RepStandard

Hey Product Hunt! My co-builder and I built RepStandard after coming across a pose-tracking model that could follow body movement in real time. Like a lot of people, staying active has always been important - sometimes at the gym, sometimes just working out at home. That sparked the idea to build a gamified app for bodyweight work - squats, push-ups, sit-ups, and plank - that actually counts your reps for you. It all runs on-device (nothing ever leaves your phone), no wearables, no gym required. A few things it does: - Adaptive daily program that scales with your progress - Gamified progression - ranks, XP, streaks, badges - Rep recognition tuned for accuracy - Dynamic music (generated with AI) that ramps up during work sets and eases off during rest - Voice cues that guide you through each set - you don't need to look at your phone during the workout It took about 6 months to build - longer than we expected, but we finally shipped it on the App Store. Now the focus is getting it in front of real users and seeing what actually works and what doesn't, which is also why we're here. So here's free 1-month Premium for anyone who wants to try it: https://apps.apple.com/redeem?ct... Would genuinely love your feedback - happy to answer anything!

@edvinasapp Congrats on the launch 🚀 I really like that everything runs on device. For a fitness app that uses a camera, privacy is a huge trust factor, and keeping everything local makes a big difference. I'm curious, after testing with real users, which exercise was the hardest to detect accurately? Push ups, squats, planks, or something else? It feels like solving those edge cases is where the real magic happens. Wishing you both an awesome launch! 💪🔥

@tan_z_tan For this app we're staying focused on bodyweight workouts. I think load recognition would be very difficult, mainly because every gym uses different plates and equipment. However the current app recognizes barbell back squat reps pretty well. Try it. Also thrusters, front squats or anything else that involves squatting works too.

How does the camera actually handle things like messy form or switching between exercises quickly? I get that on-device processing is great for privacy, but curious how reliable the rep counting ends up feeling in a real sweaty home workout.

the on-device pose counting is such a smart move, especially for privacy. one thing i'd love to see is a quick audio cue or short rest timer that kicks in between sets automatically when the camera detects you've stopped, so i'm not constantly staring at the screen to check when to go again.

On-device pose detection with nothing leaving the phone is a great call. Speaking as a barbell guy — being able to recognize the load, not just the reps, would make this a day-one install for me. Is weighted training on the roadmap at all? Congrats on shipping!

@emrahtwgn Thanks for asking. Rep counting accuracy was actually one of the biggest technical challenges. The hardest part wasn't counting reps, but avoiding false counts from movements like getting into the push-up or sit-up position, while also not missing real reps. We spent countless hours filming ourselves and refining the recognition logic. After a lot of iteration, we've reached an accuracy we're really happy with. Still things can get a bit messy if there's a lot of movement happening in the background behind the user.

@yeldem50906 Hey. The audio cues you mentioned are already implemented, so you don't need to look at the screen during the workout. We even have multiple AI voice types for the cues.

Tried the squat counter in my living room and it actually caught my rep count without me touching the screen. The XP and streak thing feels a bit cheesy but it's weirdly motivating to keep showing up.

Building on Emrah's reliability question with the part nobody's hit yet: on-device pose tracking for a full session is a thermal budget problem as much as an ML one. A phone running the camera + a pose model continuously for 30 minutes heats up and throttles, and that's exactly when inference gets flaky — so "accurate" in a 2-minute demo and "accurate at minute 25 of a sweaty circuit" can be different apps. Do you duty-cycle the model between reps or downsample frames to stay under the thermal ceiling, or is it running full-rate the whole set? And when the phone's propped against a water bottle at a bad angle, does it miscount silently or tell the user to reposition? The silent miscount is the one thing that'd make me stop trusting the number.

Real-time rep counting sounds useful for solo training too. How does the model handle exercises where body parts are partially occluded or viewed from different camera angles?

@narek_keshishyan Hey, thank you for the question. Tested it with Iphone from 13 to 17 pro - worked great with every model. However with lower model Iphones the devices gets a bit hot after some time. Regarding miscounts - you get a sound for quality reps so if user would notice if it gets misscounted by not hearing the sound.

@amjad_shaik hey probably thats a bot/AI comment but still to answer regarding the angles - we specifically instruct users to stand sideways so we have the best view of the body parts moving during the exersize.

@elanurince86376 hey, based on the details of your comment I do not think you tried the app :)) but thanks

@md_khayruzzaman We tested every exercise extensively during development. Sit-ups were probably the hardest because people perform them with very different techniques and ranges of motion. It took quite a bit of fine-tuning to make the recognition work reliably.