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Replicates TurboVision's public-model latency gate locally:
p95 per-frame inference latency must be <= 100 ms in a 2 vCPU environment.
Run pinned to 2 CPUs to match the compliance environment:
taskset -c 0,1 python benchmark_latency.py [--frames 100] [--imgsz 640]
Frames are synthesized at 1280x720 (the validator resizes the long side to
1280 before calling miners), or loaded from --image-dir if given.
"""
import argparse
import os
import time
from pathlib import Path
os.environ.setdefault("OMP_NUM_THREADS", "2")
# The compliance environment has no GPU; hide any local one so torch runs on CPU.
os.environ["CUDA_VISIBLE_DEVICES"] = ""
import numpy as np
def load_frames(image_dir: str | None, n: int) -> list[np.ndarray]:
if image_dir:
import cv2
paths = sorted(Path(image_dir).glob("*"))[:n]
frames = [cv2.imread(str(p)) for p in paths]
frames = [f for f in frames if f is not None]
if frames:
return frames
rng = np.random.default_rng(0)
return [
rng.integers(0, 255, size=(720, 1280, 3), dtype=np.uint8) for _ in range(n)
]
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("--frames", type=int, default=100)
parser.add_argument("--imgsz", type=int, default=640)
parser.add_argument("--image-dir", default=None)
parser.add_argument("--warmup", type=int, default=5)
args = parser.parse_args()
import torch
torch.set_num_threads(2)
os.environ["SV_IMG_SIZE"] = str(args.imgsz)
from miner import Miner
miner = Miner(path_hf_repo=Path(__file__).parent)
frames = load_frames(args.image_dir, args.frames)
for frame in frames[: args.warmup]:
miner.predict_batch([frame], offset=0, n_keypoints=0)
latencies_ms = []
for frame in frames:
start = time.perf_counter()
miner.predict_batch([frame], offset=0, n_keypoints=0)
latencies_ms.append((time.perf_counter() - start) * 1000)
latencies_ms.sort()
p50 = latencies_ms[len(latencies_ms) // 2]
p95 = latencies_ms[int(len(latencies_ms) * 0.95)]
print(f"model={miner.model_name} imgsz={args.imgsz} frames={len(frames)}")
print(f"p50={p50:.1f} ms p95={p95:.1f} ms mean={sum(latencies_ms)/len(latencies_ms):.1f} ms")
print("PASS (<=100 ms p95)" if p95 <= 100 else "FAIL (>100 ms p95)")
if __name__ == "__main__":
main()
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