Traditional techniques for examining fashion trends, such as surveys and focus groups, can be limited
in their reach and often require significant time and resources. To keep up with the fast-changing
nature of fashion and harness the extensive data available, algorithmic solutions have proven to be
highly efficient and practical alternatives. In this context, deep learning algorithms are essential
for offering valuable insights and predictions related to fashion trends, leveraging the power and
versatility of machine learning in the analysis.
Classification of fashion image data using Deep Learning has been approached in different ways - trying to solve multi label fashion image classification using detection, segmentation, pose estimation, etc. applied to recommendation, retrieval, forecasting, etc. Most of the techniques are based on benchmark data sets or data sets containing a particular set of fashion segment (region, type of clothing, period, etc.). There is lack of significant work in Indian fashion segment in different aspects. An extensive annotated Indian fashion dataset containing real life public images from social media, e-commerce websites and other web resources which are reliable in terms of quality and quantity are not easily available and a comprehensive indigenous computer vision engine modeled by deep learning for fashion classification is absent whose applications in identification, trend forecasting and recommendation can be tremendously useful in gaining authentic, geographical and period specific fashion insights which will enable the Indian textile, fashion and retail industry to create targeted products for Indian consumers.
Fast Code AI's Contribution
Our work uses a custom built dataset to build a deep learning classification pipeline achieving benchmark structured attribute level multi label classification paving way for many machine learning tasks like retrieval, recommendation, etc and prediction of fashion trends, consumer behavior, and market trends in the Indian fashion segment research
- Data engine
We have introduced a custom Indian dataset we are building from scratch aiming for a large, high quality, Indian fashion dataset containing fine grained attribute annotations. This dataset will be very beneficial for deep learning research in the indian fashion segment for a variety of important tasks like recommendation, trend forecasting, etc.. which was not possible to do in a large scale because of the lack of availability of a good representative Indian dataset.
- Deep learning based model pipeline for fashion identification
- Trend forecasting and recommendation based on authentic geographical and period specific indian fashion insights.