mmwcore decodes captured and live mmWave data for offline training and real-time inference. Its boundary starts at caller-owned bytes plus explicit physical contracts, then produces range-Doppler cubes, detections, calibrated point clouds, clusters, tracks, and vital-sign products.
CPython 3.12–3.14:
pip install mmwcoreRust 1.85 or newer:
cargo add mmwcoreMaintained inputs are:
- archived DCA1000 datagrams;
- headerless
int16ADC files with an explicit frame contract; - completed versioned capture directories opened with
open_capture; - finite
mmwcli.capture_stream.v1data supplied through a caller-ownedBinaryIO; - published radar-plus-camera sessions opened with
open_multisensor_capture; - finite
mmwcli.multisensor_stream.v1data opened withopen_multisensor_stream.
| mmwcli output | mmwcore entry point | Typical use |
|---|---|---|
| radar capture-session directory | open_capture |
reproducible offline radar processing |
radar --stream stdout |
open_capture_stream |
pull-driven real-time radar inference |
| radar-plus-camera session directory | open_multisensor_capture |
training data, indexed source access, and causal joins |
aggregate --stream stdout |
open_multisensor_stream |
provisional multi-sensor inference followed by COMMIT/EOF validation |
The matching acquisition commands and camera-producer workflow are documented by mmwcli and its multi-sensor guide.
The library does not configure devices, render firmware commands, or manage live acquisition. Callers must supply ADC layout, frame geometry, timing, antenna geometry, and trusted packet/frame origins when the stored format does not prove them.
group2_i_then_q: complex16 two-lane layout documented by the TI mmWave Studio reader for xWR16xx, xWR18xx, and xWR68xx captures.group4_i_then_q: complex16 four-lane, channel-interleaved layout documented by the TI mmWave Studio reader for xWR12xx and xWR14xx captures.- Source-backed antenna geometries: XWR1642, standard XWR1843 EVM, IWR6843ISK, IWR6843 AOP, and AWR1843 AOP.
These explicit decoders and geometry presets are usable only when the caller proves the actual
layout and board. Versioned mmwcli directory and stream v1 readers accept the three closed family
tuples family=xwr16xx, family=xwr18xx, and family=xwr68xx; each also requires vendor=ti,
empty model/revision, identity_source=route_declaration,
config_format=ti_mmwave_legacy_cli.v1, dtype=int16, byte_order=little, lane_count=2, and
layout=group2_i_then_q.
The embedded legacy CFG must match the declared family: xWR16xx uses the 76–81 GHz range and up to
two TX identifiers, xWR18xx uses 76–81 GHz and up to three, and xWR68xx uses 57–64 GHz and up to
three. Chirp order determines the explicit tx_order; no family selects antenna geometry or a
preset. The standalone TI CLI parser likewise requires an explicit family keyword and has no
default. ADCFileCapture.raw_capture and CaptureStreamContract.raw_capture expose the declared
tuple, but decoder acceptance does not claim that an mmwcli acquisition route has been validated.
route_declaration is not an observed device identity. See the
mmwcli hardware-support matrix.
The repository includes complete command-line examples that consume files or binary stdin and never start hardware:
| Workflow | Example |
|---|---|
| capture directory or explicit raw frames | capture_or_raw.py |
| explicit xWR18xx/XWR1843 EVM geometry and recipe | xwr18_range_doppler.py |
| finite radar live stream | radar_live_stream.py |
| multi-sensor offline training pairs | multisensor_offline_training.py |
| multi-sensor provisional live inference | multisensor_live_inference.py |
See the example index for copyable commands and finalization semantics.
open_capture validates the manifest schema, required regular files, hashes, byte count, and finite
physical contract. The directory must remain unchanged while it is open.
from mmwcore import open_capture
capture = open_capture("capture-session")
raw = capture.frame(0)
print(capture.raw_capture.family, raw.samples.shape)The hash proves internal consistency, not provenance. A supplied preset is the caller's explicit
declaration of a processing contract; the route-declared manifest does not identify or guess a
board. Pass an exact RangeDopplerRecipe or callable preset to open_capture(..., range_doppler=...) when Range-Doppler processing is wanted. Built-in board presets are conveniences,
not family defaults.
import mmwcore
stream = mmwcore.open_capture_stream(source) # caller-owned BinaryIO
for item in stream.frames():
infer(item.frame, stream.contract.radar_capture)
commit = stream.require_commit()Frames remain provisional until require_commit validates COMMIT and terminal EOF. mmwcore neither
closes the source nor opens a process, socket, or device. The source must make read honor any
required deadline or cancellation. Processing is synchronous and pull-driven, without prefetch or
worker threads.
from mmwcore import open_multisensor_capture
session = open_multisensor_capture("training-session")
radar = session.source("radar-0")
radar_capture = radar.open_radar_capture()
for camera_item, radar_item in session.causal_pairs(
"camera-0", "radar-0", lag_min_ns=0, lag_max_ns=50_000_000
):
train(
camera_item.payload,
radar_capture.frame(radar_item.item_index),
)The join uses conservative mapped time intervals, not equal frame numbers or nearest arrival time.
