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  • Classic image processing algorithm library

    Basic algorithm library:
    *Split and merge image channels  *Image data bit operations, including AND, OR, NOT and XOR, etc.
    *Color space conversion, RGB<->GrayScale, RGB<->HSV, etc.
    *Image threshold binarization
    *Image smoothing, multiple filter options, Box, Gaussian, Median, Bilateral, etc.
    *Image gradient operator, Sobel, Scharr, Laplacian operators
    *Image morphological transformation, corrosion, expansion, opening and closing operation
    *Geometric transformation: translation, scaling, rotation, affine, etc.
    Application algorithm library:
    *Canny edge detection
    *Image contour extraction and contour feature analysis
    *Histogram equalization and back projection *Feature point extraction and matching

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  • Deep learning algorithm library

    Deep learning algorithm library:
    * Implementation and optimization of reasoning end algorithm library for deep learning
    *Network reading, load Caffe network from the model or read network through ONNX
    *Generate input image Blob data
    *Feed forward according to the layer corresponding to the preloaded network structure*Classified output
    *Deep learning application algorithm library:
    * OCR
    *Item identification and classification, YOLOv3-DARKNET

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