I was trying to implement an E-Ink solution using IMX7D. Unfortunately I only had a IMXEBOOKDC3 available, not the DC4 shown on the IMX7D E-Ink tutorials. After a couple of tries I found the right way of connecting the expansion board and the the definition of the arguments on U-boot to make the IMX7D and DC3 work together.  I logged these considerations on the blog post below: http://bit.ly/IMX7D_IMXEBOOKDC3   Andres

It is one mandatory patch if you are in the case: The chip you are using is imx6sx TO1.3 and newer, and use the kobs-ng to flash your image to the Nand memory chip. If you are using MFG, you also need rebuild the kobs-ng, and update the binary into your MFG tool.  The patch have been integrated into the default release yocto_4.1.15, but if you are using the older version release before yocto_4.1.15, please make sure you have integrated the modification when you need to use kobs-ng to flash the image to Nand memory chip. commit 5ecf08703da489a3bd317341f630870a3d07dab9 Author: Han Xu <[email protected]> Date:   Thu Jan 28 14:40:14 2016 -0600     MMT-105: change the i.mx6sx revision check change the i.mx6sx revision check since v1.3 uses v1.2 boot config as well.     Signed-off-by: Han Xu <[email protected]>     (cherry picked from commit 1dac0c14d1e2016c2fa804f6628543d8d238c680) diff --git a/src/plat_boot_config.c b/src/plat_boot_config.c index 461675a..e1ef6f3 100644 --- a/src/plat_boot_config.c +++ b/src/plat_boot_config.c @@ -1,5 +1,5 @@ /* -* Copyright (C) 2010-2015 Freescale Semiconductor, Inc. All Rights Reserved. +* Copyright (C) 2010-2016 Freescale Semiconductor, Inc. All Rights Reserved. */ /* @@ -256,10 +256,12 @@ int discover_boot_rom_version(void)                                         }                                         fgets(line_buffer, sizeof(line_buffer), revision);                                         if (!strncmp(line_buffer, "1.0", strlen("1.0")) || -                                                       !strncmp(line_buffer, "1.1", strlen("1.1"))) +                                                       !strncmp(line_buffer, "1.1", strlen("1.1"))) {                                                 plat_config_data = &mx6sx_boot_config; -                                       if (!strncmp(line_buffer, "1.2", strlen("1.2"))) +                                       /* all other revisions should use the latest boot config */ +                                       } else {                                                 plat_config_data = &mx6sx_to_1_2_boot_config; +                                       }                                 }                                 if (!strncmp(line_buffer, plat_imx6ul, strlen(plat_imx6ul))) How to apply it to older version quickly:  Apply the patch and rebuild the kobs-ng in yocto_3.14_x environment: bitbake -c compile -v -f imx-kobs cd tmp/work/cortexa9hf-vfp-neon-poky-linux-gnueabi/imx-kobs/5.0-r0/imx-kobs-5.0 git apply yocto_3_14_x.patch bitbake -c compile -v -f imx-kobs you can find the new binary “kobs-ng” under “tmp/work/cortexa9hf-vfp-neon-poky-linux-gnueabi/imx-kobs/5.0-r0/build/src” Apply the patch and rebuild the kobs-ng in yocto_3.10_53 environment: . ./setup-environment build bitbake -c compile -v -f imx-kobs cd tmp/work/cortexa9hf-vfp-neon-poky-linux-gnueabi/imx-kobs/3.10.53-1.1.0-r0/imx-kobs-3.10.53-1.1.0 git apply yocto_3_10_53patch bitbake -c compile -v -f imx-kobs you can find t he new binary “kobs-ng” under tmp/work/cortexa9hf-vfp-neon-poky-linux-gnueabi/imx-kobs/3.10.53-1.1.0-r0/imx-kobs-3.10.53-1.1.0/src As one alternation method, you also can download the whole imx-kobs-5.4 package which yocto_4.1.15 is using to build. wget http://www.freescale.com/lgfiles/NMG/MAD/YOCTO//imx-kobs-5.4.tar.gz

Question: LVDS in split mode (dual lvds) is used. In this configuration, only LVDS0_CLK is used. What is the suggestion for the LVDS1_CLK?  The HW user guide says that if this is unused, then to leave it floating.  Would we also suggest the same for this case or would termination be more appropriate?  Or is there some possible way to gate this clock?  (if so, it isn't obvious in the RM) Answer: According to the MX6 Developer's Guide, any unused LVDS pins should be left floating, so the LVDS1_CLK pair, in this case should be left floating. In order to minimize any potential EMC, the lands for those balls should not have any additional traces leading away. To add a bit more information, the customer ran some tests and found that the clock gate bits for the LVDS1 are essentially ignored in Dual mode.  The only way to disable it is if they are both disabled which is not helpful in this case.  It seems that the Dual mode setting overrides the CG.

