Update native RC1 samples and supported device documentation

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# 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)

	# 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)