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Streaming iPhone data in real-time directly to Rerun 🚀 The collection process is one of the most frustrating parts of building imitation-learning datasets. I’ve got a little army of sensors—📱 iPhone, iPad, Quest 3—but getting them temporally aligned, spatially aligned, AND seeing real-time feedback while recording is tough. I...

27,383 просмотров • 1 год назад •via X (Twitter)

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🚀 Introducing EgoExo Forge - built on top of Rerun, Gradio, and Hugging Face hub (I’ll be in San Francisco July 21–29 — if you’re into robotics, egocentric AI, large-scale data collection, or just want to chat, DM me!) In my opinion, large-scale, diverse, and high-quality data is still the largest bottleneck for generalized robotics deployment. I believe that some version of imitation learning from human examples will be the most scalable + clean way to train humanoid robots 🤖 (similar to what Tesla did for Full Self Driving). Teleop is too expensive to collect a large enough dataset in a reasonable manner, so passive collection via egocentric (and in certain cases, exocentric) views feels like the right bet. Over the past few months, I've been trying to build out the scaffolding for this and using Rerun as my underlying infrastructure. Data being collected needs to be easily inspectable + time series and rerun provides the right tooling for this. My goal is to first build out a ground truth representative dataset from already existing open source data, generate some reasonable baselines, and then go out and collect my own data that adheres to the defined schema. 🔍 Starting with open-source datasets 1. EgoDex from Apple 2. HOCap from Nvidia and the University of Texas at Dallas 3. Assembly101 from Meta All these different datasets have different sensor configurations + annotations, so my goal with egoexo-forge is to have one consistent labeling scheme + data layout. I built a data pipeline that aligns all of the different datasets in one general schema assuming the COCO133 keypoint layout that allows for exo+ego, ego only, or exo only Since the scaffolding is already there, it becomes MUCH easier to add other datasets. So the next ones that I'll be including are HD-EPIC kitchens dataset, HOT3D, and finally my own personal iPhone + insta360 go collection method. Once I have a diverse variety of datasets, I'll double down on what I believe to be the key algorithms required to make useful data for imitation learning 📊 1. Camera Pose estimation via SLAM/SFM for ego perspective (and automatic calibration for exo) 2. Human pose estimation for both egocentric + exocentric views 3. Metric 3D reconstruction + object tracking I'll be setting up reasonable open-source baselines for each of these to validate that these datasets work, and then finally try to use the generated datasets for some imitation learning via the pi0-lerobot repo I've been working on. I plan on making a blog post + providing more info on all of this in the near future so stay tuned

Pablo Vela

32,085 просмотров • 1 год назад

Colmap 4.0 was very recently released, so it inspired me to do some work to better understand it and its new capabilities with Rerun. I want to really understand how Colmap, and in particular, pycolmap, works outside of just calling it via the CLI. So my goal is to use the low-level pycolmap API to log every part of the pipeline. The explicit goal is to have an alternative to the SQLite database that I can utilize. Instead of SQLite, I want to try logging everything directly to rerun and use RRD. This means I can have deep inspectability and still save the features/matches/2D view geometry, but be able to view it directly in rerun. I think this is one of the superpowers that rerun provides; data and visualizations are deeply integrated. As I'm often working with sequential data (videos), I'm going to specifically focus on four things: 1. Monocular Video Simple: Calls high-level APIs such as pycolmap.extract_features, pycolmap.match_sequential, pycolmap.incremental_mapping. These are basically identical to the CLI options and provide a good baseline. 2. Monocular Video Streamed: Take the above high-level APIs and break them down to their iterator version, logging each component in a streamed manner. This way, I can stream the intermediate features to rerun while the extraction/matching/mapping is happening. 3. Rig with unknown calibration: <- WHAT THE VIDEO SHOWS This is probably the most interesting version and the first one I've been working on. It allows one to set a rig between known sensors, such as in VR/AR devices, leading to much better reconstructions with multiple cameras. This is the case where we don't know the calibration a priori, so we have to run a reconstruction twice: once as a normal Colmap reconstruction with no rig constraints, use this to generate the constraints, and then do it again with the newly found rig. 4. Rig with known calibration: This is the RoboCap example, where we have a pre-calibrated set of sensors, so we don't need to run the two reconstructions and also gain better matching between cameras, both spatially and temporally. Again, this leads to a much better reconstruction! Along with all this, GLOMAP has become a first-class global mapper, making it super easy to use directly within pycolmap! I'm excited to do more with this and compare it to things like pycuvslam, vipe, and other alternatives.

Pablo Vela

30,070 просмотров • 3 месяцев назад

I made over 2.5 million dollars this past week betting sports. Yes, it sounds easy. Yes, it sounds simple. But the truth is, this is the result of years of obsession, discipline, and grinding at my craft. I spent four straight years playing poker 18 hours a day. That was my entire life. Wake up, play poker, think about poker, sleep, repeat. That level of focus is how I became one of the top players in the world and made over 10 million dollars playing poker. Poker built my foundation. Discipline, risk management, emotional control, and the ability to perform under real pressure. But the reality is, there are no billionaires in poker. There are billionaires in sports betting. So I went all in on sports betting and walked away from poker completely. I took everything I learned and built this the right way. I hired the best analysts and handicappers in the world, people I met through poker, and brought them together under one operation. Because of the platform I’ve built, these guys make more money working with me than they ever could on their own. That is how I’m able to operate at an extraordinary level and consistently win at a very high rate. Winning 2.5 million dollars in a week is incredible, and I’m grateful, but I’m not satisfied. I’m constantly sharpening my edge and building something bigger. My vision is to turn this into a nine figure a year business. I truly believe I’m on the path to becoming a billionaire one day. I think back to being a kid, dreaming of being a professional gambler, having a gambling themed bar mitzvah, and looking up to my father, one of the best poker players in the world. This path has been inside me for a long time. Today, my entire life revolves around becoming the best sports bettor possible. I wake up thinking about it, go to sleep thinking about it, and live it every single day. Grateful for the journey. Let’s keep going.

Sean Perry

105,912 просмотров • 5 месяцев назад

The past year has seen me have a renaissance, in the truest sense… I won’t go into details now but will at some point before long. What has brought so much happiness to my life and those around me this past year has been my falling back in love with sport. Cycling has, and always will be, my number one. Yet I’d forgotten that I simply love sport, not for results but for the sheer joy of doing it, I’d completely forgotten that the health of my mind is intrinsically connected to the health of my body. I’ve rediscovered the love I had for sport that existed before the world of professional cycling took over in the way it did. I’ve been pushing myself and trying new things this past year, indifferent to the results, just out having fun and at times going deeper than I thought I was capable of anymore. Last week I got on a TT bike for the first time in a decade, Factor Bikes built me a bike, I’ve been looking at it for two years and decided it was time to get fitted, getting back on it felt like going home. Anyway, the long and the short of this is that it’s inspired me to create a club to inspire and be inspired. A community for us to share our love for getting out there and doing it, because I’ve realized that although I spend most of my sporting life on my own I derive the most pleasure when feeling part of something. It’s in its early days, I’ve called it Sporting Club CHPT3 aka SCC3, I’d love you to check it out and join. It’s still in its infancy, but I hope it’s going to grow into something that will inspire you as much as me.

David Millar

111,669 просмотров • 2 лет назад