A computer-implemented method of generating reference data for adjusting a digital representation of a head region, the method comprising: receiving training data (100, TD) comprising: a set of input patches, each input patch comprising a target feature of a digital representation of a head region prior to adjustment of the digital representation of the head region, wherein the target feature is the same for each input patch; a set of output patches in one-to-one correspondence with the input patches, each output patch comprising the target feature of the digital representation of the head region after adjustment of the digital representation of the head region; and a basis set used for providing a compressed representation of editing instructions; using a first machine learning algorithm to generate first reference data using the training data (100, TD), the first reference data comprising editing instructions for adjusting the digital representation of the head region for a range of possible digital representations of the head region; and using a second machine learning algorithm to generate second reference data using the same training data (100, TD) as the first machine learning algorithm and the first reference data generated by the first machine learning algorithm, the second reference data comprising editing instructions for adjusting the digital representation of the head region for a range of possible digital representations of the head region, wherein the second editing instructions in the second reference data are provided in the compressed representation using the basis set. receiving training data (100, TD) comprising: a set of input patches, each input patch comprising a target feature of a digital representation of a head region prior to adjustment of the digital representation of the head region, wherein the target feature is the same for each input patch; a set of output patches in one-to-one correspondence with the input patches, each output patch comprising the target feature of the digital representation of the head region after adjustment of the digital representation of the head region; and a basis set used for providing a compressed representation of editing instructions; a set of input patches, each input patch comprising a target feature of a digital representation of a head region prior to adjustment of the digital representation of the head region, wherein the target feature is the same for each input patch; a set of output patches in one-to-one correspondence with the input patches, each output patch comprising the target feature of the digital representation of the head region after adjustment of the digital representation of the head region; and a basis set used for providing a compressed representation of editing instructions; using a first machine learning algorithm to generate first reference data using the training data (100, TD), the first reference data comprising editing instructions for adjusting the digital representation of the head region for a range of possible digital representations of the head region; and using a second machine learning algorithm to generate second reference data using the same training data (100, TD) as the first machine learning algorithm and the first reference data generated by the first machine learning algorithm, the second reference data comprising editing instructions for adjusting the digital representation of the head region for a range of possible digital representations of the head region, wherein the second editing instructions in the second reference data are provided in the compressed representation using the basis set.