[AZ-161] [AZ-162] [AZ-163] Add ONNX inference, NMS, annotation queue tests

Made-with: Cursor

tests/performance/test_inference_perf.py

@@ -0,0 +1,33 @@
+import time
+
+import cv2
+import numpy as np
+import pytest
+
+from inference.onnx_engine import OnnxEngine
+
+
+@pytest.fixture(scope="session")
+def onnx_engine_session(fixture_onnx_model):
+    return OnnxEngine(fixture_onnx_model)
+
+
+@pytest.mark.performance
+def test_pt_inf_01_single_image_onnx_latency(onnx_engine_session, fixture_images_dir):
+    engine = onnx_engine_session
+    imgs = sorted(fixture_images_dir.glob("*.jpg"))
+    assert imgs
+    frame = cv2.imread(str(imgs[0]))
+    assert frame is not None
+    model_height, model_width = engine.get_input_shape()
+    n = engine.get_batch_size()
+    frames = [frame] * n
+    blobs = [
+        cv2.dnn.blobFromImage(f, 1.0 / 255.0, (model_width, model_height), (0, 0, 0), swapRB=True, crop=False)
+        for f in frames
+    ]
+    blob = np.vstack(blobs)
+    t0 = time.perf_counter()
+    engine.run(blob)
+    elapsed = time.perf_counter() - t0
+    assert elapsed <= 10.0