启用3D模式允许设计具有多层的图片，其中一些像素比其他人突出得更远
这可能不适合所有图像，但在许多情况下可以开启
支持的图像格式取决于浏览器的兼容性
由于积木套装的性质，不完全支持透明图像
使用高分辨率时要小心，这可能会导致低功率设备出现性能问题，特别是在pdf生成和3D预览期间
计算深度图在计算上可能很昂贵。准备好等待一段时间，然后小心，尤其是如果你有一个不太强大的设备。
这是如何工作的?深度图是使用DNN（深度神经网络）计算的。由于中所述的原因在“about”部分，所有内容都完全在浏览器中运行，使用修改后的 ONNX.js版本。模型使用了 MiDaS -更具体地说是可以找到的小型ONNX版本 here.
重要: 由于选择了可变大小的像素类型， '无限计件数' 低于 '可选颜色' 是可能的 - 小心!
可用尺寸:● 此设置决定使用哪个距离函数将像素与其最接近的积木颜色对齐。
● 这决定了像素对齐所采用的策略。
● 有些算法运行速度比其他算法快——在处理较大图像时，运行贪婪算法时要格外小心。
重要: 由于这是一个线性误差抖动算法， '无限碎片计数' 有可能低于 '可选颜色' - 小心!
通常最好使用 '欧标RGB' 对于颜色距离函数，为了数学上的简洁性
如果您有一个很大的背景，但没有足够的图案块在步骤 4 中均匀地填充它，那么更改此设置就很有用。
● 点击像素可增加其高度
● 点击像素可减小其高度
| 颜色 | 尺寸 | 数量 |
|---|
| 颜色 | 号码缺失 |
|---|
根据您的硬件配置和所选分辨率，生成 PDF 文件可能需要几秒钟。 如果您要生成高分辨率的说明文件，尤其是高质量 PDF文件，请做好等待的准备。 高分辨率也可能导致页面加载缓慢，甚至在性能较低的设备上可能无法正常显示，因此我建议从默认分辨率开始，然后逐步提高分辨率。
下载说明书后发送给店铺客服确认清单与价格，点击下单定制
● 这是3D效果的（非常）粗略预览。
● 将鼠标悬停在图像上即可改变视角
● 请确保您的深度图不为空。
● 由于这是动态生成的，因此在性能较低的设备上可能效果不佳。
● 请注意，效果会因浏览器而异，可能比较细微，并且可能无法100%还原实物艺术品的实际效果。
● 这是一组可用于生成深度说明和零件清单的模板。
● 这些部分用作填充，以便使正确的像素向外突出。
● 请注意，较大的盘子可能难以安装/拆卸到底座上。
可用板:较长的指令可能会分成多个文件。
根据您的硬件配置和所选分辨率，生成 PDF 文件可能需要几秒钟。 如果您要生成高分辨率的说明文件，尤其是高质量 PDF 文件，请做好等待的准备。 高分辨率也可能导致页面加载缓慢，甚至在性能较低的设备上可能无法正常显示，因此我建议从默认分辨率开始，然后逐步提高分辨率。
下载说明书后发送给店铺客服确认清单与价格，点击下单定制
Below is a recording of my tech talk from BrickCon 2021
If you're interested in understanding how this site works, the talk goes over the techniques and algorithms that were used
It also goes over some ideas that haven't (yet) been implemented within the tool, so it functions fairly well as a more general overview of the Lego mosaic space
You can find the slide deck used in the talk here (with some updates since the talk), and if the video doesn't load, you can find it directly on BrickCon's YouTube channel here
These are some other articles and videos featuring Lego Art Remix
Some are quite interesting even outside the context of this tool in particular, since they go into the history of Lego mosaics
Note that some were made when the tool was older
In 2020, The Lego Group released the
Lego Art
theme, which allows people to create a predetermined image using lego studs.
Lego Art Remix lets you upload your own image, and then uses computer vision to use the studs from a Lego
Art set that you already have to recreate the image.
This project is not affiliated with The Lego Group
The computer vision techniques used are pretty inexpensive (with the exception of optional depth map generation), and the resolutions being dealt with are naturally quite low, so as of the time of writing, the algorithm runs quite quickly. This allows for it to be run on the client, and on the machines that I tested, it ran in near real time.
The most computationally expensive part of the process, apart from depth map generation, is generating the instructions, since even pdf generation is done client side.
Since it runs almost entirely within the browser (see the source code), no image data is sent to a server and so it's very secure. This also makes it much easier for me to maintain and host. The only server code consists of simple increments to anonymously estimate usage for the purposes for tracking performance in case the static deployment needs to be scaled up, and for the counter in the about section.
Even the deep neural network to compute depth maps is being run entirely within the browser, in a web worker, using a modified version of ONNX.js. I've compiled a version of the library based on this pull request, with a small additional change I made to support the resize operation in v10. The model used is MiDaS - more specifically, the small ONNX version which can be found here.
As of the time of writing, I don't have all of the sets, and I haven't had much time to test. As a result, there's probably a few bugs, so let me know if you find any.
Algorithm improvement ideas are always welcome. Improvements that maintain the efficiency to within a reasonable degree would allow the algorithm to keep running on the client, which I really like.
Note: No user data is stored, so this is just aggregated info based on simple increments
| Date | Images created |
|---|