OpenCV.ImgProc.CascadeClassifier

Documentation

data CascadeClassifier

Instances

FromPtr CascadeClassifier

Methods

fromPtr :: IO (Ptr (C CascadeClassifier)) -> IO CascadeClassifier

WithPtr CascadeClassifier

Methods

withPtr :: CascadeClassifier -> (Ptr (C CascadeClassifier) -> IO b) -> IO b

newCascadeClassifier :: FilePath -> IO (Maybe CascadeClassifier)

Create a new cascade classifier. Returns Nothing if the classifier is empty after initialization. This usually means that the file could not be loaded (e.g. it doesn't exist, is corrupt, etc.)

cascadeClassifierDetectMultiScale

Arguments

:: IsSize size Int32

=> CascadeClassifier

-> Maybe Double

Scale factor, default is 1.1

-> Maybe Int32

Min neighbours, default 3

-> Maybe (size Int32)

Minimum size. Default: no minimum.

-> Maybe (size Int32)

Maximum size. Default: no maximum.

-> Mat (S '[w, h]) (S 1) (S Word8)

-> Vector (Rect Int32)

Example:

cascadeClassifierArnold
  :: forall (width    :: Nat)
            (height   :: Nat)
            (channels :: Nat)
            (depth    :: *  )
   . (Mat (ShapeT [height, width]) ('S channels) ('S depth) ~ Arnold_small)
  => IO (Mat (ShapeT [height, width]) ('S channels) ('S depth))
cascadeClassifierArnold = do
    -- Create two classifiers from data files.
    Just ccFrontal <- newCascadeClassifier "data/haarcascade_frontalface_default.xml"
    Just ccEyes    <- newCascadeClassifier "data/haarcascade_eye.xml"
    -- Detect some features.
    let eyes  = ccDetectMultiscale ccEyes    arnoldGray
        faces = ccDetectMultiscale ccFrontal arnoldGray
    -- Draw the result.
    pure $ exceptError $
      withMatM (Proxy :: Proxy [height, width])
               (Proxy :: Proxy channels)
               (Proxy :: Proxy depth)
               white $ \imgM -> do
        void $ matCopyToM imgM (V2 0 0) arnold_small Nothing
        forM_ eyes  $ \eyeRect  -> lift $ rectangle imgM eyeRect  blue  2 LineType_8 0
        forM_ faces $ \faceRect -> lift $ rectangle imgM faceRect green 2 LineType_8 0
  where
    arnoldGray = exceptError $ cvtColor bgr gray arnold_small

    ccDetectMultiscale cc = cascadeClassifierDetectMultiScale cc Nothing Nothing minSize maxSize

    minSize = Nothing :: Maybe (V2 Int32)
    maxSize = Nothing :: Maybe (V2 Int32)

cascadeClassifierDetectMultiScaleNC

Arguments

:: IsSize size Int32

=> CascadeClassifier

-> Maybe Double

Scale factor, default is 1.1

-> Maybe Int32

Min neighbours, default 3

-> Maybe (size Int32)

Minimum size. Default: no minimum.

-> Maybe (size Int32)

Maximum size. Default: no maximum.

-> Mat (S '[w, h]) (S 1) (S Word8)

-> Vector (Rect Int32, Int32, Double)

Special version which returns bounding rectangle, rejectLevels, and levelWeights