Engineering

[Fixture] Benchmarking stereo depth models on embedded edge accelerators

Development fixture on benchmarking stereo depth models on edge accelerators.

Running disparity calculations locally at 30fps under 15W power constraints requires careful kernel optimization and fixed-point quantization.

edge/pipeline_runner.pypython
# Example synthetic pipeline benchmark
import time

def process_frame(stereo_pair):
    depth_map = disparity_engine.compute(stereo_pair.left, stereo_pair.right)
    signals = behavioral_extractor.extract(depth_map)
    return signals
Synthetic snippet demonstrating the on-device inference boundary.