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 (30, 31) 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 (30, 31) by applying image processing to the captured image (30, 31) 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 (30, 31) by applying said image processing to the captured image (30, 31), 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 (30, 31) 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 (30, 31), and detect the respective residual amounts of yarns of said plural yarn cones (2, 2A-2E), one by one, in the captured image (30, 31), 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 (30, 31) 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 (30, 31) by applying image processing to the captured image (30, 31) 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 (30, 31) by applying said image processing to the captured image (30, 31), 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 (30, 31) 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 (30, 31), and detect the respective residual amounts of yarns of said plural yarn cones (2, 2A-2E), one by one, in the captured image (30, 31), 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 (30, 31) 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 (30, 31), and detect the respective residual amounts of yarns of said plural yarn cones (2, 2A-2E), one by one, in the captured image (30, 31), 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.