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Object detection is extensively utilized in robotic navigation, clever video surveillance, industrial inspection, aerospace and lots of other fields. It is an important branch of picture processing and pc imaginative and prescient disciplines, and can also be the core part of clever surveillance systems. At the same time, target detection is also a fundamental algorithm in the sector of pan-identification, which plays a significant role in subsequent tasks reminiscent of face recognition, iTagPro online gait recognition, ItagPro crowd counting, and occasion segmentation. After the first detection module performs goal detection processing on the video body to obtain the N detection targets within the video frame and the first coordinate info of every detection goal, the above methodology It also consists of: displaying the above N detection targets on a screen. The first coordinate information corresponding to the i-th detection target; acquiring the above-talked about video body; positioning within the above-mentioned video frame in keeping with the first coordinate data corresponding to the above-talked about i-th detection goal, obtaining a partial image of the above-talked about video frame, and determining the above-talked about partial picture is the i-th image above.

The expanded first coordinate info corresponding to the i-th detection goal; the above-mentioned first coordinate data corresponding to the i-th detection target is used for positioning in the above-talked about video body, together with: in accordance with the expanded first coordinate info corresponding to the i-th detection goal The coordinate info locates within the above video body. Performing object detection processing, if the i-th picture includes the i-th detection object, buying position info of the i-th detection object in the i-th image to acquire the second coordinate information. The second detection module performs target detection processing on the jth picture to determine the second coordinate data of the jth detected goal, itagpro tracker the place j is a positive integer not larger than N and not equal to i. Target detection processing, obtaining multiple faces in the above video frame, and first coordinate information of each face; randomly acquiring target faces from the above a number of faces, and intercepting partial pictures of the above video body in line with the above first coordinate info ; performing goal detection processing on the partial image through the second detection module to obtain second coordinate information of the target face; displaying the target face in line with the second coordinate info.

Display a number of faces within the above video frame on the display. Determine the coordinate checklist in response to the first coordinate information of each face above. The first coordinate info corresponding to the goal face; acquiring the video body; and positioning in the video frame in keeping with the first coordinate information corresponding to the goal face to acquire a partial picture of the video body. The extended first coordinate info corresponding to the face; the above-mentioned first coordinate data corresponding to the above-mentioned goal face is used for positioning in the above-talked about video frame, including: based on the above-talked about extended first coordinate info corresponding to the above-mentioned target face. Within the detection course of, if the partial image includes the goal face, acquiring place information of the target face in the partial picture to obtain the second coordinate info. The second detection module performs target detection processing on the partial image to determine the second coordinate data of the opposite target face.