‎Regular micro SD card

← Older revision Revision as of 20:11, 18 July 2019 Line 29: Line 29:  Requirements: Requirements:  * μUSB-to-USB cable * μUSB-to-USB cable −* Linux: compile [https://sourceforge.net/p/elphel/cp210x_gpio/ci/master/tree/ cp210x driver]+* Linux: compile [https://git.elphel.com/Elphel/cp210x_gpio cp210x driver]  Instructions: Instructions:  * Power on * Power on Oleg

‎Setup (guide)

← Older revision Revision as of 23:32, 2 July 2019 (17 intermediate revisions by the same user not shown)Line 1: Line 1:  ==Requirements== ==Requirements== −* Kubuntu 16.04.4 LTS+* Kubuntu 16.04 LTS  ==Setup (guide)== ==Setup (guide)==  Just follow: Just follow: −* [http://www.python36.com/install-tensorflow141-gpu/ '''this guide'''] (Ubuntu 16.04 64-bit, CUDA 9.1, cuDNN 7.1.2, python3) or+* The [[Tensorflow_with_gpu#Walkthrough_for_CUDA_10.1_.2820190602.29|'''walkthrough''']] in the bottom is for CUDA 10.1, cuDNN 7.6.1, python3 −* this [http://www.python36.com/how-to-install-tensorflow-gpu-with-cuda-9-2-for-python-on-ubuntu/ '''newer one'''] (Ubuntu 16.04 64-bit, CUDA 9.2, cuDNN 7.1.4, python3)+* [http://www.python36.com/how-to-install-tensorflow-gpu-with-cuda-9-2-for-python-on-ubuntu/ '''This guide'''] (Ubuntu 16.04 64-bit, CUDA 9.2, cuDNN 7.1.4, python3)  +* [http://www.python36.com/install-tensorflow141-gpu/ '''This guide'''] (Ubuntu 16.04 64-bit, CUDA 9.1, cuDNN 7.1.2, python3)     ==Setup (some details)== ==Setup (some details)== Line 130: Line 131:    # Solution:   # Solution:    <b>~$ sudo pip3 install setuptools --upgrade</b></font>   <b>~$ sudo pip3 install setuptools --upgrade</b></font>  +  +==Walkthrough for CUDA 10.1 (20190602)==  +  +===Install CUDA===  +* In this [https://www.tensorflow.org/install/gpu guide] there's a [https://developer.nvidia.com/cuda-toolkit-archive link to CUDA toolkit].  +** That toolkit (CUDA Toolkit 10.1 update1 (May 2019)) also updated the system driver to 418.67  +** Reboot  +===Install cuDNN===  +* Have to have an account with NVIDIA - downloaded [https://developer.nvidia.com/rdp/cudnn-download#a-collapse761-101 cuDNN v7.6.1 (June 24, 2019), for CUDA 10.1]  +  +===Option 1: installing tensorflow from source===  +Basically, [https://www.tensorflow.org/install/source '''this guide'''], some key notes:  +* [https://www.tensorflow.org/install/source#install_bazel Install bazel] - version 0.25.2 (newer will not work)  +* To build, read [https://www.tensorflow.org/install/source#download_the_tensorflow_source_code this link]:  + git clone https://github.com/tensorflow/tensorflow.git  + cd tensorflow  + git checkout r1.14  + ./configure  +   + bazel build --config=opt --config=cuda //tensorflow/tools/pip_package:build_pip_package  + # 4-5 hours later  + ./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg  + sudo pip3 install /tmp/tensorflow_pkg/tensorflow-[Tab]  +  +* Testing:  + ~$ python3  + >>> import tensorflow as tf  + >>> hello = tf.constant('Hello, World!')                                                                                                                                                                             + >>> sess = tf.Session()  +  +===Option 2: using docker===  +Follow [https://www.tensorflow.org/install/docker '''this guide''']. Key notes:  +* Tensorflow docker image requires nvidia docker image, nvidia docker image requires ''apt install nvidia-docker2'', ''nvidia-docker2'' requires ''apt install docker-ce'':  + - https://github.com/NVIDIA/nvidia-docker  + - https://docs.docker.com/install/linux/docker-ce/ubuntu/  +  +* Test run:  + # Test 1: GPU support inside container:  + sudo docker run --runtime=nvidia --rm nvidia/cuda:10.1-base nvidia-smi  + # Test 2: Test all together  + sudo docker pull tensorflow/tensorflow:latest-gpu-py3-jupyter  + sudo docker run --runtime=nvidia -it --rm tensorflow/tensorflow:latest-gpu-py3-jupyter python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"  + # Test 3: Run a local script (and include a local dir) in contatiner:  + https://www.tensorflow.org/install/docker Oleg

