To fill the binary image of draped fabric into a comparable grayscale image with detailed shade information, the three-dimensional point cloud of draped fabric was obtained with a self-built three-dimensional scanning device. The three-dimensional point cloud of drape fabric is encapsulated into a triangular mesh, and the binary and grayscale images of draped fabric were rendered in virtual environments separately. A pix2pix convolutional neural network with the binary image of draped fabric as input and the grayscale image of draped fabric as output was constructed and trained. The relationship between the binary image and the grayscale image was established. The results show that the trained pix2pix neural network can fill unknown binary top view images of draped fabric to grayscale images. The average pixel cosine similarity between filling results and ground truth could reach 0.97.

中文翻译：

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用 pix2pix 卷积神经网络填充悬垂织物的二值图像

为了将悬垂织物的二值图像填充为具有详细色调信息的可比较灰度图像，利用自建的三维扫描装置获得悬垂织物的三维点云。悬垂织物的三维点云封装成三角形网格，悬垂织物的二值和灰度图像分别在虚拟环境中渲染。构建并训练了以悬垂织物的二值图像作为输入、悬垂织物的灰度图像作为输出的pix2pix卷积神经网络。建立了二值图像和灰度图像之间的关系。结果表明，经过训练的 pix2pix 神经网络可以将悬垂织物的未知二元顶视图图像填充为灰度图像。