The Android O8.0.0_1.4.0 for i.MX 7ULP RFP(GA) release is now available on IMX_SW web page. Overview -> BSP Updates and Releases -> Android O8.1.0 for i.MX 7ULP GA.   Files available:   # Name Description 1 android_o8.1.0_1.4.0_7ulp-ga_docs.tar.gz Android O8.1.0_1.4.0 for 7ULP GA Documentation 2 imx-o8.1.0_1.4.0_7ulp-ga.tar.gz i.MX Android proprietary source code for Android O8.1.0_1.4.0_7ULP_GA 3 android_o8.1.0_1.4.0_7ulp-ga_image_7ulpevk.tar.gz Prebuilt images with NXP extended features for the i.MX7ULP EVK board 4 android_o8.1.0_1.4.0_7ulp-ga_tools.tar.gz Manufacturing Toolkit and VivanteVTK for Android O8.1.0_1.4.0_7ULP_GA 5 fsl_aacp_dec_O8.1.0-7ULP_GA.tar.gz AAC Plus Codec for  O8.1.0_1.4.0_7ULP_GA   Target boards: i.MX 7ULP EVK   Features and Known issues For features and known issues, please consult the Release Notes in detail.#

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目录 1 创建 i.MX8QXP Linux 5.4.24 板级开发包编译环境 ..... 3 1.1 下载板级开发包 ....................................................... 3 1.2 创建yocto编译环境: ................................................. 4 1.3 独立编译 ................................................................. 9 2 Device Tree .............................................................. 16 2.1 恩智浦的device Tree结构 ..................................... 16 2.2 device Tree的由来(no updates) ............................ 19 2.3 device Tree的基础与语法(no updates) ................. 22 2.4 device Tree的代码分析(no updates) ..................... 44 3 恩智浦i.MX8XBSP 包文件目录结构 .......................... 77 4 恩智浦i.MX8XBSP的编译(no updates) ..................... 79 4.1 需要编译哪些文件 ................................................. 79 4.2 如何编译这些文件 ................................................. 80 4.3 如何链接为目标文件及链接顺序 ............................ 81 4.4 kernel Kconfig ....................................................... 83 5 恩智浦BSP的内核初始化过程(no updates) .............. 83 5.1 初始化的汇编代码 ................................................. 85 5.2 初始化的C代码 ...................................................... 89 5.3 init_machine........................................................ 102 6 恩智浦BSP的内核定制 ........................................... 105 6.1 DDR修改 ............................................................. 106 6.2 IO管脚配置与Pinctrl驱动 ..................................... 107 6.3 新板bringup......................................................... 123 6.4 更改调试串口 ...................................................... 132 6.5 uSDHC设备定制(eMMC flash,SDcard, SDIOcard)137 6.6 LVDS LCD 驱动定制 ........................................... 147 6.7 LVDS LDB SerDas驱动支持 ............................... 150 6.8 MiPi DSI SerDas驱动支持 .................................. 156 6.9 V4L2框架汽车级高清摄像头/桥驱动：数字/模拟 . 160 6.10 GPIO_Key 驱动定制 .......................................... 177 6.11 GPIO_LED 驱动定制 ......................................... 181 6.12 Fuse nvram驱动 .................................................. 184 6.13 SPI与SPI Slave驱动 ........................................... 185 6.14 USB 3.0 TypeC 改成 USB 3.0 TypeA(未验证) .... 193 6.15 汽车级以太网驱动定制 ........................................ 193 6.16 i.MX8DX MEK支持 .............................................. 212 6.17 i.MX8DXP MEK支持 ........................................... 212 6.18 NAND Flash支持与烧录 ...................................... 213

This is a How-To documentation for OpenCL on i.MX6 using LTIB, there are all necessary steps and sample code to create,  build and run a HelloWorld application.

http://freescale.eefocus.com/bbs/article_175_179914.html Freescale i.mx53 i.mx6x series solution to speed up the progress of your product 深圳市优创科技有限公司 Josephwang 王伟 深圳市南山区高新技术产业园南区创维大厦C15 Tel:0755-26017990  13128865181        Mail:[email protected]        QQ:[email protected]