‎Option 2: using docker

← Older revision Revision as of 23:13, 2 July 2019 (9 intermediate revisions by the same user not shown)Line 130: Line 130:    # Solution:   # Solution:    <b>~$ sudo pip3 install setuptools --upgrade</b></font>   <b>~$ sudo pip3 install setuptools --upgrade</b></font>  +  +==Walkthrough for CUDA 10.1 (20190602)==  +  +===Install CUDA===  +* In this [https://www.tensorflow.org/install/gpu guide] there's a [https://developer.nvidia.com/cuda-toolkit-archive link to CUDA toolkit].  +** That toolkit (CUDA Toolkit 10.1 update1 (May 2019)) also updated the system driver to 418.67  +** Reboot  +===Install cuDNN===  +* Have to have an account with NVIDIA - downloaded [https://developer.nvidia.com/rdp/cudnn-download#a-collapse761-101 cuDNN v7.6.1 (June 24, 2019), for CUDA 10.1]  +  +===Option 1: installing tensorflow from source===  +Basically, [https://www.tensorflow.org/install/source '''this guide'''], some key notes:  +* [https://www.tensorflow.org/install/source#install_bazel Install bazel] - version 0.25.2 (newer will not work)  +* To build, read [https://www.tensorflow.org/install/source#download_the_tensorflow_source_code this link]:  + git clone https://github.com/tensorflow/tensorflow.git  + cd tensorflow  + git checkout r1.14  + ./configure  +  + bazel build --config=opt --config=cuda //tensorflow/tools/pip_package:build_pip_package  + # 4-5 hours later  + ./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg  + sudo pip3 install /tmp/tensorflow_pkg/tensorflow-[Tab]  +  +===Option 2: using docker===  +Follow [https://www.tensorflow.org/install/docker '''this guide''']. Key notes:  +* Tensorflow docker image requires nvidia docker image, nvidia docker image requires ''apt install nvidia-docker2'', ''nvidia-docker2'' requires ''apt install docker-ce'':  + - https://github.com/NVIDIA/nvidia-docker  + - https://docs.docker.com/install/linux/docker-ce/ubuntu/  +  +* Test run:  + # Test 1: GPU support inside container:  + sudo docker run --runtime=nvidia --rm nvidia/cuda:10.1-base nvidia-smi  + # Test 2: Test all together  + sudo docker pull tensorflow/tensorflow:latest-gpu-py3-jupyter  + sudo docker run --runtime=nvidia -it --rm tensorflow/tensorflow:latest-gpu-py3-jupyter python -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"  + # Test 3: Run a local script (and include a local dir) in contatiner:  + https://www.tensorflow.org/install/docker Oleg

← Older revision Revision as of 22:04, 2 July 2019 (2 intermediate revisions by the same user not shown)Line 130: Line 130:    # Solution:   # Solution:    <b>~$ sudo pip3 install setuptools --upgrade</b></font>   <b>~$ sudo pip3 install setuptools --upgrade</b></font>  +  +==Walkthrough for CUDA 10.1==  +  +===CUDA===  +* In this [https://www.tensorflow.org/install/gpu guide] there's a [https://developer.nvidia.com/cuda-toolkit-archive link to CUDA toolkit].  +** That toolkit (CUDA Toolkit 10.1 update1 (May 2019)) also updated the system driver to 418.67  +** Reboot  +===cuDNN===  +* Have to have an account with NVIDIA - downloaded [https://developer.nvidia.com/rdp/cudnn-download#a-collapse761-101 cuDNN v7.6.1 (June 24, 2019), for CUDA 10.1] Oleg

‎103992

← Older revision Revision as of 19:01, 11 June 2019 Line 8: Line 8:     Mechanical CAD files and 3D model: [[Elphel_camera_parts_0393-00#0393-00-992_-_103992_rev_0_Adapter_for_FLIR_Lepton-3_160x120_LWIR_sensor_module | 0393-00-992]] Mechanical CAD files and 3D model: [[Elphel_camera_parts_0393-00#0393-00-992_-_103992_rev_0_Adapter_for_FLIR_Lepton-3_160x120_LWIR_sensor_module | 0393-00-992]]  +  +{|  +|valign='top'|[[Image:103992_top.jpeg|thumb|200px|top view, sensor module installed]]  +|valign='top'|[[Image:103992_top_2.jpeg|thumb|200px|top view, socket only]]  +|valign='top'|[[Image:103992_bottom.jpeg|thumb|200px|bottom view]]  +|} Oleg

Oleg uploaded File:103992 bottom.jpeg

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== Licensing ==
{{CC }} Oleg

Oleg uploaded File:103992 top 2.jpeg

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== Licensing ==
{{CC }} Oleg

Oleg uploaded File:103992 top.jpeg

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== Licensing ==
{{CC }} Oleg

