Method for checking the reliability of a camera system of a motor vehicle including the steps of: - providing at least one image of a region in the surroundings of the motor vehicle by means of a camera of the camera system, - detecting at least one object external to said motor vehicle in the image by means of an image processing device of the camera system, - providing sensor data by means of at least one sensor of the motor vehicle, wherein the sensor data characterizes conditions in the surroundings of the motor vehicle, wherein data provided as the sensor data is any one of ∘ data indicating a current operating state of a headlight of the motor vehicle, and/or ∘ data indicating a current operating state of a windshield wiper of the motor vehicle, and/or ∘ sensor data of a rain sensor and/or of a brightness sensor of the motor vehicle, - first classifying the at least one object depending on the sensor data SD and herein associating the object with a class (K1, K2, K3, K4) among several predetermined classes (K1, K2, K3, K4) depending on the conditions in the surroundings, wherein the classes (K1, K2, K3, K4) differ from each other with respect to the conditions in the surroundings, wherein the classes (K1, K2, K3, K4) differ from each other in a brightness of the region in the surroundings - second classifying the at least one object and herein associating the object with one of the classes (K1, K2, K3, K4) based on the image and independently of the sensor data by a classification device using a predetermined classification model, and - comparing classification results of the first and the second classification and deciding on the reliability depending on the comparison, wherein: - an algorithm is used as the classification model, which is trained with test image data with respect to the classification, the training of the algorithm includes that objects are detected in the test image data and are each associated with one of the classes (K1, K2, K3, K4) depending on sensor data of at least one sensor, which characterizes conditions in the surroundings at the time of capture of the test image data, wherein the classified objects are taken as a basis for training the algorithm and - if it is detected by the camera system that the object has been associated with a different class (K1, K2, K3, K4) by the first classification than by the second classification, an error signal is generated by the camera system. - providing at least one image of a region in the surroundings of the motor vehicle by means of a camera of the camera system, - detecting at least one object external to said motor vehicle in the image by means of an image processing device of the camera system, - providing sensor data by means of at least one sensor of the motor vehicle, wherein the sensor data characterizes conditions in the surroundings of the motor vehicle, wherein data provided as the sensor data is any one of ∘ data indicating a current operating state of a headlight of the motor vehicle, and/or ∘ data indicating a current operating state of a windshield wiper of the motor vehicle, and/or ∘ sensor data of a rain sensor and/or of a brightness sensor of the motor vehicle, ∘ data indicating a current operating state of a headlight of the motor vehicle, and/or ∘ data indicating a current operating state of a windshield wiper of the motor vehicle, and/or ∘ sensor data of a rain sensor and/or of a brightness sensor of the motor vehicle, - first classifying the at least one object depending on the sensor data SD and herein associating the object with a class (K1, K2, K3, K4) among several predetermined classes (K1, K2, K3, K4) depending on the conditions in the surroundings, wherein the classes (K1, K2, K3, K4) differ from each other with respect to the conditions in the surroundings, wherein the classes (K1, K2, K3, K4) differ from each other in a brightness of the region in the surroundings - second classifying the at least one object and herein associating the object with one of the classes (K1, K2, K3, K4) based on the image and independently of the sensor data by a classification device using a predetermined classification model, and - comparing classification results of the first and the second classification and deciding on the reliability depending on the comparison, wherein: - an algorithm is used as the classification model, which is trained with test image data with respect to the classification, the training of the algorithm includes that objects are detected in the test image data and are each associated with one of the classes (K1, K2, K3, K4) depending on sensor data of at least one sensor, which characterizes conditions in the surroundings at the time of capture of the test image data, wherein the classified objects are taken as a basis for training the algorithm and - if it is detected by the camera system that the object has been associated with a different class (K1, K2, K3, K4) by the first classification than by the second classification, an error signal is generated by the camera system.