An image processing device configured to detect respective statuses of plural yarn cones (2, 2A-2E), arranged on a knitting machine main body or at a periphery of the knitting machine main body, characterized by an acquisition unit for acquiring a captured image including plural yarn cones (2, 2A-2E), arranged on the knitting machine main body or at a periphery of the knitting machine main body; and a yarn cone status detection unit for detecting respective statuses of the plural yarn cones (2, 2A-2E) included in the captured image by applying image processing to the captured image acquired by the acquisition unit , wherein said yarn cone status detection unit is configured to detect respective residual amounts of yarns of the plural yarn cones (2, 2A-2E) in the captured image by applying said image processing to the captured image , and wherein said yarn cone status detection unit is configured to: identify plural regions (A-E) enclosing one yarn cone respectively, by inputting said captured image acquired by the acquisition unit to a first learned model (5B1) which has machine-learned the correlation between a cone image including one yarn cone and the regions (A-E) respectively enclosing one yarn cone of the plural yarn cones (2, 2A-2E) in the captured image , and detect the respective residual amounts of yarns of said plural yarn cones (2, 2A-2E), one by one, in the captured image , by inputting the cone image including said one yarn cone to a second learned model (5A, 5B2) which has machine-learned the correlation between the cone image including one yarn cone and the residual amount of yarn of the yarn cone in the cone image . an acquisition unit for acquiring a captured image including plural yarn cones (2, 2A-2E), arranged on the knitting machine main body or at a periphery of the knitting machine main body; and a yarn cone status detection unit for detecting respective statuses of the plural yarn cones (2, 2A-2E) included in the captured image by applying image processing to the captured image acquired by the acquisition unit , wherein said yarn cone status detection unit is configured to detect respective residual amounts of yarns of the plural yarn cones (2, 2A-2E) in the captured image by applying said image processing to the captured image , and wherein said yarn cone status detection unit is configured to: identify plural regions (A-E) enclosing one yarn cone respectively, by inputting said captured image acquired by the acquisition unit to a first learned model (5B1) which has machine-learned the correlation between a cone image including one yarn cone and the regions (A-E) respectively enclosing one yarn cone of the plural yarn cones (2, 2A-2E) in the captured image , and detect the respective residual amounts of yarns of said plural yarn cones (2, 2A-2E), one by one, in the captured image , by inputting the cone image including said one yarn cone to a second learned model (5A, 5B2) which has machine-learned the correlation between the cone image including one yarn cone and the residual amount of yarn of the yarn cone in the cone image . identify plural regions (A-E) enclosing one yarn cone respectively, by inputting said captured image acquired by the acquisition unit to a first learned model (5B1) which has machine-learned the correlation between a cone image including one yarn cone and the regions (A-E) respectively enclosing one yarn cone of the plural yarn cones (2, 2A-2E) in the captured image , and detect the respective residual amounts of yarns of said plural yarn cones (2, 2A-2E), one by one, in the captured image , by inputting the cone image including said one yarn cone to a second learned model (5A, 5B2) which has machine-learned the correlation between the cone image including one yarn cone and the residual amount of yarn of the yarn cone in the cone image . <EOS>