‎0353-99-25 - Screw, M2, Socket Head, Stainless steel 18-8, l=8mm

← Older revision Revision as of 23:39, 13 May 2019 Line 134: Line 134:     === 0353-99-25 - Screw, M2, Socket Head, Stainless steel 18-8, l=8mm === === 0353-99-25 - Screw, M2, Socket Head, Stainless steel 18-8, l=8mm === −McMaster p/n 91292A008+McMaster p/n 91292A008, new p/n 91292A832  {{Cad4|0353-99-25}} {{Cad4|0353-99-25}}     ---- ---- Oleg

← Older revision Revision as of 19:26, 6 May 2019 Line 1: Line 1:  ==<font color="blue">Description</font>== ==<font color="blue">Description</font>== −10389 board is required (and possible 103891).+[[10389]] board is required (and possibly [[103891]]).     Use cases: Use cases: Andrey.filippov

‎External trigger receive (external source only)

← Older revision Revision as of 17:55, 2 May 2019 Line 69: Line 69:  ===External trigger receive (external source only)=== ===External trigger receive (external source only)===  The sync cable wires can be looped or not - does not matter. The sync cable wires can be looped or not - does not matter. −  http://192.168.0.9/parsedit.php?sensor_port=0&immediate&TRIG_CONDITION=0x95555&TRIG_OUT=0x0&TRIG_PERIOD=100000000&TRIG=4+  http://192.168.0.9/parsedit.php?sensor_port=0&immediate&TRIG_CONDITION=0x95555&TRIG_OUT=0x66555&TRIG_PERIOD=100000000&TRIG=4  * at the same time the fpga generator outputs a 1 fps signal - if the sync cable wires are properly connected the camera can be triggered from this 'external' signal * at the same time the fpga generator outputs a 1 fps signal - if the sync cable wires are properly connected the camera can be triggered from this 'external' signal    Oleg

← Older revision Revision as of 06:00, 26 April 2019 Line 8: Line 8:  {{Cad4a|0393-28-02}} {{Cad4a|0393-28-02}}  ---- ----  +=== 0393-28-021 ===  +{{Cad4a|0393-28-021}}  +----  +  +=== 0393-28-022 ===  +{{Cad4a|0393-28-022}}  +----  +     === 0393-28-03 === === 0393-28-03 === Line 15: Line 23:  === 0393-28-04 === === 0393-28-04 ===  {{Cad4a|0393-28-04}} {{Cad4a|0393-28-04}}  +----  +  +=== 0393-28-041 ===  +{{Cad4a|0393-28-041}}  +----  +  +=== 0393-28-042 ===  +{{Cad4a|0393-28-042}}  ---- ----    Andrey.filippov

‎pre (editing files on the boot SD card)

← Older revision Revision as of 20:11, 23 April 2019 Line 7: Line 7:  * Remove 10389 board if installed (otherwise will have to rewrite eeprom) * Remove 10389 board if installed (otherwise will have to rewrite eeprom)  * To load bitstream for MT9F002 appropriate changes need to be made to: * To load bitstream for MT9F002 appropriate changes need to be made to: −** device tree+** (not necessary, can skip) device tree    <font size=2>set sensors to '''mt9f002''' in ''elphel393-detect_sensors,sensors'' entry</font>   <font size=2>set sensors to '''mt9f002''' in ''elphel393-detect_sensors,sensors'' entry</font>  ** /etc/elphel393/default_10389.xml for setup w/o 10389 or 10389's eeprom otherwise write '''MT9F002''' as application ** /etc/elphel393/default_10389.xml for setup w/o 10389 or 10389's eeprom otherwise write '''MT9F002''' as application Oleg

‎0393-28-08

← Older revision Revision as of 16:03, 12 April 2019 (One intermediate revision by the same user not shown)Line 1: Line 1:  [[Elphel_camera_parts_0393|Elphel NC393 series camera parts]] [[Elphel_camera_parts_0393|Elphel NC393 series camera parts]]    −=== 0393-27-01f - C/CS SFE adapter ===+=== 0393-28-01 === −{{Cad4c|0393-27-01f}}+{{Cad4a|0393-28-01}}  +----  +   +=== 0393-28-02 ===  +{{Cad4a|0393-28-02}}  +----  +   +=== 0393-28-03 ===  +{{Cad4a|0393-28-03}}  +----  +   +=== 0393-28-04 ===  +{{Cad4a|0393-28-04}}  +----  +   +=== 0393-28-05 ===  +{{Cad4a|0393-28-05}}  +----  +   +=== 0393-28-06 ===  +{{Cad4a|0393-28-06}}  +----  +   +=== 0393-28-07 ===  +{{Cad4a|0393-28-07}}  +----  +   +=== 0393-28-08 ===  +{{Cad4a|0393-28-08}}  +----  +=== 0393-28-09 ===  +{{Cad4a|0393-28-09}}  ---- ---- Andrey.filippov

