Software and lasers are used in finishing apparel to produce a desired wear pattern or other design. A technique includes using machine learning to create or extract a laser input file for wear pattern from an existing garment. Machine learning can be by a generative adversarial network, having generative and discriminative neural nets. The generative adversarial network is trained and then used to create a model. This model is used generate the laser input file from an image of the existing garment with the finishing pattern. With this laser input file, a laser can re-create the wear pattern from the existing garment onto a new garment.

Software and lasers are used in finishing apparel to produce a desired wear pattern or other design. A technique includes using machine learning to create or extract a laser input file for wear pattern from an existing garment. Machine learning can be by a generative adversarial network, having generative and discriminative neural nets. The generative adversarial network is trained and then used to create a model. This model is used generate the laser input file from an image of the existing garment with the finishing pattern. With this laser input file, a laser can re-create the wear pattern from the existing garment onto a new garment.

Laser finishing of apparel products allows an operating model that reduces finishing cost, lowers carrying costs, increases productivity, shortens time to market, be more reactive to trends, reduce product constraints, reduces lost sales and dilution, and more. Improved aspects include design, development, planning, merchandising, selling, making, and delivering. The model uses fabric templates, each of which can be used to produce a multitude of laser finishes. Operational efficiency is improved.

A fabric has enhanced response characteristics for laser finishing. The fabric can be denim for denim apparel such as jeans. Software and lasers are used to finish apparel made of the fabric to produce a desired wear or distressing pattern or other design. The fabric allows for relatively fast color change in response to the laser, color changes in hue from indigo blue to white, many grayscale levels, and maintains strength and stretch properties. A method used to make the fabric includes spinning, dyeing, and weaving yarns in such a way to obtain the desired enhanced response characteristics for laser finishing.

A fabric has enhanced response characteristics for laser finishing. The fabric can be denim for denim apparel such as jeans. Software and lasers are used to finish apparel made of the fabric to produce a desired wear or distressing pattern or other design. The fabric allows for relatively fast color change in response to the laser, color changes in hue from indigo blue to white, many grayscale levels, and maintains strength and stretch properties. A method used to make the fabric includes spinning, dyeing, and weaving yarns in such a way to obtain the desired enhanced response characteristics for laser finishing.

An example of a dye discharge fluid includes a water-soluble organic solvent, a heat activated reducing agent, and water. A pH of the dye discharge fluid is less than 7. The dye discharge fluid may be used with a colored pigmented inkjet ink, a white pigmented inkjet ink, and/or a colored textile fabric, and may be included in a fluid set and/or a printing kit.

A system allows a user to create new designs for apparel and preview these designs before manufacture. Software and lasers are used in finishing apparel to produce a desired wear pattern or other design. The user's preview may be based upon a two-dimensional image of a wear pattern in a laser input file and, from a set of two-dimensional images of a base garment, create a three-dimensional view of the base garment with the wear pattern.

Software and lasers are used in finishing apparel to produce a desired wear pattern or other design. A technique includes using machine learning to create or extract a laser input file for wear pattern from an existing garment. Machine learning can be by a generative adversarial network, having generative and discriminative neural nets. The generative adversarial network is trained and then used to create a model. This model is used generate the laser input file from an image of the existing garment with the finishing pattern. With this laser input file, a laser can re-create the wear pattern from the existing garment onto a new garment.

Software and lasers are used in finishing apparel to produce a desired wear pattern or other design. A technique includes using machine learning to create or extract a laser input file for wear pattern from an existing garment. Machine learning can be by a generative adversarial network, having generative and discriminative neural nets. The generative adversarial network is trained and then used to create a model. This model is used generate the laser input file from an image of the existing garment with the finishing pattern. With this laser input file, a laser can re-create the wear pattern from the existing garment onto a new garment.

The invention relates to a process of treating a dyed fabric, in which fungi are used. The invention also relates to a package comprising a water impervious container and a fabric or a garment treated according to the process, and to a fabric or a garment as obtainable by the process of the invention.