Initial commit

Divers/jetson/inference.py

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+import pyrealsense2 as rs
+import cv2
+import numpy as np
+import jetson.inference
+import jetson.utils
+import time
+
+net=jetson.inference.detectNet("SSD-Inception-v2", threshold=0.5)
+#net=jetson.inference.detectNet("SSD-MobileNet-v2", threshold=0.5)
+display=jetson.utils.videoOutput("display://0")
+
+pipeline=rs.pipeline()
+config=rs.config()
+
+config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 15)
+config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 15)
+
+align_to = rs.stream.color
+align = rs.align(align_to)
+
+pipeline.start(config)
+
+while True:
+
+    frames=pipeline.wait_for_frames()
+
+    aligned_frames = align.process(frames)
+
+    depth_frame=aligned_frames.get_depth_frame()
+    color_frame=aligned_frames.get_color_frame()
+
+    if not depth_frame or not color_frame:
+        continue
+
+    depth_image=np.array(depth_frame.get_data())
+    color_image=np.array(color_frame.get_data())
+
+    depth_colormap=cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET)
+
+    start=time.time()
+    cuda_image=jetson.utils.cudaFromNumpy(color_image)    
+    detections=net.Detect(cuda_image, color_image.shape[1], color_image.shape[0])
+    print("Temps", time.time()-start)
+    
+    display.Render(cuda_image)
+    cuda_image=jetson.utils.cudaToNumpy(cuda_image)
+
+    cv2.imshow('RealSense1', depth_colormap)
+    #cv2.imshow('RealSense2', color_image)
+    cv2.imshow('cuda_image', cuda_image)
+    key=cv2.waitKey(1)&0xFF
+    if key==ord('q'):
+        pipeline.stop()
+        quit()