Padel Video & Image Annotation in Label Studio

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 games) • Pre-filled with model predictions — confirm or correct • ~15 seconds per clip Project 2 — Player identity (P1–P4 bounding boxes) • 276 frames with pre-drawn boxes (venue 1, 5 games) • 252 additional frames (venue 2) — boxes must be drawn manually • Assign each of 4 players a consistent ID per match Project 3 — Ball position + event marking ★ LARGEST TASK • 12,415 frames (both venues, 10 games) • Fully manual — mark ball position AND event per frame • No pre-labels; this is the most time-consuming project Project 4 — Racket bounding boxes • 916 frames (both venues) • Draw a box around EVERY visible racket in each frame Project 5 — Court keypoints • 176 frames (venue 2 only) • Place up to 12 named court keypoints per frame TOTAL ESTIMATED EFFORT: ~150–160 hours for a careful annotator (~19–20 full working days at 8 hrs/day) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHAT YOU MUST DELIVER ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ When all tasks in a project are complete: 1. Export from Label Studio as JSON (full format with annotations) 2. Name files exactly: • [login to view URL] • [login to view URL] • [login to view URL] • [login to view URL] • [login to view URL] 3. Deliver all 5 files in one final submission 4. Include a short notes file listing any frames you skipped and why We will run automatic quality checks against our gold set. If a batch falls below the quality bar, we will return specific disagreements for you to fix (included in scope — no extra charge for one revision round). ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ QUALITY BARS (must be met) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ • Shot-type: ~80% agreement with gold set • Player identity: ≥95% boxes on correct person • Ball + events: ≥85% ball within 8px; ≥85% events on correct frame • Racket boxes: all visible rackets boxed (completeness matters most) • Court keypoints: points within ~8px; leave invisible points blank ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ REQUIREMENTS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ MUST HAVE: ✓ Prior experience with image/video annotation (bounding boxes, keypoints) ✓ Comfortable installing and using Label Studio locally ✓ Windows or Mac with enough disk space (~10 GB free) ✓ Stable internet for downloading the 6.3 GB package ✓ Strong attention to detail and ability to follow precise labeling rules ✓ Ability to work independently through a large dataset without supervision ✓ Good English reading comprehension (all instructions are in English) NICE TO HAVE: • Experience with sports video annotation • Experience with Label Studio specifically • Familiarity with padel or tennis (helps with shot-type judgment) • Prior work on ball tracking or event detection datasets NOT REQUIRED: • Programming skills • ML/model training knowledge ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ HOW TO APPLY ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Your proposal MUST include: 1. Examples of prior annotation work (screenshots or portfolio links) 2. Your estimated timeline to complete all 5 projects 3. Confirmation you can install Label Studio (Python 3.9+) locally 4. Your fixed price quote for the FULL scope (all 5 projects + 1 revision round) 5. Answer to screening question: "How would you handle a frame where two teammates look identical and you cannot tell them apart?" Proposals without annotation examples will not be considered. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PAYMENT STRUCTURE (milestones) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Payment is milestone-based: M1 (10%) — Setup Label Studio + complete 1 pilot game across all applicable projects; we review before you continue M2 (20%) — Project 1 (shot-type) complete + accepted M3 (15%) — Project 2 (player identity) complete + accepted M4 (40%) — Project 3 (ball + events) complete + accepted M5 (10%) — Projects 4 + 5 complete + accepted M6 (5%) — Final revision pass after our QA feedback Do not start bulk labeling before M1 pilot is approved. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHAT WE PROVIDE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ • Complete labeling package (download link upon award) • Label Studio XML configs (copy-paste into project settings) • Per-project [login to view URL] with rules, hotkeys, edge cases, skip rules • Example correct labels and expected JSON export format per project • Reference rally video clips for context while labeling frames • One round of QA feedback with specific items to fix ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ IMPORTANT RULES (summary) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ • Work ONE GAME AT A TIME — player identities (P1–P4) reset every match • NEVER carry player IDs between games or between venues • Two venues = completely different events (different players, courts) • Where pre-labels exist: confirm or correct — don't redraw from scratch • Ball + events: never guess a hidden ball — mark "ball_not_visible" instead • Racket: box ALL visible rackets, not just the hitter's • Court: leave keypoints blank if not visible — never guess off-screen Full detailed instructions are in the package README and per-project guides.

Project ID: 40493650