A colon polyp image processing method, comprising: detecting, by a colon polyp image processing apparatus, a position of a polyp in a to-be-processed endoscopic image by using a polyp positioning model, and positioning a polyp image block in the endoscopic image, the polyp image block having: a position region of the polyp in the endoscopic image; and performing, by the colon polyp image processing apparatus, a polyp type classification detection on the polyp image block by using a polyp property identification model, and outputting an identification result; characterized by before the detecting, by a colon polyp image processing apparatus, a position of a polyp in a to-be-processed endoscopic image by using a polyp positioning model, the method further comprising: identifying, by the colon polyp image processing apparatus, a picture type of the endoscopic image, and determining that the endoscopic image is a white light type picture or an endoscope narrow band imaging, NBI, type picture; wherein the identifying, by the colon polyp image processing apparatus, a picture type of the endoscopic image, and determining that the endoscopic image is a white light type picture or an endoscope NBI type picture comprises: performing classification training on an original image classification model through white light type picture training data and NBI type picture training data by using a neural network algorithm, to obtain a trained image classification model; extracting a blood vessel color feature from the endoscopic image by using the trained image classification model; and classifying a value of the blood vessel color feature by using the trained image classification model, to determine that the endoscopic image is the white light type picture or the NBI type picture. detecting, by a colon polyp image processing apparatus, a position of a polyp in a to-be-processed endoscopic image by using a polyp positioning model, and positioning a polyp image block in the endoscopic image, the polyp image block having: a position region of the polyp in the endoscopic image; and performing, by the colon polyp image processing apparatus, a polyp type classification detection on the polyp image block by using a polyp property identification model, and outputting an identification result; characterized by before the detecting, by a colon polyp image processing apparatus, a position of a polyp in a to-be-processed endoscopic image by using a polyp positioning model, the method further comprising: identifying, by the colon polyp image processing apparatus, a picture type of the endoscopic image, and determining that the endoscopic image is a white light type picture or an endoscope narrow band imaging, NBI, type picture; wherein the identifying, by the colon polyp image processing apparatus, a picture type of the endoscopic image, and determining that the endoscopic image is a white light type picture or an endoscope NBI type picture comprises: performing classification training on an original image classification model through white light type picture training data and NBI type picture training data by using a neural network algorithm, to obtain a trained image classification model; extracting a blood vessel color feature from the endoscopic image by using the trained image classification model; and classifying a value of the blood vessel color feature by using the trained image classification model, to determine that the endoscopic image is the white light type picture or the NBI type picture.