ZPE-XR

Package Install

Installable package: python3.11 -m pip install zpe-xr. Current release: 0.3.1 on PyPI. Source: Zer0pa/ZPE-XR.

python3.11 -m pip install zpe-xr

For full install, smoke, source, and developer commands, click here.

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00 · ZPE-XR · MOTION TRANSPORT RESEARCH-READY · COMPARATOR 0/5 Hands that travel, byte for byte. Two-hand pose transport codec · zpe-xr v0.3.1 · github.com/Zer0pa/ZPE-XR In a VR session your hands are always moving — picking up, pointing, reaching across a room. Today that motion is a stream of raw floats, expensive on the network and erased the moment the session ends. ZPE-XR is a different answer: a sealed 25.9-byte packet for two complete hands per frame, decoded in 0.057 ms to byte-identical output on any machine, any year. The transport works on ContactPose. Unity and Meta runtime integration is still external; float16+zlib still wins raw fidelity by 0.2 mm.

Scope: ContactPose transport. Comparator 0/5 and runtime closure pending; byte-identical transport is not a fidelity win.

01 · THE GAP ARRIVED WRONG VR hands arrive late or too large — the experience breaks before the scene does.

02 · MARKETS ADJACENT FORECASTS Release posture BLOCKED Hand tracking solutions $10.9B '33 Extended Reality market $59.2B '31 Spatial computing $280B '28 Ultraleap ref revenue ~$30M Hand tracking 19.7% CAGR through 2033; XR 41% CAGR to 2031. Transport is the wire all of it runs on.

03 · VALUE OF MARKET 23.9× Smaller than a raw two-hand frame · 6.63× smaller than Ultraleap VectorHand

04 · INSIGHT A hand in motion is data that needs to travel.

05.1 · CURRENT TECH FLOAT STREAM AND ZLIB XR developers ship hand motion as raw float streams or float16+zlib. Both move bytes. Neither is a transport: no sealed packet, no sequence numbering, no loss recovery, no byte-identical replay, no record after the session ends.

05.2 · OUR TECH SEALED PACKETS ZPE-XR encodes two complete hands — 21 joints each — as a sealed, CRC32-checked packet at 25.9 bytes per frame, 23.9× smaller than raw. A backup sequence number recovers from drops without a keyframe stall. Encode plus decode runs in 0.057 ms, and every recorded ContactPose stream plays back the same hands on any machine, any year.

05.3 · BENCHMARKS CONTACTPOSE MEASURED Compression23.9×vs raw Enc+dec0.057ms MPJPE0.479mm Comparator0/5fidelity Transport size PASS Round-trip speed PASS Fidelity MISS Scope: ContactPose 5-sequence, 3,500 frames. Transport passes. Fidelity comparator 0/5.

06 · MEASUREMENT TRANSPORT VS FIDELITY Every transport number ships next to a fidelity reading.

06.1 · COMPARATIVE PERFORMANCE CONTACTPOSE BYTES PER FRAME ZPE-XR 25.9 bytes/frame float16+zlib ~110 bytes/frame raw float32 619.5 bytes/frame comparator fidelity 0/5 ContactPose five-sequence run, 3,500 frames. ZPE-XR ships 25.9 bytes per two-hand frame — 6.63× under Ultraleap, 1.47× under Photon Fusion. float16+zlib still wins raw fidelity: 0.277 mm vs 0.479 mm MPJPE — comparator 0/5.

07 · KEY METRICS MEASURED RESULTS

07.1 · VS RAW 23.9× vs raw float32 · ContactPose two-hand comparator

07.2 · BYTES / FRAME 25.9B two complete hands · 6.63× smaller than Ultraleap

07.3 · ENC + DEC 0.057ms encode + decode mean · 3,500-frame ContactPose run

07.4 · MPJPE 0.479mm ZPE-XR vs 0.277 mm float16+zlib · fidelity comparator 0/5

07.5 · LOSS @ 10% 0.399% pose error at 10% loss · 9.5× more resilient than Ultraleap proxy

08 · DETERMINISM BOUNDED REPLAY Packets replay identically. Deployment evidence stays external.

08.1 · WHAT REPLAYS EXACTLY CONTACTPOSE SURFACE On the measured ContactPose surface — five sequences, 3,500 frames — every ZPE-XR packet carries a CRC32 tail and a backup sequence number. The recorded stream decodes byte-for-byte the same on any machine, any year. The checksum is a provenance anchor, not just an error detector. The determinism claim is bounded to the encoded stream — not to the sensor estimating the hand or the engine smoothing the output. float16+zlib still wins raw fidelity: 0.277 mm versus 0.479 mm MPJPE. Comparator 0/5; closing that gap is active research.

08.2 · THE FIDELITY GAP Honest Blocker · float16+zlib wins fidelity (0.277 mm vs 0.479 mm). Comparator 0/5. Unity and Meta runtime closure is externally dependent. Photon Fusion semantic parity remains an open secondary. Replay-error corpus evidence beyond ContactPose is unresolved. PyPI zpe-xr 0.3.1 stale; 0.3.2 pending.

09 WHEN HANDS BECOME PERSISTENT DATA.

09.1 · THE AMBITION Embodiment in XR has been disposable. ZPE-XR makes it the opposite: a sealed packet small enough to network at chat-app bandwidth, faithful enough to play back as the same hands every time, and structured enough to search across recordings. Headsets, robots, archives, and training corpora share one transport for motion.

09.2 · WHAT WORKS NOW A ContactPose-bounded transport: 25.9 bytes per two-hand frame, 0.057 ms round-trip, byte-identical replay under packet loss.

09.3 · WHAT'S STILL OPEN Raw fidelity against float16+zlib, Unity and Meta runtime closure, Photon semantic parity, broader corpora, and the 0.3.2 release.

09.4 · TELEPRESENCE · NEAR-TERM (12–24 MO) Multiplayer hands at messaging-app bandwidth A four-player social session at 90 fps fits inside 6.84 KB/s — the bandwidth budget of a chat app, not a video call. Social-VR studios stop paying a voice-call price just to render fingers, and continuous embodied presence becomes a default rather than a feature.

09.5 · ARCHIVES · NEAR-TERM (12–24 MO) Embodied sessions become persistent records A two-hour session compresses to roughly 49 MB with no fidelity drift on replay. Coaching reviews, surgical rehearsal, factory walkthroughs, and forensic playback stop ending when the headset comes off. Embodiment graduates from disposable runtime state into a scrubable, hash-addressable record.

09.6 · MOTION SEARCH · MID-TERM (24–48 MO) Hand motion becomes a queryable corpus Once every frame is hashed and every gesture fingerprinted, recorded sessions become a search surface. “Find every clip where two hands hand off a mug” turns into a tractable query. Coaches, ergonomists, and rehab clinicians get a search bar over embodied behavior.

09.7 · HUMAN-ROBOT REPLAY · MID-TERM (24–48 MO) Headset hands and robot arms share a clock When a human demonstration and a robot re-run share one packet format, imitation-learning pipelines and teleoperation review collapse into a single timeline with one parity hash. Human-in-the-loop robotics gets a common ground truth where today it has two stacks talking past each other.

09.8 · PHYSICAL AI · PARADIGM (48 MO+) Embodiment becomes network infrastructure The same 26-byte envelope that carries a human hand can carry a robot manipulator across headsets, simulators, training agents, and forensic archives without rewriting at each boundary. Spatial computing stops treating presence as a per-engine reconstruction problem; the network itself carries embodiment as a first-class signal.

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Install / Developer Commands Detailed

Package Install

Installable package: python3.11 -m pip install zpe-xr. Current release: 0.3.1 on PyPI. Source: Zer0pa/ZPE-XR.

python3.11 -m pip install zpe-xr

Import smoke:

python3.11 - <<'PY'
import importlib.metadata as md
import zpe_xr

print("zpe-xr", md.version("zpe-xr"))
PY

Install success only proves package acquisition/import. Product scope, stale PyPI state, platform limits, and blockers remain in the front-door sections below.

• PyPI copy is stale and the wheel matrix is uneven; use Python 3.11 for smoke checks.

Quick Start

Install from PyPI:

pip install zpe-xr

Verify from source:

git clone https://github.com/Zer0pa/ZPE-XR.git zpe-xr
cd zpe-xr
python -m venv .venv
source .venv/bin/activate
python -m pip install "./code[dev]"
python ./executable/verify.py
python -m pytest ./code/tests -q

Read docs/ARCHITECTURE.md first, then docs/LEGAL_BOUNDARIES.md, then the Phase 5 and Phase 6 proof anchors above. LICENSE is the legal source of truth; the repo uses SAL v7.1.