Image recognition method and device, electronic equipment and storage medium
An image recognition and panoramic image technology, applied in the field of deep learning, can solve problems such as information gaps, low recall rate of target detection, and inability to learn semantic information of panoramic images, so as to achieve the effect of improving the recall rate
Pending Publication Date: 2022-06-28
SHENZHEN ARASHI VISION CO LTD
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[0003] However, the existing image detection models can only perform feature extraction in the form of a planar image, and cannot learn the semantic information of the panoramic image, resulting in information faults, and will detect the same object located on two boundaries as two different objects. , so that the target detection recall rate is low, therefore, there is an urgent need for an image detection method that can learn the semantic information of the panorama and improve the target detection recall rate
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[0028] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of this application.
[0029] Embodiments of the present application provide an image recognition method, apparatus, electronic device, and storage medium.
[0030] Wherein, the image recognition apparatus may be specifically integrated in an electronic device, and the electronic device may be a terminal, a server, or the like. The terminal may be a mobile phone, a tablet computer, an intelligent Bluetooth device, a notebook computer, or a personal computer (Personal Computer, PC) an...
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The embodiment of the invention discloses an image recognition method and device, electronic equipment and a storage medium. According to the embodiment of the invention, a panoramic image and a convolution window are obtained, the panoramic image comprises a first boundary and a second boundary, and the first boundary is parallel to the second boundary; determining a first target area in the panoramic image based on the position between the convolution window and the first boundary; a convolution window is adopted to carry out convolution processing on data in the first target area and a second target area to obtain a convolution value, and the second target area is a corresponding area when the convolution window intersects with the first boundary on the panoramic image; and performing target object identification on the panoramic image based on the convolution value to obtain an identification result of the target object. In the embodiment of the invention, the data in the first target area can be associated with the data in the second target area during convolution, so that the semantic information of the panoramic image can be learned, and the target detection recall rate is improved.
Description
technical field [0001] The present application relates to the technical field of deep learning, and in particular, to an image recognition method, apparatus, electronic device and storage medium. Background technique [0002] The panoramic image stitched from multiple images records all the information of 360 degrees in a certain direction in the shooting scene. Although the panoramic image has been projected into a plan view, the panorama expanded in a plane is about the scene of the two borders in the 360-degree direction. The content is associative, and the semantics of its content expression is still panoramic. [0003] However, the existing image detection model can only perform feature extraction in the way of a plan view, and cannot learn the semantic information of the panorama, resulting in information faults, and the same target located on the two boundaries will be detected as two different targets. , which makes the target detection recall rate low. Therefore, a...
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IPC IPC(8): G06V20/10
Inventor 侯俊肖龙报林晓帆
Owner SHENZHEN ARASHI VISION CO LTD