Important: If you have any questions or would like to report any issues with the DDR tools or supporting documents please create a support ticket in the i.MX community. Please note that any private messages or direct emails are not monitored and will not receive a response.   This is a detailed programming aid for the registers associated with MMDC initialization. The last sheet formats the register settings for use with ARM RealView ICE. It can also be used with the windows executable for the DDR Stress Test. This programming aid was used for internal NXP validation boards.

logcat Logcat is the most powerful debug tool for Android. Logcat is to Android what the dmesg is to kernel. It shows messages logs from system and applications. logcat can be used directly on board console or via adb. $ logcat directly on board console. It gives the complete log message list and waits for any new log message. $ logcat & board console. It gives log list and run in background. Any new log message will be displayed. # adb logcat Using adb you can get log messages through Ethernet or USB connection. $ logcat -d > logcat.txt it sends log messages to logcat.txt file and exits. $ logcat *:W it filters expression displays all log messages with priority level "warning" and higher, on all tags * * http://developer.android.com/guide/developing/debugging/debugging-log.html

i.MX6 4.0.0 BSP release doesn't support ASRC_P2P function. This patch provides the reference codes to enable ASRC_P2P function for SSI. It can convert input sample rate to 44.1K_16bit/44.1K_24bit and 48K_16bit/48K_24bit. You can modify the configurations in the Board file. By the way, the SSI controler works at slave mode. Known limitations for the patch: -- The SDMA doesn't support SSI Dual FIFO when using ASRC_P2P function. -- From the waveform, the converted 24bit data have some abnormal data(values between 0 and 1) , but can't hear any abnormal sound from headphone. One suggestion is given under https://community.freescale.com/docs/DOC-95340

When streaming, if you want to play a streaming URL, it can be inconvenient if the browser cannot recognize the URL as a media stream and downloads the content rather than using Gallery to play it. To create this kind of media streaming, you need to write an apk to use VideoView to play the URL/media stream from the console. Here is the command of how to play a media file or network stream from console. Gingerbread am start -n com.cooliris.media/com.cooliris.media.MovieView -d "<URL>"       The URL can be file position or network stream URL, such as: you can play a local file by: am start -n com.cooliris.media/com.cooliris.media.MovieView -d "/mnt/sdcard/test.mp4" You can also play a http stream by: am start -n com.cooliris.media/com.cooliris.media.MovieView -d "http://v.iask.com/v_play_ipad.php?vid=76710932" Or play a rtsp stream by: am start -n com.cooliris.media/com.cooliris.media.MovieView -d "rtsp://10.0.2.1:554/stream" ICS am start -n com.android.gallery3d/com.android.gallery3d.app.MovieActivity -d "<URL>"        The URL has the same definition of Gingerbread.

This tutorial teaches how to program bootloader on a SD Card using ATK. To program kernel and root file system to the SD card, please follow this i.MX35 PDK Linux Booting SD    ATK (Advanced Toolkit)       ATK (Advanced Toolkit) is a Windows software for programming the flash memory of i.MX boards. It can be downloaded here.     Using ATK       This section will describe the procedure to erase and program the bootloader in the SD Card.       1. Connect a serial cable between PC and i.MX board.       2. Set the switches:       Debug Board: SW9 -> 0         SW10 -> 0         Personality Board: SW1 and SW2 (All bits) -> 0     3. Run ATK going to Start -> Programs -> AdvancedToolKit -> AdvancedToolKit           Set the options:       i.MX CPU -> i.MX35_TO2       Device memory -> DDR2;       Communication Channel -> Serial Port (Usually COM1)     4. Click Flash Tools to erase, program, or dump the the memory and click GO     Erasing     1. To erase SD Card, select the parameters as below: Select MMC/SD as "Flash Model".     Select Erase on "Operation Type". 2. Turn on the board and press Erase.     3. ATK shows a message: "Flash erase successful!" when card is erased   Programming     Next, program the bootloader image into the memory card following the steps below:     1. Select the parameters: The bootloader binary image file can be found into your Board Support Package (click here to download) Select Program on "Operation Type".     Address: 0x00000000     File: "mx35_3stack_redboot_mmc.bin" (or similar name that indicates a MMC/SD image)     2. Press Program.     3. Close ATK, turn off the board and set switches to:     Debug Board: SW9 -> 0       SW10 -> 0 Personality Board: SW2 (Bits 1 and 2) -> 1       SW2 (All other bits) -> 0       SW1 (All bits) -> 0     4. Open Hyper Terminal, set it 115200,N,8 and see RedBoot Prompt.      

