Abstract: A system and method for predicting sellability of a fashion product is provided. The system includes a memory having computer-readable instructions stored therein. The system further includes a processor configured to access one or more catalogue images of a fashion product. The processor is configured to determine a plurality of visual attributes of the fashion product. The processor is further configured to determine a plurality of non-visual attributes corresponding to the fashion product. In addition, the processor is configured to estimate a first sellability confidence value for the reference fashion style using a deep learning model. The first sellability confidence value is estimated based upon the visual attributes. Further, the processor is configured to estimate a second sellability confidence value for the reference fashion style using a non-visual parameter model. The second sellability confidence value is estimated based upon the non-visual attributes.

Abstract: A generative system includes a memory having computer readable instructions stored therein. The system further includes a processor configured to access a plurality of fashion images of a plurality of fashion products. The processor is configured to train a generative model using the plurality of fashion images of the fashion products. The processor is further configured to estimate latent vectors corresponding to the plurality of fashion images via the generative model. Furthermore, the processor is configured to transform the latent vectors to generate one or more transformed fashion images via the generative model. The one or more transformed fashion images are generated using characteristics of the plurality of fashion images. Moreover, the processor further configured to create one or more fashion products based upon the generated transformed fashion images.

Abstract: A discrete wavelet transform (DWT) based generative system for generating images of fashion products is provided. The system includes a memory having computer-readable instructions stored therein. The system includes a processor configured to access a plurality of fashion images of a plurality of fashion products. Each fashion image is generated at a first resolution. The processor is configured to train one or more DWT based generative models using the plurality of fashion images of the fashion products. Each of the generative models is selectively trained using a directional fashion image. The directional fashion image includes details of the fashion products corresponding to a pre-determined orientation and scale. The processor is further configured to generate an upsampled fashion image corresponding to each of the fashion images. Each upsampled fashion image is generated at a second resolution.

Abstract: An image processing system and method for determining one or more attributes of a fashion apparel is provided. The system includes a pattern template. The pattern template further includes a plurality of patterns and the fashion apparel is positioned on top of the patterned template. The system further includes an imaging device configured to capture an image of the fashion apparel positioned on top of the pattern template. In addition, the system includes a size and color determination module coupled to the imaging sensor and configured to receive the image and extract a size and a color of the fashion apparel by using the plurality of patterns in the pattern template.

Abstract: A system and method for determining color variants of a fashion product is provided. A system for determining a color variant of a fashion product is provided. The system comprises a categorization module configured to receive a plurality of images corresponding to a plurality of fashion products and configured to categorize the plurality of images into a plurality of styles. The system further includes a color variant determination module configured to compute a plurality of embeddings for the corresponding plurality of images, compute a mean value for the plurality of embeddings and compare each embedding to one or more predefined constraints to determine whether the embedding belongs to a color variant set.

Abstract: A system and method for extraction of design elements of a fashion product is provided. The system includes a memory having computer-readable instructions stored therein. The system further includes a processor configured to access a catalogue image of a fashion product. In addition, the processor is configured to segment the catalogue image of the fashion product to determine an article of interest of the fashion product. The processor is further configured to generate an outer contour of the article of interest using a contour tracing technique. Moreover, the processor is configured to analyze coordinates of the generated contour based upon convexity defects of the contour to identify one or more design points. Furthermore, the processor is configured to extract one or more design elements of the fashion product using the identified design points.

Abstract: A discrete wavelet transform (DWT) based generative system for generating images of fashion products is provided. The system includes a memory having computer-readable instructions stored therein. The system includes a processor configured to access a plurality of fashion images of a plurality of fashion products. Each fashion image is generated at a first resolution. The processor is configured to train one or more DWT based generative models using the plurality of fashion images of the fashion products. Each of the generative models is selectively trained using a directional fashion image. The directional fashion image includes details of the fashion products corresponding to a pre-determined orientation and scale. The processor is further configured to generate an upsampled fashion image corresponding to each of the fashion images. Each upsampled fashion image is generated at a second resolution.

Abstract: A generative system for creating fashion products is provided. The system includes a memory having computer readable instructions stored therein. The system further includes a processor configured to access a plurality of fashion images of a plurality of fashion products. The processor is configured to train a generative model using the plurality of fashion images of the fashion products. The processor is further configured to estimate latent vectors corresponding to the plurality of fashion images via the generative model. Furthermore, the processor is configured to transform the latent vectors to generate one or more transformed fashion images via the generative model. The one or more transformed fashion images are generated using characteristics of the plurality of fashion images. Moreover, the processor further configured to create one or more fashion products based upon the generated transformed fashion images.

Abstract: A system and method for predicting sellability of a fashion product is provided. The system includes a memory having computer-readable instructions stored therein. The system further includes a processor configured to access one or more catalogue images of a fashion product. The processor is configured to determine a plurality of visual attributes of the fashion product. The processor is further configured to determine a plurality of non-visual attributes corresponding to the fashion product. In addition, the processor is configured to estimate a first sellability confidence value for the reference fashion style using a deep learning model. The first sellability confidence value is estimated based upon the visual attributes. Further, the processor is configured to estimate a second sellability confidence value for the reference fashion style using a non-visual parameter model. The second sellability confidence value is estimated based upon the non-visual attributes.

Abstract: An image processing system and method for determining one or more attributes of a fashion apparel is provided. The system includes a pattern template. The pattern template further includes a plurality of patterns and the fashion apparel is positioned on top of the patterned template. The system further includes an imaging device configured to capture an image of the fashion apparel positioned on top of the pattern template. In addition, the system includes a size and color determination module coupled to the imaging sensor and configured to receive the image and extract a size and a color of the fashion apparel by using the plurality of patterns in the pattern template.

Abstract: A system and method for extraction of design elements of a fashion product is provided. The system includes a memory having computer-readable instructions stored therein. The system further includes a processor configured to access a catalogue image of a fashion product. In addition, the processor is configured to segment the catalogue image of the fashion product to determine an article of interest of the fashion product. The processor is further configured to generate an outer contour of the article of interest using a contour tracing technique. Moreover, the processor is configured to analyze coordinates of the generated contour based upon convexity defects of the contour to identify one or more design points. Furthermore, the processor is configured to extract one or more design elements of the fashion product using the identified design points.

Abstract: A system and method for determining color variants of a fashion product is provided. A system for determining a color variant of a fashion product is provided. The system comprises a categorization module configured to receive a plurality of images corresponding to a plurality of fashion products and configured to categorize the plurality of images into a plurality of styles. The system further includes a color variant determination module configured to compute a plurality of embeddings for the corresponding plurality of images, compute a mean value for the plurality of embeddings and compare each embedding to one or more predefined constraints to determine whether the embedding belongs to a color variant set.