Accessory Image Labeling Project
Budget: €8 – €30 EUR
I have a sizable collection of fashion-related images specifically accessories that must be tagged with the correct category in line with my existing taxonomy. Your work directly feeds our machine learning pipelines, keeps on-site search snappy, and ultimately shapes the user experience, so accuracy is critical.
You will log into the annotation platform of your choice (let me know which one you prefer Labelbox, CVAT, SuperAnnotate, or anything comparable) and review each image, choosing the most relevant category according to the taxonomy I provide. If an image is unclear or falls outside our guidelines, simply flag it so I can review or remove it. I am targeting a minimum 95 % audit accuracy, and I need each assigned batch turned around within 24–48 hours.
To make sure we stay on track:
• I will share the taxonomy document, sample labeled images, and platform credentials once we start.
• You let me know which tool you will use and how you plan to reach the 95 % benchmark, including any QC workflow you follow.
• Whenever you hit an edge case or feel that an accessory image could belong in more than one category, flag it with a brief note so we can refine the rules together.
If you have solid visual pattern recognition skills, experience labeling images for machine-learning training, and you communicate clearly, we’ll be a great fit. Tell me your preferred platform and any automation or validation tricks you use, and we can get the first batch moving right away.
You will log into the annotation platform of your choice (let me know which one you prefer Labelbox, CVAT, SuperAnnotate, or anything comparable) and review each image, choosing the most relevant category according to the taxonomy I provide. If an image is unclear or falls outside our guidelines, simply flag it so I can review or remove it. I am targeting a minimum 95 % audit accuracy, and I need each assigned batch turned around within 24–48 hours.
To make sure we stay on track:
• I will share the taxonomy document, sample labeled images, and platform credentials once we start.
• You let me know which tool you will use and how you plan to reach the 95 % benchmark, including any QC workflow you follow.
• Whenever you hit an edge case or feel that an accessory image could belong in more than one category, flag it with a brief note so we can refine the rules together.
If you have solid visual pattern recognition skills, experience labeling images for machine-learning training, and you communicate clearly, we’ll be a great fit. Tell me your preferred platform and any automation or validation tricks you use, and we can get the first batch moving right away.