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Addressing the challenges of manual reporting management in textile production, a machine vision-based automatic reporting system was developed for a digital textile printing factory. This system intelligently matches the patterns of the fabrics currently in production with the designs in the order database, enabling rapid and accurate management of production orders. Initially, the client system uses an industrial camera to capture real-time images of printed fabrics on the production line, which are then subjected to preprocessing such as filtering and normalization. These images are then transmitted to the server system via HTTP protocol, where a neural network model based on Vision Transformer is employed for feature extraction and multi-layer feature fusion. Subsequently, the images are matched with pattern designs in the order database to identify the orders needing reporting. Finally, the matching results are managed in the database and returned to the client for display and confirmation of the reporting results. Experimental results demonstrate that this automatic reporting system achieves a TOP-3 match rate of 90.4%, fulfilling the needs of factory fabric production.