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tennis-cv

project guide for building a tennis CV tracker

Details

External ID
1364330119
Source
GITHUB
Company
—
Product
tennis-cv
Website domain
x.com
Launched
Sept. 10, 2026
Cohort
—
Upvotes
57
Upvotes percentile
0.8490263899564437
Tags
—
Fetched at
Sept. 14, 2026, 5:28 p.m.
Updated at
Sept. 14, 2026, 5:28 p.m.

Enrichment

Theme
habit and daily routine trackers
Vertical
Media & entertainment
Function
Dev tools
Audience
Developer
AI stance
AI feature
Project type
Hobby / open-source project
Normalized one-liner
project guide for building a tennis computer vision tracker
Manually corrected
False

Could you build this?

Partial While basic video processing scripts can be vibe coded, training and deploying high-frame-rate computer vision models to accurately detect fast-moving small tennis balls and calculate 3D trajectory/speeds requires ML expertise.

What it would actually take: A full version requires a Python and OpenCV pipeline integrated with fine-tuned object detection (RF-DETR/YOLO) for the ball and racket, paired with human pose estimation (e.g., MediaPipe or RTMPose) for stroke classification. The hard challenges involve multi-frame ball tracking despite motion blur, 2D-to-3D homography calibration of the court to compute true ball speed, and low-latency inference on mobile video inputs.

Competitors

Other products that read as similar to this one — 73 launches clear the similarity bar, closest 8 shown.

Attention rank: #6 of 74 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 303 days after the earliest competitor.

Other launches for this product

Same idea, different domain

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