processing option: allff ============================================ TARGET_ARCH=arm64 TARGET_PLATFORM=rk3399 TARGET_UBOOT_CONFIG=rk3399 TARGET_SPL_CONFIG= TARGET_KERNEL_CONFIG=rockchip_linux_defconfig TARGET_KERNEL_DTS=rk3399-evb-ind-lpddr4-linux TARGET_TOOLCHAIN_CONFIG= TARGET_BUILDROOT_CONFIG=rockchip_rk3399 TARGET_RECOVERY_CONFIG=rockchip_rk3399_recovery TARGET_PCBA_CONFIG=rockchip_rk3399_pcba TARGET_RAMBOOT_CONFIG= ============================================ ============Start build uboot============ TARGET_UBOOT_CONFIG=rk3399 ========================================= ## make rk3399_defconfig -j4 ./make.sh: line 248: make: command not found ====Build uboot failed!====
时间: 2023-08-23 08:05:54 浏览: 72
根据你提供的输出,这是一个正在构建 U-Boot 的过程。
首先,输出显示了一些处理选项,其中包括 "allff"。然后,它列出了一些目标配置和构建选项,例如目标架构、平台、U-Boot 配置等。
接下来,它开始构建 U-Boot,并指示使用的 U-Boot 配置为 "rk3399"。
然后,它尝试执行命令 `make rk3399_defconfig -j4`,但是出现了错误提示 `make: command not found`,表明系统中没有安装 `make` 工具。
最后,输出显示构建 U-Boot 失败。
要解决此问题,你需要确保在系统上安装了 `make` 工具。你可以使用以下命令在 Ubuntu 或基于 Debian 的系统上安装 `make`:
```
sudo apt-get install build-essential
```
这个命令将安装 `build-essential` 包,其中包括 `make` 工具和其他构建所需的工具。安装完成后,你应该能够重新运行构建命令并成功构建 U-Boot。
相关问题
type="submit"
This is a HTML attribute that is used to define a button or input element as a clickable submit button in a form. When the user clicks on this button, the form data is submitted to the server for processing.
Example:
```html
<form action="/login" method="post">
<label for="username">Username:</label>
<input type="text" id="username" name="username"><br>
<label for="password">Password:</label>
<input type="password" id="password" name="password"><br>
<input type="submit" value="Submit">
</form>
```
In this example, the `type="submit"` attribute is used to create a submit button for the login form. When the user clicks on the "Submit" button, the form data (i.e. the username and password) is sent to the `/login` URL using the HTTP POST method.
image /= 255.0
This code line is dividing all the pixel values in an image by 255.0.
In computer vision and image processing, pixel values usually range between 0 and 255, representing the brightness or intensity of the corresponding point on the image. However, some algorithms and models require the pixel values to be normalized, meaning that they should be scaled to a smaller range, usually between 0 and 1, to improve the efficiency and accuracy of the computations.
Therefore, by dividing all the pixel values by 255.0, we can obtain a normalized image where the pixel values range between 0 and 1. This way, we can ensure that the image is ready to be fed into a machine learning model, for example.