x86-npu-inference-opencv-7.ino
Python/OpenCV pipeline leveraging 4K capability and prepared for NPU acceleration via OpenVINO.
This script requires an OpenCV installation linked to OpenVINO to fully leverage the 15-16 TOPS NPU. The Intel Wildcat Lake SoC handles hardware decoding via Intel Xe3 graphics. Ensure Intel graphics drivers are up to date under Windows 11 or Linux. The example uses a USB webcam, but can be adapted to industrial cameras via M.2 or Ethernet. 4K resolution must be supported by the monitor connected via HDMI 2.1 or DisplayPort 1.4.
x86-npu-inference-opencv-7.ino
import cv2
import numpy as np
# Note : Pour utiliser le NPU Intel Wildcat Lake, OpenCV doit être compilé avec le backend OpenVINO
# Installez les dépendances : pip install openvino opencv-python numpy
def detect_objects():
print("Démarrage de la caméra via OpenCV (Webcam USB ou CSI adapté)")
cap = cv2.VideoCapture(0)
if not cap.isOpened():
print("Erreur : Impossible d'ouvrir la caméra")
return
# Configuration pour la sortie 4K (HDMI 2.1 / DP 1.4)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 3840)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 2160)
try:
while True:
ret, frame = cap.read()
if not ret:
break
# Exemple de traitement léger sur le CPU/GPU Xe3
# Pour une vraie utilisation NPU, injecter un modèle .bin.xml OpenVINO ici
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray, 50, 150)
cv2.imshow('EdgeComp MS-U320 Vision Pipeline', edges)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
except Exception as e:
print(f"Erreur : {e}")
finally:
cap.release()
cv2.destroyAllWindows()
if __name__ == "__main__":
detect_objects()