  IMX6 SL boot process is described in Chapter 8 (System Boot) of the Reference Manual. Shortly, the loading boot data from boot SD card is performed in two stages : first read IVT, DCD, then read executable code, using the Boot Data Structure.    At first, boot ROM copies 4K byte (containing IVT and DCD ) from sector 0 of the boot SD card to internal buffer in OCRAM, located in reserved area (0x00900000 - 0x00907000). This area must not be used by user application.   Then, “after checking the Image Vector Table header value (0xD1) from Program Image, the ROM code performs a DCD check. After successful DCD extraction, the ROM code extracts from Boot Data Structure the destination pointer and length of image to be copied to RAM device from where code execution occurs”.   The IVT contains field entry - absolute address of the first instruction to execute from the image.   Note : according to Figure 8-3 (Internal ROM and RAM memory map), only OCRAM Free Area (68KB) from 0x00907000 till 0x00918000 may be used by user’s application.   The attachment contains SD-bootable example.

Requirements: Host machine with Ubuntu 14.04 UDOO Quad/Dual Board uSD card with at least 8 GB Download documentation and install latest Official Udoobuntu OS (at the moment of writing: UDOObuntu 2.1.2), https://www.udoo.org/downloads/   Overview: This document describes how to install and test Keras (Open source neural network library) and Theano (numerical computation library for python ) for deep learning library usage on i.MX6QD UDOO board.  Installation: $ sudo apt-get update && sudo apt-get upgrade update your date system: e.g. $ sudo date -s “07/08/2017 12:00” First satisfy the run-time and build time dependencies: $ sudo apt-get install python-software-properties software-properties-common make unzip zlib1g-dev git pkg-config autoconf automake libtool curl  python-pip python-numpy libblas-dev liblapack-dev python-dev libatlas-base-dev gfortran libhdf5-serial-dev libhdf5-dev python-setuptools libyaml-dev libpython2.7-dev $ sudo easy_install scipy The last step is installing scipy through pip, and can take several hours. Theano First, we have a few more dependencies to get: $sudo pip install scikit-learn $sudo pip install pillow $sudo pip install h5py With these dependencies met, we can install a stable Theano release from the git source: $ git clone https://github.com/Theano/Theano $ cd Theano Numpy 1.9 cause conflicts with armv7, so we need to change the setup.py configuration: $ sudo nano setup.py Remove line    #       install_requires=['numpy>=1.9.1', 'scipy>=0.14', 'six>=1.9.0'], And add setup_requires=["numpy"], install_requires=["numpy"], Then install it: $ sudo python setup.py install Keras The installation can occur with the command: (this could take a lot of time!!!) $ cd .. $ git clone https://github.com/fchollet/keras.git $ cd keras $ sudo python setup.py install $ LC_ALL=C $sudo pip install --upgrade keras After Keras is installed, you will want to edit the Keras configuration file ~/.keras/keras.json to use Theano instead of the default TensorFlow backend. If it isn't there, you can create it. This requires changing two lines. The first change is: "image_dim_ordering": "tf"  --> "image_dim_ordering": "th" and the second: "backend": "tensorflow" --> "backend": "theano" (The final file should look like the example below) sudo nano ~/.keras/keras.json {     "image_dim_ordering": "th",     "epsilon": 1e-07,     "floatx": "float32",     "image_data_format": "channels_last",     "backend": "theano" } You can also define the environment variable KERAS_BACKEND and this will override what is defined in your config file : $ KERAS_BACKEND=theano python -c "from keras import backend" Testing Quick test: udooer@udoo:~$ python Python 2.7.6 (default, Oct 26 2016, 20:46:32) [GCC 4.8.4] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import keras Using Theano backend. >>>  Test 2: Be aware this test take some time (~1hr on udoo dual): $ curl -sSL -k https://github.com/fchollet/keras/raw/master/examples/mnist_mlp.py | python Output: For demonstration, deep-learning-models repository provided by pyimagesearch and from fchollet git, and also have three Keras models (VGG16, VGG19, and ResNet50) online — these networks are pre-trained on the ImageNet dataset, meaning that they can recognize 1,000 common object classes out-of-the-box. $ cd keras $ git clone https://github.com/fchollet/deep-learning-models $ Cd deep-learning-models $ ls -l Notice how we have four Python files. The resnet50.py , vgg16.py , and vgg19.py  files correspond to their respective network architecture definitions. The imagenet_utils  file, as the name suggests, contains a couple helper functions that allow us to prepare images for classification as well as obtain the final class label predictions from the network Classify ImageNet classes with ResNet50 ResNet50 model, with weights pre-trained on ImageNet. This model is available for both the Theano and TensorFlow backend, and can be built both with "channels_first" data format (channels, height, width) or "channels_last" data format (height, width, channels). The default input size for this model is 224x224. We are now ready to write some Python code to classify image contents utilizing  convolutional Neural Networks (CNNs) pre-trained on the ImageNet dataset. For udoo Quad/Dual use ResNet50 due to avoid space conflict. Also we are going to use ImageNet (http://image-net.org/) that is an image database organized according to the WordNet hierarchy, in which each node of the hierarchy is depicted by hundreds and thousands of images. from keras.applications.resnet50 import ResNet50 from keras.preprocessing import image from keras.applications.resnet50 import preprocess_input, decode_predictions import numpy as np   model = ResNet50(weights='imagenet')   #for this sample I download the image from: http://i.imgur.com/wpxMwsR.jpg  img_path = 'elephant.jpg' img = image.load_img(img_path, target_size=(224, 224)) x = image.img_to_array(img) x = np.expand_dims(x, axis=0) x = preprocess_input(x)   preds = model.predict(x) # decode the results into a list of tuples (class, description, probability) # (one such list for each sample in the batch) print('Predicted:', decode_predictions(preds, top=3)[0]) Save the file an run it. Results for elephant image: Top prediction was 0.8890 for African Elephant Testing with this image: http://i.imgur.com/4FIOwAN.jpg Results: Top prediction was: 0.7799 for golden_retriever. Now your Udoo is ready to use Keras and Theano as Deep Learning libraries, next time we are going to show some usage example for image classification models with OpenCV. References: GitHub - fchollet/keras: Deep Learning library for Python. Runs on TensorFlow, Theano, or CNTK.  GitHub - Theano/Theano: Theano is a Python library that allows you to define, optimize, and evaluate mathematical expres…  GitHub - fchollet/deep-learning-models: Keras code and weights files for popular deep learning models.  Installing Keras for deep learning - PyImageSearch 

