Image segmentation method and device, electronic equipment and storage medium
An image segmentation and image technology, applied in the fields of deep learning, computer vision, and artificial intelligence, can solve the problems of high cost of manual labeling, no solution proposed, and low efficiency, and achieve the goals of reducing labeling costs, solving low efficiency, and improving accuracy Effect
Pending Publication Date: 2022-02-18
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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Therefore, there are problems of high cost and low efficiency of manual labeling
[0004]
For the above problems, no effective solution has been proposed
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[0019] Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
[0020] In order to solve the technical problems of low efficiency and high cost of manual labeling in the prior art, the present disclosure provides an image segmentation method, which uses a training image and a mask generated by the detection result of the training sample through the target detection model The image segmentation model obtained by information training ...
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The invention provides an image segmentation method and device, electronic equipment and a storage medium, and relates to the field of artificial intelligence, in particular to the technical field of deep learning and computer vision.According to the implementation scheme, the method: acquiring a to-be-segmented image; segmenting the to-be-segmented image by using the image segmentation model to obtain a segmentation result, the image segmentation model being obtained by training a training sample and mask information of the training sample, and the mask information being generated by a detection result obtained by detecting the training sample by using the target detection model. The target detection model is used for detecting the training sample to obtain the detection result, then the mask information is generated, the training sample and the mask information are used for training the image segmentation model, pixel-level labeling of the training sample does not need to be carried out through a manual labeling mode, and therefore the purposes of reducing the labeling cost of the image segmentation model and improving the precision of the segmentation result, and the problems of low manual labeling efficiency and high cost in the prior art are solved.
Description
technical field [0001] The present disclosure relates to the field of artificial intelligence, specifically to the technical fields of deep learning and computer vision, and in particular to an image segmentation method, device, electronic equipment and storage medium. Background technique [0002] In industrial quality inspection or patrol inspection, the inspection of parts can help manufacturers detect whether parts are missing or damaged. However, due to the dense area of parts and the small size of parts, manual inspection has higher requirements for inspectors. . [0003] Therefore, with the development of technology, artificial intelligence models are usually used for detection nowadays, but before the above-mentioned models are detected, a large amount of data labeling is required for the training of the model. Therefore, there are problems of high cost and low efficiency of manual labeling. [0004] For the above problems, no effective solution has been proposed...
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Login to View More IPC IPC(8): G06T7/10G06T7/00G06V10/764G06V10/774G06V10/82G06K9/62
CPCG06T7/10G06T7/0004G06T2207/30164G06T2207/20081G06T2207/20084G06F18/241G06F18/214
Inventor 李超辛颖薛松王云浩张滨冯原彭岩韩树民
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD