An apparatus for monitoring a switchgear, the apparatus comprising: - an input unit; - a processing unit; and - an output unit; wherein, the input unit is configured to provide the processing unit with a monitor infra-red image of a switchgear; wherein, the processing unit is configured to implement a machine learning classifier algorithm to analyse the monitor infra-red image and determine if there is one or more anomalous hot spots in the switchgear; wherein, the machine learning classifier algorithm has been trained on the basis of a plurality of training images of a switchgear; wherein, the processing unit is configured to implement an image processing algorithm operating as a discriminator to analyse the monitor infra-red image to determine information relating to the expected efficacy of the machine learning classifier algorithm in analysing the monitor infra-red image, wherein the plurality of training images comprises at least one real infra-red image of a switchgear and a plurality of different synthetic infra-red images of a switchgear generated on the basis of at least one real infra-red image of a switchgear by the image processing algorithm operating as a generator; wherein the image processing algorithm is trained to operate as the discriminator on the basis of at least some of the plurality of training images; wherein the at least some of the plurality of training images used to train the image processing algorithm operating as the discriminator comprises the plurality of synthetic infra-red images and one or more of the at least one real infra-red image; wherein the information relating to the expected efficacy of the machine learning classifier algorithm in analysing the monitor infra-red image comprises a similarity metric between the monitor infra-red image and the plurality of training images; and wherein, the output unit is configured to output the information relating to the expected efficacy of the machine learning classifier algorithm in analysing the monitor infra-red image. - an input unit; - a processing unit; and - an output unit; wherein, the input unit is configured to provide the processing unit with a monitor infra-red image of a switchgear; wherein, the processing unit is configured to implement a machine learning classifier algorithm to analyse the monitor infra-red image and determine if there is one or more anomalous hot spots in the switchgear; wherein, the machine learning classifier algorithm has been trained on the basis of a plurality of training images of a switchgear; wherein, the processing unit is configured to implement an image processing algorithm operating as a discriminator to analyse the monitor infra-red image to determine information relating to the expected efficacy of the machine learning classifier algorithm in analysing the monitor infra-red image, wherein the plurality of training images comprises at least one real infra-red image of a switchgear and a plurality of different synthetic infra-red images of a switchgear generated on the basis of at least one real infra-red image of a switchgear by the image processing algorithm operating as a generator; wherein the image processing algorithm is trained to operate as the discriminator on the basis of at least some of the plurality of training images; wherein the at least some of the plurality of training images used to train the image processing algorithm operating as the discriminator comprises the plurality of synthetic infra-red images and one or more of the at least one real infra-red image; wherein the information relating to the expected efficacy of the machine learning classifier algorithm in analysing the monitor infra-red image comprises a similarity metric between the monitor infra-red image and the plurality of training images; and wherein, the output unit is configured to output the information relating to the expected efficacy of the machine learning classifier algorithm in analysing the monitor infra-red image. wherein, the input unit is configured to provide the processing unit with a monitor infra-red image of a switchgear; wherein, the processing unit is configured to implement a machine learning classifier algorithm to analyse the monitor infra-red image and determine if there is one or more anomalous hot spots in the switchgear; wherein, the machine learning classifier algorithm has been trained on the basis of a plurality of training images of a switchgear; wherein, the processing unit is configured to implement an image processing algorithm operating as a discriminator to analyse the monitor infra-red image to determine information relating to the expected efficacy of the machine learning classifier algorithm in analysing the monitor infra-red image, wherein the plurality of training images comprises at least one real infra-red image of a switchgear and a plurality of different synthetic infra-red images of a switchgear generated on the basis of at least one real infra-red image of a switchgear by the image processing algorithm operating as a generator; wherein the image processing algorithm is trained to operate as the discriminator on the basis of at least some of the plurality of training images; wherein the at least some of the plurality of training images used to train the image processing algorithm operating as the discriminator comprises the plurality of synthetic infra-red images and one or more of the at least one real infra-red image;