Dataannotering Jobs

PROJECT: Padel Sports Analytics — Manual Video/Image Labeling We need an experienced data annotator to label padel (sport) match footage using Label Studio. This is a structured, well-documented job with clear instructions, example outputs, and quality bars for each task type. You will receive a complete labeling package (~6.3 GB) containing: - 5 independent Label Studio projects - Pre-configured labeling interfaces (XML configs) - All images, video clips, and pre-labels where applicable - Step-by-step guides per project - Example correct outputs for every project ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SCOPE — EXACT VOLUME ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Project 1 — Shot-type classification • 3,038 short slow-motion swing clips (venue 1 only, 4 gam...

I have many Sports match clips of 10 seconds length. Within that brief window there are 15 separate actions I need clearly marked: exact in timecodes for each event plus a short textual label. Some of the moments involve goals, fouls, pass and a few other on-ball actions; I will supply a reference sheet that names all 15 so you can concentrate on frame-accurate tagging rather than guesswork. We have our own annotation platform. Fast annotators are required. Annotate accurate events of 10second video within 20 seconds.

I have many Sports match clips of 10 seconds length. Within that brief window there are 15 separate actions I need clearly marked: exact in timecodes for each event plus a short textual label. Some of the moments involve goals, fouls, pass and a few other on-ball actions; I will supply a reference sheet that names all 15 so you can concentrate on frame-accurate tagging rather than guesswork. We have our own annotation platform. Fast annotators are required. Annotate accurate events of 10second video within 20 seconds.

Please note the clips contains explicit/nsfw content. If you are not comfortable, DO NOT apply. Each clip is $0.06. I have a batch of very short clips—each between 10 and 20 seconds—that I need properly annotated so they can slot straight into my training dataset. We have an automated rating system for the quality. (1-100) so the final payment will be 0.06 * number of clips * quality score. You will use our own system to do the annotation. All the tags already exist in my taxonomy; your job is to open each clip, pick the correct tag from that list, note the primary camera angle etc.