使用 Vision Builder AI 讀取 NI-1722 影像

Hello
我有一個視覺檢查的專案,早先是使用 IEEE 1394 camera
配合 Vision Builder AI 3.6 所寫成,最近更換為 NI-1722
Smart camera , 但更換後發現我只能使用 remote target 的模式
去存取 NI-1722 , 於是就將設定移轉至 NI-1722 ,但執行工作時
發現檢查速度非常的慢 。
請問有什麼方可以由NI-1722讀取影像,就像原有的 IEEE-1394 或
GigE 的模式,而非 Smart camera remote target 的模式,
並將工作設定於本地的 PC 內執行。
另外 我發現了Smart Camera 及 Vision Builder AI
的功能規格上有這一段的描逑,我應該如何設定才可達成
With Vision Builder AI, you can perform the following tasks:
Acquire and process images with any NI frame grabber
NI Compact Vision System, NI Embedded Vision System
NI Smart Cameras as well as GigE Vision, IEEE 1394 cameras
and USB DirectShow cameras
謝謝......

http://forums.ni.com/t5/Machine-Vision/Logging-an-​image-on-the-local-drive-using-Vision-Builder-2010​...
http://forums.ni.com/t5/Machine-Vision/Save-images​-on-NI-Smart-Camera-1742/m-p/1574514
Saving images to disk is discouraged on the smart cameras because of the number of writes to disk that can occur before the disk fails.
所以看起來在PC端把Smart Camera當成GigE相機,這樣的應用是不被建議的。
給您參考一下。

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    0x13169F6A - lvrt <unknown> + 0
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    0x13156B9A - lvrt <unknown> + 0
    0x1315956B - lvrt <unknown> + 0
    0x13165E4F - lvrt <unknown> + 0
    0x1316957B - lvrt <unknown> + 0
    0x13169F6A - lvrt <unknown> + 0
    0x13858167 - lvrt <unknown> + 0
    0x130A81DC - lvrt <unknown> + 0
    0x130A7FD3 - lvrt <unknown> + 0
    0x130A8249 - lvrt <unknown> + 0
    0x7C80B729 - kernel32 <unknown> + 0
    0x00000000 - multisim <unknown> + 0
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    0x138AFC29 - lvrt <unknown> + 0
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    0x13156B9A - lvrt <unknown> + 0
    0x1315956B - lvrt <unknown> + 0
    0x13165E4F - lvrt <unknown> + 0
    0x1316957B - lvrt <unknown> + 0
    0x13169F6A - lvrt <unknown> + 0
    0x13858167 - lvrt <unknown> + 0
    0x130A81DC - lvrt <unknown> + 0
    0x130A7FD3 - lvrt <unknown> + 0
    0x130A8249 - lvrt <unknown> + 0
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    0x00000000 - multisim <unknown> + 0
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    0x1315956B - lvrt <unknown> + 0
    0x13165E4F - lvrt <unknown> + 0
    0x1316957B - lvrt <unknown> + 0
    0x13169F6A - lvrt <unknown> + 0
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    0x130A81DC - lvrt <unknown> + 0
    0x130A7FD3 - lvrt <unknown> + 0
    0x130A8249 - lvrt <unknown> + 0
    0x7C80B729 - kernel32 <unknown> + 0
    0x00000000 - multisim <unknown> + 0

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    I want to know if that is possible ,and if it is how can I do so ?
    THANK YOU !
    Solved!
    Go to Solution.
    Attachments:
    aaaa.JPG ‏19 KB

    Hi layal,
    You are certainly on the right track with using the Vision Builder for Automated Inspection (VBAI). For an extensive outline of all the functions available to you, take a look at the VBAI manual here. First, you would typically want to define a reference coordinate system unless you can guarantee that the part will be located in the same position and orientation in the images. This is discussed on page 2-7 of the manual. Then, you could certainly compare the image, or certain portions in a specified region of interest (ROI) of the image to a template and detect the differences, check for gaps and part widths, locate edges relative to the coordinate system, etc. All the features are outlined in the manual in the context of some examples. I highly suggest that you take a look through the manual and also consider evaluating the VBAI software for 30 days if you do not have it already. You can access the download for the evaluation from the 1st link I posted. If you have more specific questions on the inspection, or how to carry it out, please provide more details concerning the pass/fail conditions for your part.
    Also, please bear in mind that if you run VBAI on a regular PC running an OS such as windows, the performance will not truly be real-time. To achieve deterministic performance, you would have to deploy this inspection to a real-time target such as the NI EVS, Smart Camera or a PC running LabVIEW Real-Time as the OS. Hope this helps!

  • Vision Builder Crashes Labview

    I have an application where I need to acquire and inspect many high resolution images 3Mp at high throughput. 
    I'm using:
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    NI-Imaq 4.1
    Imaqdx 3.2
    Vision Builder AI 3.6
    ISG 3Mp Camera through Startech 1394a PCI card
    In order to meet the cycle rate, I'm trying to multi-thread the application by having one thread that acquires images and enqueues them into another thread that saves them to the hard drive then runs the VBAI inspection.  The VBAI inspection then uses the "simulate acquisition" step inorder to load the image from the hard drive and make the appropriate measurements.  I've run the application and monitored the processor usage, and the processor seems to stay within 0-80%.  However, my application will crash intermittantly. 
    I've been able to repeat the behavior pretty reliably if I activate/toggle a ring control on my front panel while the cycle is running, and I can't do so if the VBAI thread is not running.
    I understand that this is could be a difficult problem to help debug remotely.  I'm wondering if there is anyone with similar experience, or some better way for me to creat a high throughput machine vision app with VBAI.
    Thanks,
    Ryan 

    Dear Ryan,
    You are right, this is difficult to debug remotely, but I can make a suggestion or two. Perhaps you've taken care of these, perhaps not...
    One potential downfall with this setup is running into a race condition. If you don't establish data dependency, and make sure that you save and close a particular image before trying to open back up again with VBAI, you could cause the behavior described. Race conditions would be even more of a concern if you were using a certain number of files as an image buffer, and then recycling through them. 
    What in this ring control? What does the ring control do?
    Have you tried generating LabVIEW code from your VBAI inspection, and then encapsulating the VBAI code in a subVI, and just passing your images into that instead of saving them to disk? I would suggest doing this to see if you still experienced the crashes when you are only working in LabVIEW, and without saving and opening images from disk.
    Let me know how things go; I hope the above suggestions provide some help. 
    Best Regards,
    ~Nate 

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