21 posts
The forehand-or-backhand call has been stuck for two weeks. The fix: draw a skeleton on every player and read the actual swing.
A human has clicked four corners for every match this project ever charted. A free pretrained network just took the job — and knew when to refuse it.
The ball tracker blinks at the worst moments. Broadcast microphones don't. The software learns to listen for the pock of strings on ball.
The machine couldn't tell wide errors from deep ones. The fix: stop trying to watch the bounce and calculate it, like Hawk-Eye does.
Court Vision introduces itself to the real volunteers who chart tennis matches by hand, and asks whether its drafts actually save them time.
A bigger test made the trust score honestly drop — then a check that could never fail got caught, and the score climbed back up.
A confidence flag tells a volunteer chart-corrector which draft points to trust — and this post checks whether the flag itself can be trusted.
The project finally gets an honest report card: how many fixes would turn the machine's chart into a human's? Today's first answer: 2.2%.
A TV scoreboard graphic nobody notices turns out to be the only reliable way to tell where one point ends and the next begins.
A free specialist replaces an expensive all-purpose tracker — and exposes that its rival's biggest flaw was secretly marking the end of every point.
Graded against a real human chart for the first time, the system's biggest miss was a lefty problem, not a broken tool.
The software faces its first honest test against a match a human already scored, and the camera math needs fixing first.
When the software can't tell who hit the ball, it holds a vote instead of guessing — and the ball outvotes the serve call, on camera.
The serve toss lets the software find the ball itself, and it charts its first full point without a human drawing a single box.
The 'still' broadcast camera actually drifts mid-point — and that breaks a free trick for spotting players in video.
Most of a tennis broadcast isn't the match — the software has to spot the one camera angle that actually shows it.
The software found the players by noticing who never moved, then called every forehand and backhand from where the ball crossed their body.
Teaching software to spot every hit and bounce in a rally, just from watching the ball's path bend.
How four painted corners taught the software to turn a TV picture of the court into a real, to-scale court diagram — for free.
An AI that finds objects by description can't tell one tennis ball from six on court — until you point at the one in play.
Can a computer watch a tennis broadcast and write down every shot, the way a courtside volunteer does by hand?