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МВТ-02, (cv.HoughCircles(img,cv.HOUGH_GRADIENT,1,20, param1=50,param2=30…

- - - - cvtColor()
        
        void cv::cvtColor ( InputArray src, OutputArray dst, int code, int dstCn = 0 )
        
        Converts an image from one color space to another. The function converts an input image from one color space to another. In case of a transformation to-from RGB color space, the order of the channels should be specified explicitly (RGB or BGR). Note that the default color format in OpenCV is often referred to as RGB but it is actually BGR (the bytes are reversed). So the first byte in a standard (24-bit) color image will be an 8-bit Blue component, the second byte will be Green, and the third byte will be Red. The fourth, fifth, and sixth bytes would then be the second pixel (Blue, then Green, then Red), and so on. The conventional ranges for R, G, and B channel values are: 0 to 255 for CV_8U images 0 to 65535 for CV_16U images 0 to 1 for CV_32F images
      - inRange()
        
        void cv::inRange ( InputArray src, InputArray lowerb, InputArray upperb, OutputArray dst ) Python: cv.inRange( src, lowerb, upperb[, dst] ) -> dst
        
        Checks if array elements lie between the elements of two other arrays.
        
        Parameters
        
        src first input array.
        
        lowerb inclusive lower boundary array or a scalar.
        
        upperb inclusive upper boundary array or a scalar.
        
        dst output array of the same size as src and CV_8U type.
  - - - returns 3x3 perspective transformation for the corresponding 4 point pairs.
      - Mat cv::getPerspectiveTransform ( const Point2f src[], const Point2f dst[] ) Python: cv.getPerspectiveTransform( src, dst ) -> retval
  - - - Applies a fixed-level threshold to each array element. The function applies fixed-level thresholding to a multiple-channel array. The function is typically used to get a bi-level (binary) image out of a grayscale image ( compare could be also used for this purpose) or for removing a noise, that is, filtering out pixels with too small or too large values. There are several types of thresholding supported by the function. They are determined by type parameter. Also, the special values THRESH_OTSU or THRESH_TRIANGLE may be combined with one of the above values. In these cases, the function determines the optimal threshold value using the Otsu's or Triangle algorithm and uses it instead of the specified thresh.
      - Parameters
        
        src input array (multiple-channel, 8-bit or 32-bit floating point).
        
        dst output array of the same size and type and the same number of channels as src.
        
        thresh threshold value.
        
        maxval maximum value to use with the THRESH_BINARY and THRESH_BINARY_INV thresholding types.
        
        type thresholding type (see ThresholdTypes).
    - - Applies an adaptive threshold to an array.
      - Parameters
        
        src Source 8-bit single-channel image.
        
        dst Destination image of the same size and the same type as src.
        
        maxValue Non-zero value assigned to the pixels for which the condition is satisfied
        
        adaptiveMethod Adaptive thresholding algorithm to use, see AdaptiveThresholdTypes. The BORDER_REPLICATE | BORDER_ISOLATED is used to process boundaries.
        
        thresholdType Thresholding type that must be either THRESH_BINARY or THRESH_BINARY_INV, see ThresholdTypes.
        
        blockSize Size of a pixel neighborhood that is used to calculate a threshold value for the pixel: 3, 5, 7, and so on.
        
        C Constant subtracted from the mean or weighted mean (see the details below). Normally, it is positive but may be zero or negative as well.
  - - - Convolves an image with the kernel. The function applies an arbitrary linear filter to an image. In-place operation is supported. When the aperture is partially outside the image, the function interpolates outlier pixel values according to the specified border mode.
      - Parameters
        
        src input image.
        
        dst output image of the same size and the same number of channels as src.
        
        ddepth desired depth of the destination image, see combinations
        
        kernel convolution kernel (or rather a correlation kernel), a single-channel floating point matrix; if you want to apply different kernels to different channels, split the image into separate color planes using split and process them individually.
        
        anchor anchor of the kernel that indicates the relative position of a filtered point within the kernel; the anchor should lie within the kernel; default value (-1,-1) means that the anchor is at the kernel center.
        
        delta optional value added to the filtered pixels before storing them in dst.
        
        borderType pixel extrapolation method, see BorderTypes. BORDER_WRAP is not supported
  - - - morphologyEx()
        
        Parameters
        
        borderValue Border value in case of a constant border. The default value has a special meaning.
        
        borderType Pixel extrapolation method, see BorderTypes. BORDER_WRAP is not supported.
        
        iterations Number of times erosion and dilation are applied.
        
        anchor Anchor position with the kernel. Negative values mean that the anchor is at the kernel center.
        
        kernel Structuring element. It can be created using getStructuringElement.
        
        op Type of a morphological operation, see MorphTypes
        
        dst Destination image of the same size and type as source image.
        
        src Source image. The number of channels can be arbitrary. The depth should be one of CV_8U, CV_16U, CV_16S, CV_32F or CV_64F.
        
        Any of the operations can be done in-place. In case of multi-channel images, each channel is processed independently.
        
        The function cv::morphologyEx can perform advanced morphological transformations using an erosion and dilation as basic operations.
        
        Performs advanced morphological transformations.
      - dilate()
        
        Parameters
        
        borderValue border value in case of a constant border
        
        borderType pixel extrapolation method, see BorderTypes. BORDER_WRAP is not suported.
        
        iterations number of times dilation is applied.
        
        anchor position of the anchor within the element; default value (-1, -1) means that the anchor is at the element center.
        
        kernel structuring element used for dilation; if element=Mat(), a 3 x 3 rectangular structuring element is used. Kernel can be created using getStructuringElement
        
        dst output image of the same size and type as src.
        
        src input image; the number of channels can be arbitrary, but the depth should be one of CV_8U, CV_16U, CV_16S, CV_32F or CV_64F.
        
        Dilates an image by using a specific structuring element.
      - erode()
        
        Parameters
        
        borderValue border value in case of a constant border
        
        borderType pixel extrapolation method, see BorderTypes. BORDER_WRAP is not supported.
        
        iterations number of times erosion is applied.
        
        anchor position of the anchor within the element; default value (-1, -1) means that the anchor is at the element center.
        
        kernel structuring element used for erosion; if element=Mat(), a 3 x 3 rectangular structuring element is used. Kernel can be created using getStructuringElement.
        
        dst output image of the same size and type as src.
        
        src input image; the number of channels can be arbitrary, but the depth should be one of CV_8U, CV_16U, CV_16S, CV_32F or CV_64F.
        
        Erodes an image by using a specific structuring element.
- - - - cv.createTrackbar()
        
        cv.getTrackbarPos()
      - cv.line() , cv.circle() , cv.rectangle() , cv.ellipse() , cv.putText()
        
        cv.line()- функция для создания линии
        
        cv.circle() Рисование круга
        
        cv.rectangle() Рисование прямоугольника
        
        cv.ellipse() Рисование эллипса
        
        cv.putText() Добавление текста к изображениям
        
        cv.polylines() Рисование многоугольника
      - Для захвата видео необходимо создать объект cv.VideoCapture()
        
        FourCC — это 4-байтовый код, используемый для указания видеокодека
        
        мы записываем видео и обрабатываем его кадр за кадром, и мы хотим сохранить это видео. cv.VideoWriter()
      - Записать изображение в файл (используя cv::imwrite )
        
        Отображение изображения в окне OpenCV (используя cv::imshow )
        
        Прочитать изображение из файла (используя cv::imread )
      - cv.setMouseCallback() обрабатывание событии мыши. Мышь как кисть)