Patch for i.MX6 boards with LPDDR2 using single channel

This white paper is a discussion of random hangs and other issues using Windows Embedded Compact on Freescale i.MX6 application processor and how they were solved. All information in this document applies to Windows Embedded Compact 7 and 2013 as well as all variants of the i.MX6.      

i.MX 6 SoloX MCC MCC is a library for lightweight communication between cores Configured at compile time (mcc_config.h) Current version (2.0) is not backward compatible MCC works with shared memory area Communication is performed through ‘send’ and ‘receive’ functions Shared memory Cores communicate through shared memory Core structures of the MCC  MCC_ENDPOINT core Identifies a processor core, A9 is 0 and M4 is 1. node In Linux, each process using MCC has its own node number. MQX has only one node number. port Any number of ports per node is allowed. Value MCC_RESERVED_PORT_NUMBER is not allowed. The number of endpoints in system is defined during compile time by macro MCC_ATTR_MAX_RECEIVE_ENDPOINTS. MCC_BOOKEEPING_STRUCT Endpoint table I. MCC API  Functions Standard API −int mcc_initialize(MCC_NODE); −int mcc_destroy(MCC_NODE); −int mcc_create_endpoint(MCC_ENDPOINT*, MCC_PORT); −int mcc_destroy_endpoint(MCC_ENDPOINT*); −int mcc_send(MCC_ENDPOINT*, MCC_ENDPOINT*, void*, MCC_MEM_SIZE, unsigned int); −int mcc_recv(MCC_ENDPOINT*, MCC_ENDPOINT*, void*, MCC_MEM_SIZE, MCC_MEM_SIZE*, unsigned int); −int mcc_msgs_available(MCC_ENDPOINT*, unsigned int*); −int mcc_get_info(MCC_NODE, MCC_INFO_STRUCT*); MCC_SEND_RECV_NOCOPY_API_ENABLED −int mcc_get_buffer(void**, MCC_MEM_SIZE*, unsigned int); −int mcc_send_nocopy(MCC_ENDPOINT*, MCC_ENDPOINT*, void*, MCC_MEM_SIZE); −int mcc_recv_nocopy(MCC_ENDPOINT*, MCC_ENDPOINT*, void**, MCC_MEM_SIZE*, unsigned int); −int mcc_free_buffer(void*);