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Found 6 results

  1. Hi I am new to this forum. I am trying to use python-periphery library to use the pins on the board. if I do : from periphery import GPIO gpio3 = GPIO(3,"in") I get the following error: Traceback (most recent call last): File "/usr/local/lib/python3.7/dist-packages/periphery/gpio.py", line 1017, in _open with open("/sys/class/gpio/export", "w") as f_export: PermissionError: [Errno 13] Permission denied: '/sys/class/gpio/export' During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/linaro/Desktop/temp_hum.py", line 7, in <module> gpio3 = GPIO(3,"in") File "/usr/local/lib/python3.7/dist-packages/periphery/gpio.py", line 999, in __init__ self._open(line, direction) File "/usr/local/lib/python3.7/dist-packages/periphery/gpio.py", line 1020, in _open raise GPIOError(e.errno, "Exporting GPIO: " + e.strerror) periphery.gpio.GPIOError: [Errno 13] Exporting GPIO: Permission denied Any Idea how to solve this?
  2. Hi All, I understand that in order to run an AI model on the NPU I have to convert it to RKNN, but whenever I do that my model (tf-lite) looses accuracy up to 15-20%. I have checked Rockchip_Trouble_Shooting_RKNN_Toolkit_V1.7.3_EN.pdf document in section 8.1 and it says that this issue might be related to setting mean_values/std_values incorrectly. then I found the below section in Rockchip_Trouble_Shooting_RKNN_Toolkit_V1.3.2_EN.pdf on how to set mean_values/std_values, but still don't quite understand it: I have 3 questions: 1) I am doing a binary classification and my Input data is (240,240,3) for training, would this be my (Cin0, Cin1,Cin2) ? 2) how do I set the Scale parameter ? 3)how do I get (Cout0,Cout1, Cout2) ? thank you, I would really appreciate your help
  3. Two webcams were connected in the tinker edge. `cv2.open()` works well for two webcams, but only one webcam can be read. How do I `cv2.read()` two webcams at the same time?
  4. Hi, We have a Program ready for testing build with Node-red, we decide to work with tinker edge R. and we found the following discussion in asus Tinker Board Forum : https://tinker-board.asus.com/forum/index.php?/topic/15110-how-to-use-do-on-node-red-tinkeros-gpio/&tab=comments#comment-15662 We did same steps as CyberT did , downlowded nrgpio.sh suggested by Mr yi-hsin_hung, and replaced in the eadge-R in specific folder, but unfortunately it doesn't work. Please can you help to resolve this problem . Thanks in advance.
  5. Yearly event in UK, the Engineering Design Show (EDS) provides an access to latest products, services, and innovations to the sectors of engineering, electronics and embedded design. Our partner, Solid State Supplies (SSSL), is having a booth at the exhibition, featuring workshops and product demos showcasing the technology and applications ahead of time. Using ASUS Tinker Board 2 & Tinker Edge R, ALPR and Face Recognition Dev kit provides unparalleled graphics acceleration and processor capabilities for AI application. Kindly invite you to join and stay tuned for the coming event! Event Name : The Engineering Design Show 2021(EDS) Date/Time: Date(s) - 19/10/2021 - 20/10/2021 10:00 am - 4:00 pm Location: Ricoh Arena (Address :Judds Lane , Coventry, CV6 6GE , United Kingdom ) Booth number : Stand K2 - Solid State Supplies Link: The Engineering Design Show 2021 - Stand K2 - Solid State Supplies (sssltd.com)
  6. Hi team, I’ve recently bought an Asus Tinker Edge R to reply machine learning model. After few research and reading and I didn’t find much documentation on how to run object detection model on Tinker Edge R with an external camera. I’ve tried to rknn-toolkit too. I also want to use the NPU & GPU capabilities of the Tinker Edge R to experiment and see if it’s possible to use this device for my ML deployment or not. I’ve tested tflite on thinker Edge R I achieved like 3FPS which is not possible to use or deploy any model with this FPS. Could please share some documentations on how to run object detection model with Tinker Edge R. I also lost while trying to convert the model into rknn. Thank You.
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