Example Task

What Does an Image Tagging Task Look Like?

rapidworkers.io/dashboard/job/image-tagging-example

Dashboard / Image Tagging Task

Tag Product Image — 4 Attribute Fields (Category, Color, Pattern, Gender)

Pay Rate

$0.10

Time to Complete

2 min

Availability

22 / 60

Requirement

None

Job Description

Open the image URL. Fill in 4 attribute fields from the provided lists. Use "Other" if unclear. Screenshot the image with your answers visible. Submit.

Reference

Screenshot showing the product image alongside the four completed tag fields

Submission Instructions

Category (T-shirt / Hoodie / Jacket / Pants / Shorts / Dress / Skirt / Other)

Primary color (Black / White / Gray / Navy / Red / Green / Blue / Yellow / Brown / Other)

Pattern (Solid / Striped / Graphic print / Plaid / Other)

Gender presentation (Menswear / Womenswear / Unisex)

Screenshot of image with completed fields visible

Complete Job

This is how workers see your task on RapidWorkers

Job Description

Open the product image at the URL provided (a clothing item on a white background). Fill in the following attribute fields based on what you see in the image: (1) Category — select one: T-shirt, Hoodie, Jacket, Pants, Shorts, Dress, Skirt, Other; (2) Primary color — select the most dominant color from the list: Black, White, Gray, Navy, Red, Green, Blue, Yellow, Brown, Other; (3) Pattern — select one: Solid, Striped, Graphic print, Plaid, Other; (4) Gender presentation — select one: Menswear, Womenswear, Unisex.

After filling in all four fields, take a screenshot showing the image visible alongside your completed answers. Submit the four tag fields and the screenshot. Do not guess — if you cannot determine an attribute clearly from the image alone, select "Other" for that field.

Submission Instructions

Step 1: Open the image URL and view the product at full size.

Step 2: Fill in all four attribute fields based on what you see.

Step 3: If any attribute is unclear from the image alone, select "Other."

Step 4: Screenshot the image with your completed fields visible. Submit.

Create Your Task
Got Questions?

Frequently Asked Questions

Single-label classification (assign one category from a fixed list), multi-label tagging (select all applicable tags from your taxonomy), attribute extraction (color, material, condition, size from product images), and short image descriptions (write one sentence describing what is in the image). Bounding box drawing and pixel-level segmentation are not supported — those require specialist annotation tools that workers do not use through RapidWorkers.

Yes. Define your attribute list in the brief (category, color, condition, subcategory, etc.) and workers fill in each attribute for the image you provide. Require workers to answer every attribute field — submissions with missing fields are rejected before payment.

Write your taxonomy explicitly in the brief with a definition for each tag and at least one example image per category. If workers can interpret a tag differently, they will. For categories with overlap, add a decision rule (e.g., "if both X and Y apply, use X"). Review the first 20 submissions carefully to catch systematic misclassifications before the rest of the batch runs.

Yes. Specify the format (one sentence, under 15 words, describe the main subject and setting) and workers write a short caption for each image. This works well for alt-text generation, training caption models, and accessibility audits. Set a word count range — open-ended "describe this image" produces descriptions too variable to be useful as training data.

You provide a direct URL to each image in the task brief. Workers open the URL, view the image, and apply your tags. Images hosted behind authentication or login walls cannot be accessed. Use a public CDN or generate publicly accessible links before posting the task.

Workers may decline tasks that involve graphic content. Specify in your brief if the images may contain sensitive content so workers who are not comfortable with those categories can skip without starting. For adult content classification, you must describe what workers will see in the brief before they accept the task.

Yes, within the constraint of one image per task submission. For large datasets (500+ images), post the job as a repeating task with a high worker allocation. Workers take individual images from the queue, tag them, and submit. You build the labeled dataset progressively as submissions are approved. Batching many images into one task produces lower-quality results than one image per task.

Ready to Label Your Image Dataset?

Define your taxonomy, post your image URLs, and let real people apply your labels — you review every tagged submission before releasing payment.

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