\u51fa\u5178\u30b5\u30a4\u30c8<\/a><\/p>\n#!\/usr\/bin\/env python
\n# Fast reading from the raspberry camera with Python, Numpy, and OpenCV
\n# Allows to process grayscale video up to 124 FPS (tested in Raspberry Zero Wifi with V2.1 camera)
\n#
\n# Made by @CarlosGS in May 2017
\n# Club de Robotica - Universidad Autonoma de Madrid
\n# http:\/\/crm.ii.uam.es\/
\n# License: Public Domain, attribution appreciated
\nimport cv2
\nimport numpy as np
\nimport subprocess as sp
\nimport time
\nimport atexit
\nframes = [] # stores the video sequence for the demo
\nmax_frames = 300
\nN_frames = 0
\n# Video capture parameters
\n(w,h) = (640,240)
\nbytesPerFrame = w * h
\nfps = 250 # setting to 250 will request the maximum framerate possible
\n#fps = 30 # setting to 250 will request the maximum framerate possible
\n# \"raspividyuv\" is the command that provides camera frames in YUV format
\n# \"--output -\" specifies stdout as the output
\n# \"--timeout 0\" specifies continuous video
\n# \"--luma\" discards chroma channels, only luminance is sent through the pipeline
\n# see \"raspividyuv --help\" for more information on the parameters
\n#videoCmd = \"raspividyuv -w \"+str(w)+\" -h \"+str(h)+\" --output - --timeout 0 --framerate \"+str(fps)+\" --luma --nopreview\"
\n#videoCmd = \"raspividyuv -w \"+str(w)+\" -h \"+str(h)+\" --output - --timeout 0 --framerate \"+str(fps)+\" --nopreview\"
\n#videoCmd = \"raspivid -w \"+str(w)+\" -h \"+str(h)+\" --output - --timeout 0 --framerate \"+str(fps)+\" --nopreview\"
\nvideoCmd = \"raspividyuv -w 1920 -h 1080 --output - --timeout 0 --framerate \"+str(fps)+\" --nopreview\"
\nvideoCmd = videoCmd.split() # Popen requires that each parameter is a separate string
\ncameraProcess = sp.Popen(videoCmd, stdout=sp.PIPE) # start the camera
\natexit.register(cameraProcess.terminate) # this closes the camera process in case the python scripts exits unexpectedly
\n# wait for the first frame and discard it (only done to measure time more accurately)
\nrawStream = cameraProcess.stdout.read(bytesPerFrame)
\nprint(\"Recording...\")
\nstart_time = time.time()
\nwhile True:
\ncameraProcess.stdout.flush() # discard any frames that we were not able to process in time
\n# Parse the raw stream into a numpy array
\nframe = np.fromfile(cameraProcess.stdout, count=bytesPerFrame, dtype=np.uint8)
\nif frame.size != bytesPerFrame:
\nprint(\"Error: Camera stream closed unexpectedly\")
\nbreak
\nframe.shape = (h,w) # set the correct dimensions for the numpy array
\n# The frame can be processed here using any function in the OpenCV library.
\n# Full image processing will slow down the pipeline, so the requested FPS should be set accordingly.
\n#frame = cv2.Canny(frame, 50,150)
\n# For instance, in this example you can enable the Canny edge function above.
\n# You will see that the frame rate drops to ~35fps and video playback is erratic.
\n# If you then set fps = 30 at the beginning of the script, there will be enough cycle time between frames to provide accurate video.
\n# One optimization could be to work with a decimated (downscaled) version of the image: deci = frame[::2, ::2]
\nframes.append(frame) # save the frame (for the demo)
\n#del frame # free the allocated memory
\nN_frames += 1
\nif N_frames > max_frames: break
\nend_time = time.time()
\ncameraProcess.terminate() # stop the camera
\nelapsed_seconds = end_time-start_time
\nprint(\"Done! Result: \"+str(N_frames\/elapsed_seconds)+\" fps\")
\nprint(\"Writing frames to disk...\")
\nout = cv2.VideoWriter(\"slow_motion.avi\", cv2.VideoWriter_fourcc(*'MJPG'), 30, (w,h))
\nfor n in range(N_frames):
\n#cv2.imwrite(\"frame\"+str(n)+\".png\", frames[n]) # save frame as a PNG image
\nframe_rgb = cv2.cvtColor(frames[n],cv2.COLOR_GRAY2RGB) # video codec requires RGB image
\nout.write(frame_rgb)
\nout.release()
\nprint(\"Display frames with OpenCV...\")
\nfor frame in frames:
\ncv2.imshow(\"Slow Motion\", frame)
\ncv2.waitKey(1) # request maximum refresh rate
\ncv2.destroyAllWindows()<\/code><\/p>\n","protected":false},"excerpt":{"rendered":"Raspberry Pi\u306ePiCam\u306f\u3001\u3082\u306e\u51c4\u304f\u65e9\u3044\u30ad\u30e3\u30d7\u30c1\u30e3\u304c\u3067\u304d\u307e\u3059\u3002 640X480\u3067\u3001\u306a\u3093\u3068\u3001 946.946038832 fps\u304c\u3067\u307e\u3057\u305f\u3002\u4eca\u307e\u3067\u306b\u898b\u305f\u3053\u3068\u306e\u306a\u3044\u30d3\u30c7\u30aa\u30ad\u30e3\u30d7\u30c1\u30e3\u6027\u80fd\u3067\u3059\u3002\u305d\u306e\u65b9\u6cd5\u306f\u3001raspi…<\/p>\n
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