Image base establishment method and system, image base and image classification method
A technology for establishing methods and image libraries, applied in character and pattern recognition, special data processing applications, instruments, etc., can solve problems such as uneven labeling quality, and achieve the effect of improving purity and increasing professionalism
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[0062] figure 1 It is the flow chart of embodiment 1 of the establishment method of the image library of the present invention, such as figure 1 As shown, the method for establishing the image library includes:
[0063] Step 101, acquiring an image to be labeled;
[0064] Step 102, determine the initial label of the image according to the image recognition algorithm, specifically including:
[0065] Step A1, extracting feature information of the image;
[0066] Step A2, comparing the feature information with the image reference feature information in the feature library to obtain a comparison result;
[0067] Step A3, determining the initial label of the image according to the comparison result, specifically: assigning the label of the image in the feature library to the image to be labeled when the comparison result satisfies a certain preset condition.
[0068] We choose ImageNet-1K as the training sample. ImageNet-1K is currently a recognized image classification datase...
Embodiment approach
[0078] The specific implementation method is: for each picture to be tagged, first obtain 10 initial tags by using the image recognition algorithm in the background, and then push this picture to multiple users together with the 10 initial tags.
[0079] Users can select several ideal tags from 10 given initial tags and submit them to the background.
[0080] Users can also enter custom text content in the input field and submit it to the background. The backstage is based on a certain word segmentation strategy (such as the longest match of dictionary strings) to segment the user-defined input text content. For example, the user input is "running puppy", and the result of word segmentation is "running", "of", "little dog"; the user input is "naughty teddy dog", and the result of word segmentation is "naughty", "of" ","Teddy dog".
[0081] After collecting word segmentation results (repeatable) to a certain number N (N>=30) in the word segmentation result pool, use word2vec ...
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