Image recognition method and apparatus, electronic device, and computer-readable medium

An electronic device, comprising:

• one or more processors;
• and
• a storage apparatus storing one or more programs;
• wherein
• when the one or more programs are executed by the one or more processors, the one or more processors implement operations comprising:
• obtaining a target image;
• determining a probability that each pixel point in the target image belongs to each of at least three target categories, wherein the at least three target categories comprise a category of face region, a category of mouth region, and a category of non-face background, and wherein the determining a probability that each pixel point in the target image belongs to each of at least three target categories comprises:
• determining a first probability of each pixel point in the target image belonging to the category of face region,
• determining a second probability of each pixel point in the target image belonging to the category of mouth region, and
• determining a third probability of each pixel in the target image belonging to the category of non-face background;
• generating at least three probability graphs based on the first probability, the second probability, and the third probability of each pixel point in the target image belonging to the category of face region, the category of mouth region, and the category of non-face background, respectively;
• and
• determining a category of each pixel point in the target image based on the at least three probability graphs to improve an accuracy of recognizing an edge of a mouth in the target image.

A non-transitory computer-readable medium storing computer programs, wherein the programs implement operations when executed by the processors, the operations comprising:

• obtaining a target image;
• determining a probability that each pixel point in the target image belongs to each of at least three target categories, wherein the at least three target categories comprise a category of face region, a category of mouth region, and a category of non-face background, and wherein the determining a probability that each pixel point in the target image belongs to each of at least three target categories comprises:
• determining a first probability of each pixel point in the target image belonging to the category of face region,
• determining a second probability of each pixel point in the target image belonging to the category of mouth region, and
• determining a third probability of each pixel in the target image belonging to the category of non-face background;
• generating at least three probability graphs based on the first probability, the second probability, and the third probability of each pixel point in the target image belonging to the category of face region, the category of mouth region, and the category of non-face background, respectively;
• and
• determining a category of each pixel point in the target image based on the at least three probability graphs to improve an accuracy of recognizing an edge of a mouth in the target image.