Update native RC1 samples and supported device documentation

README.md

@@ -51,6 +51,10 @@ Typical Metro deployments include:
 
 ## Prerequisites
 
+Target stack: Intel DLStreamer **2026.3.0 RC1** with the matching OpenVINO GenAI bundle **2026.5.0.0.dev20261030** (OpenVINO Runtime **2026.5.0.dev20261030**).
+Use the [native RC1 setup](../README.md#native-rc1-runtime) before running these samples; this is a development stack, not a stable release.
+See the [device validation matrix](../DEVICE_SUPPORT_MATRIX.md) for measured CPU, GPU, and NPU results.
+
 - Python 3.11+
 - OpenCV and NumPy
 
@@ -86,7 +90,16 @@ baseline, and classifies each frame as `normal`, `dark`, `bright`, or
 `sudden-change`.
 The annotated frames are written to `output_opencv.mp4`.
 
+The full sample is in [opencv_sample.py](opencv_sample.py); run it with `python3 opencv_sample.py` or copy the code below.
+
+<!-- sample: opencv_sample.py -->
 ```python
+# SPDX-License-Identifier: MIT
+# Copyright (C) Intel Corporation
+#
+# Light-Level Anomaly Detection: OpenCV sample.
+# See README.md for prerequisites and inputs. Run: python3 opencv_sample.py
+
 import cv2
 import numpy as np
 
@@ -139,6 +152,7 @@ cap.release()
 writer.release()
 print(f"Light-level anomalies detected: {anomalies}", flush=True)
 ```
+<!-- /sample -->
 
 **Device targets:**
 

opencv_sample.py

@@ -0,0 +1,57 @@
+# SPDX-License-Identifier: MIT
+# Copyright (C) Intel Corporation
+#
+# Light-Level Anomaly Detection: OpenCV sample.
+# See README.md for prerequisites and inputs. Run: python3 opencv_sample.py
+
+import cv2
+import numpy as np
+
+INPUT_VIDEO = "test_video.mp4"
+DARK_BOUND = 40.0    # mean luminance below this is underexposed
+BRIGHT_BOUND = 215.0  # mean luminance above this is overexposed
+JUMP_BOUND = 35.0    # frame-to-frame luminance jump that counts as sudden
+
+cap = cv2.VideoCapture(INPUT_VIDEO)
+fps = cap.get(cv2.CAP_PROP_FPS) or 30.0
+width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+writer = cv2.VideoWriter(
+    "output_opencv.mp4", cv2.VideoWriter_fourcc(*"mp4v"), fps, (width, height))
+
+prev_level = None
+frame_idx = 0
+anomalies = 0
+while True:
+    ok, frame = cap.read()
+    if not ok:
+        break
+    frame_idx += 1
+
+    v = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)[:, :, 2]
+    level = float(np.mean(v))
+
+    status = "normal"
+    if level < DARK_BOUND:
+        status = "dark"
+    elif level > BRIGHT_BOUND:
+        status = "bright"
+    elif prev_level is not None and abs(level - prev_level) >= JUMP_BOUND:
+        status = "sudden-change"
+    prev_level = level
+
+    if status != "normal":
+        anomalies += 1
+        print(f"Frame {frame_idx}: LIGHT ANOMALY ({status}) level={level:.1f}",
+              flush=True)
+    color = (0, 255, 0) if status == "normal" else (0, 0, 255)
+    label = f"level={level:.1f} {status}"
+    (_, text_height), _ = cv2.getTextSize(
+        label, cv2.FONT_HERSHEY_SIMPLEX, 5.0, 2)
+    cv2.putText(frame, label, (10, text_height + 10),
+                cv2.FONT_HERSHEY_SIMPLEX, 5.0, color, 2)
+    writer.write(frame)
+
+cap.release()
+writer.release()
+print(f"Light-level anomalies detected: {anomalies}", flush=True)