If training needs Range-Doppler cubes instead of raw frames, bind the exact recipe or preset through
open_radar_capture(range_doppler=...) and call range_doppler. Choose processing geometry from
the actual board, never from the family string alone.
from mmwcore import open_multisensor_stream
stream = open_multisensor_stream(source) # caller-owned BinaryIO
provisional = list(stream.items())
commit = stream.require_commit()
accepted = [item for item in provisional if commit.accepts(item)]Radar and delivery_observed camera items expose mapped_time on the same host-relative axis.
A camera exposure_midpoint remains unmapped in the live stream unless the producer supplies a
live mapping; mmwcore never substitutes delivery time for exposure time. Items and derived results
remain provisional until global COMMIT and EOF.
from mmwcore.core import ADCComplexLayout, ADCFrameSpec
from mmwcore.io import ADCFileFrameReader
spec = ADCFrameSpec(
num_chirps=2,
num_rx=4,
num_samples=128,
layout=ADCComplexLayout.GROUP2_I_THEN_Q,
)
reader = ADCFileFrameReader("adc.bin", spec, frame_periodicity_s=0.01)
raw = reader.read_frame(0)
print(raw.samples.shape)ADCFileFrameReader rejects incomplete files by default and reads frames without loading the full
capture.
from mmwcore.core import ADCFrameSpec
from mmwcore.io import assemble_dca1000_frame_bytes
spec = ADCFrameSpec(num_chirps=1, num_rx=1, num_samples=2)
raw, stats = assemble_dca1000_frame_bytes(
[datagram_0, datagram_1],
spec,
frame_start_byte_count=trusted_frame_origin,
payload_values_per_packet=2,
)Stateless assembly requires exactly one complete frame: fixed payload lengths, contiguous u48 byte
slots, and contiguous wrapping u32 packet numbers. frame_start_byte_count must come from the
capture lifecycle; it is never inferred from the first packet or a modulo guess.
Use an explicit PointCloudRecipe with process_adc_to_calibrated_point_cloud, then
cluster_point_cloud and ClusterTracker2D. Source-backed geometry helpers cover XWR1642,
standard XWR1843 EVM, IWR6843ISK, IWR6843 AOP, and AWR1843 AOP; the IWR6843 processing recipes are
one optional preset family, not the mmwcore input boundary. Thresholds, calibration, Tx order, and
tracker timing remain explicit. Keep one tracker instance for a sequence; recreating it discards
temporal state.
use mmwcore::{AdcComplexLayout, AdcFrameSpec, decode_adc_i16};
let spec = AdcFrameSpec::new(1, 1, 2, AdcComplexLayout::Group2IThenQ).expect("valid spec");
let cube = decode_adc_i16(&[1, 2, 3, 4], spec, false).expect("valid captured payload");
assert_eq!(cube.shape(), [1, 1, 1, 2]);mmwcore.core: axes, units, ADC, cube, detection, point-cloud, and tracking contracts.mmwcore.config: finite radar profiles, capture contracts, antenna geometries, and recipes.mmwcore.io: packet, ADC-file, radar/multi-sensor directory, and finite live-stream readers.mmwcore.dsp: FFT, clutter removal, CFAR, calibration, AoA, projection, and clustering.mmwcore.tracking: assignment, stateful trackers, runners, metrics, and validation artifacts.mmwcore.plot: optional research visualizations outside the Rust compute core.
The retained laboratory capture used for the figures below has 5000 frames, 2 chirps, 4 receivers,
128 complex samples, group2_i_then_q, and a 10 ms period. It lacks slope and sample-rate metadata,
so range remains in bins. The source capture is not distributed; the figures are evidence, not a
runnable fixture.
Synthetic tests verify shapes, axes, finite values, wrap behavior, and deterministic transforms. They do not prove a board configuration, capture provenance, universal thresholds, or performance superiority. Device documentation and redistributable reference vectors remain authoritative.
The reproducible synthetic pipeline, workload contract, and comparison rules are documented in docs/benchmarking.md.
uv sync --extra dev --locked
uv run pytest --cov=mmwcore
cargo test --workspace --locked
uv run python benchmarks/pipeline.py --warmups 0 --samples 1 --stream-frames 2See CONTRIBUTING.md and docs/architecture.md.
Apache-2.0. See LICENSE.

