feat(simulation): add Worker AI polygon runtime and terrain navigation

simulation/ai-polygon/segformer/qualify.py

@@ -0,0 +1,52 @@
+"""Worker-only offline SegFormer comparison; no live control authority."""
+
+import argparse
+import hashlib
+import json
+import time
+from pathlib import Path
+
+import numpy as np
+import torch
+from PIL import Image
+from transformers import SegformerForSemanticSegmentation, SegformerImageProcessor
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--image", type=Path, required=True)
+    parser.add_argument("--output", type=Path, required=True)
+    args = parser.parse_args()
+    processor = SegformerImageProcessor.from_pretrained("/assets", local_files_only=True)
+    model = (
+        SegformerForSemanticSegmentation.from_pretrained("/assets", local_files_only=True)
+        .cuda()
+        .eval()
+    )
+    image = Image.open(args.image).convert("RGB").crop((100, 0, 700, 600))
+    tensor = processor(images=image, return_tensors="pt")["pixel_values"].cuda()
+    times = []
+    with torch.inference_mode():
+        for _ in range(6):
+            torch.cuda.synchronize()
+            start = time.monotonic()
+            logits = model(tensor).logits
+            logits = torch.nn.functional.interpolate(
+                logits, size=(512, 512), mode="bilinear", align_corners=False
+            )
+            labels = logits.argmax(1)[0].cpu().numpy().astype(np.uint8)
+            times.append((time.monotonic() - start) * 1000)
+    args.output.mkdir(parents=True, exist_ok=True)
+    Image.fromarray(labels).save(args.output / "labels.png")
+    ids, counts = np.unique(labels, return_counts=True)
+    report = {
+        "source_sha256": hashlib.sha256(args.image.read_bytes()).hexdigest(),
+        "classes": {model.config.id2label[int(i)]: int(counts[n]) for n, i in enumerate(ids)},
+        "inference_ms": times,
+    }
+    (args.output / "report.json").write_text(json.dumps(report, indent=2), encoding="utf-8")
+    print(json.dumps(report))
+
+
+if __name__ == "__main__":
+    main()