The repeated trial-weaving and proofing process are traditionally conducted to exhibit the ever-changing appearance of the colored spun yarn fabric knitted by different colored spun yarns. In this paper, a novel method of appearance generation for colored spun yarn fabric was proposed based on conditional image-to-image translation. The generated image is required to have the same color and the fabric style simultaneously as the color card and the assigned style. The common pix2pix model was modified by adding the category label to the image channel to involve the style constraint. To improve the generation performance, the U-Net architecture was replaced by the residual block architecture. Four commonly used style fabrics and different color cards were adopted to build the image pairs for experiments. The visual inspection and category similarity were used as the evaluation metrics. Experimental results reveal that the proposed method can transfer different color cards to the designated style fabrics based on the constraints, being effective and superior for image generation of colored spun yarns. The proposed scheme can provide references for the designer by presenting the image perception, saving labor, and material resources in the proofing process.

中文翻译：

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基于条件图像转换的彩色细纱织物外观生成

传统上通过反复试织和打样工艺，呈现出由不同色纱织成的色纱织物千变万化的外观。在本文中，提出了一种基于条件图像到图像转换的彩色细纱织物外观生成的新方法。生成的图像需要与色卡和指定的款式同时具有相同的颜色和面料款式。对常见的 pix2pix 模型进行了修改，将类别标签添加到图像通道以涉及样式约束。为了提高生成性能，U-Net 架构被残差块架构取代。采用四种常用款式面料和不同色卡构建图像对进行实验。视觉检查和类别相似性被用作评估指标。实验结果表明，所提出的方法可以根据约束条件将不同的色卡转移到指定风格的织物上，对于彩色细纱的图像生成是有效和优越的。提出的方案可以通过在打样过程中呈现图像感知，节省人工和材料资源，为设计人员提供参考。