← Older revision Revision as of 09:18, 12 April 2019 Line 1: Line 1:  [[Elphel_camera_parts_0393|Elphel NC393 series camera parts]] [[Elphel_camera_parts_0393|Elphel NC393 series camera parts]]    −=== 0393-27-01f - C/CS SFE adapter ===+=== 0393-28-01 === −{{Cad4c|0393-27-01f}}+{{Cad4a|0393-28-01}}  +----  +   +=== 0393-28-02 ===  +{{Cad4a|0393-28-02}}  +----  +   +=== 0393-28-03 ===  +{{Cad4a|0393-28-03}}  +----  +   +=== 0393-28-04 ===  +{{Cad4a|0393-28-04}}  +----  +   +=== 0393-28-05 ===  +{{Cad4a|0393-28-05}}  +----  +   +=== 0393-28-06 ===  +{{Cad4a|0393-28-06}}  +----  +   +=== 0393-28-07 ===  +{{Cad4a|0393-28-07}}  +----  +   +=== 0393-28-08 ===  +{{Cad4a|0393-28-08}}  ---- ---- Andrey.filippov

Created page with "Elphel NC393 series camera parts === 0393-27-01f - C/CS SFE adapter === {{Cad4c|0393-27-01f}} ----"

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[[Elphel_camera_parts_0393|Elphel NC393 series camera parts]]

=== 0393-27-01f - C/CS SFE adapter ===
{{Cad4c|0393-27-01f}}
---- Andrey.filippov

‎Additional manual setup for linux-elphel.project

← Older revision Revision as of 21:25, 4 April 2019 (3 intermediate revisions by the same user not shown)Line 75: Line 75:     After creating a new workspace with '''setup_eclipse.py''' it can be opened with Eclipse, the projects you plan to use have to be indexed (right-click on the project in the Navigator ⇒ Index ⇒ Rebuild. After creating a new workspace with '''setup_eclipse.py''' it can be opened with Eclipse, the projects you plan to use have to be indexed (right-click on the project in the Navigator ⇒ Index ⇒ Rebuild.  +=== Additional manual setup for linux-elphel.project===  +[[File:Eclipse_cdt.png|right|300px|frame|Adding ''linux/include/generated/autoconf.h'' entry to ''linux-elphel'' project properties]]  +Until we found a way how to set it automatically, the linux/include/generated/autoconf.h file has to be added to the project properties, as shown in the screenshot.     ==Initializing Eclipse Workspace for Existing (Cloned) Verilog Projects== ==Initializing Eclipse Workspace for Existing (Cloned) Verilog Projects== Andrey.filippov

Andrey.filippov uploaded File:Eclipse cdt.png

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== Licensing ==
{{GNU FDLv1.3 }} Andrey.filippov

‎Setup

← Older revision Revision as of 23:54, 28 March 2019 Line 87: Line 87:    . ./oe-init-build-env   . ./oe-init-build-env    bitbake u-boot device-tree linux-xlnx core-image-elphel393   bitbake u-boot device-tree linux-xlnx core-image-elphel393 −''Temporary: linux-xlnx in Rocko depends on branch 'lwir' for x393. Change in projects.json line 42 from 'master' to 'lwir'.''+<!--''Temporary: linux-xlnx in Rocko depends on branch 'lwir' for x393. Change in projects.json line 42 from 'master' to 'lwir'.''-->  </font> </font>    Andrey.filippov

‎Requirements

← Older revision Revision as of 22:59, 28 March 2019 (One intermediate revision by the same user not shown)Line 11: Line 11:  * Building embedded Linux image for Zynq ARMv7 platform - Elphel 10393 board * Building embedded Linux image for Zynq ARMv7 platform - Elphel 10393 board  * Yocto Poky revision = 2.6 (Thud) * Yocto Poky revision = 2.6 (Thud) −* <s>Yocto Poky revision = 2.4 (Rocko)</s>+* Yocto Poky revision = 2.4 (Rocko)  * <s>Yocto Poky revision = 2.0 (Jethro)</s> * <s>Yocto Poky revision = 2.0 (Jethro)</s>    Line 29: Line 29:     ==<font color="blue">Requirements</font>== ==<font color="blue">Requirements</font>==  +* Kubuntu 16.04 x64 (as of Dec 2018) for Poky 2.4 Rocko  * Kubuntu 18.04 x64 (as of Dec 2018) * Kubuntu 18.04 x64 (as of Dec 2018)  * For Poky 2.6 Thud see [http://www.yoctoproject.org/docs/2.6/mega-manual/mega-manual.html Yocto Project Poky 2.6 mega-manual] * For Poky 2.6 Thud see [http://www.yoctoproject.org/docs/2.6/mega-manual/mega-manual.html Yocto Project Poky 2.6 mega-manual] Oleg