{-# language QuasiQuotes #-} {-# language TemplateHaskell #-} {-# language MultiParamTypeClasses #-} module OpenCV.ImgProc.CascadeClassifier ( CascadeClassifier , newCascadeClassifier , cascadeClassifierDetectMultiScale , cascadeClassifierDetectMultiScaleNC ) where import "base" Data.Int import "base" Foreign.ForeignPtr (ForeignPtr, withForeignPtr) import "base" Foreign.C.String (withCString) import "base" System.IO.Unsafe (unsafePerformIO) import "base" Data.Word import "base" Foreign.Marshal.Alloc (alloca) import "base" Foreign.Ptr (Ptr) import "base" Control.Exception (mask_) import "base" Foreign.Storable (peek) import "base" Foreign.Marshal.Array (peekArray) import qualified "inline-c" Language.C.Inline as C import qualified "inline-c" Language.C.Inline.Unsafe as CU import qualified "inline-c-cpp" Language.C.Inline.Cpp as C import qualified "vector" Data.Vector as V import "linear" Linear (V2(..)) import "this" OpenCV.Core.Types import "this" OpenCV.Internal.C.Inline ( openCvCtx ) import "this" OpenCV.Internal.C.Types import "this" OpenCV.Internal import "this" OpenCV.TypeLevel C.context openCvCtx C.include "opencv2/core.hpp" C.include "opencv2/objdetect.hpp" C.using "namespace cv" newtype CascadeClassifier = CascadeClassifier {unCascadeClassifier :: ForeignPtr (C CascadeClassifier)} type instance C CascadeClassifier = C'CascadeClassifier instance WithPtr CascadeClassifier where withPtr = withForeignPtr . unCascadeClassifier instance FromPtr CascadeClassifier where fromPtr = objFromPtr CascadeClassifier $ \ptr -> [CU.exp| void { delete $(CascadeClassifier * ptr) }|] -- | 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.) newCascadeClassifier :: FilePath -> IO (Maybe CascadeClassifier) newCascadeClassifier fp = do cc <- withCString fp $ \c'fp -> fromPtr [CU.exp| CascadeClassifier * { new CascadeClassifier(cv::String($(const char * c'fp))) } |] -- TODO: empty() seems to return bogus numbers when the classifier is not -- empty, and I'm not sure why. This is also why I'm not using toBool. empty <- fmap (== 1) (withPtr cc (\ccPtr -> [CU.exp| bool { $(CascadeClassifier * ccPtr)->empty() } |])) return $ if empty then Nothing else Just cc {- | 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) @ <> -} cascadeClassifierDetectMultiScale :: (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) -> V.Vector (Rect Int32) cascadeClassifierDetectMultiScale cc scaleFactor minNeighbours minSize maxSize src = unsafePerformIO $ withPtr cc $ \ccPtr -> withPtr src $ \srcPtr -> withPtr c'minSize $ \minSizePtr -> withPtr c'maxSize $ \maxSizePtr -> alloca $ \(numRectsPtr :: Ptr Int32) -> alloca $ \(rectsPtrPtr :: Ptr (Ptr (Ptr (C'Rect Int32)))) -> mask_ $ do [CU.block| void { std::vector rects; $(CascadeClassifier * ccPtr)->detectMultiScale( *$(Mat * srcPtr), rects, $(double c'scaleFactor), $(int32_t c'minNeighbours), 0, *$(Size2i * minSizePtr), *$(Size2i * maxSizePtr)); *$(int32_t * numRectsPtr) = rects.size(); cv::Rect * * rectsPtr = new cv::Rect * [rects.size()]; *$(Rect2i * * * rectsPtrPtr) = rectsPtr; for (std::vector::size_type i = 0; i != rects.size(); i++) { rectsPtr[i] = new cv::Rect(rects[i]); } } |] numRects <- fromIntegral <$> peek numRectsPtr rectsPtr <- peek rectsPtrPtr rects :: [Rect Int32] <- peekArray numRects rectsPtr >>= mapM (fromPtr . return) [CU.block| void { delete [] *$(Rect2i * * * rectsPtrPtr); }|] return (V.fromList rects) where c'scaleFactor = maybe 1.1 realToFrac scaleFactor c'minNeighbours = maybe 3 fromIntegral minNeighbours c'minSize = maybe (toSize (V2 0 0)) toSize minSize c'maxSize = maybe (toSize (V2 0 0)) toSize maxSize {- | Special version which returns bounding rectangle, rejectLevels, and levelWeights -} cascadeClassifierDetectMultiScaleNC :: (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) -> V.Vector (Rect Int32, Int32, Double) cascadeClassifierDetectMultiScaleNC cc scaleFactor minNeighbours minSize maxSize src = unsafePerformIO $ withPtr cc $ \ccPtr -> withPtr src $ \srcPtr -> withPtr c'minSize $ \minSizePtr -> withPtr c'maxSize $ \maxSizePtr -> alloca $ \(numRectsPtr :: Ptr Int32) -> alloca $ \(rectsPtrPtr :: Ptr (Ptr (Ptr (C'Rect Int32)))) -> alloca $ \(rejectLevelsPtrPtr :: Ptr (Ptr Int32)) -> alloca $ \(levelWeightsPtrPtr :: Ptr (Ptr C.CDouble)) -> mask_ $ do [CU.block| void { std::vector rects; std::vector rejectLevels; std::vector levelWeights; $(CascadeClassifier * ccPtr)->detectMultiScale( *$(Mat * srcPtr), rects, rejectLevels, levelWeights, $(double c'scaleFactor), $(int32_t c'minNeighbours), 0, *$(Size2i * minSizePtr), *$(Size2i * maxSizePtr), true); *$(int32_t * numRectsPtr) = rects.size(); cv::Rect * * rectsPtr = new cv::Rect * [rects.size()]; *$(Rect2i * * * rectsPtrPtr) = rectsPtr; int32_t * rejectLevelsPtr = new int32_t [rejectLevels.size()]; *$(int32_t * * rejectLevelsPtrPtr) = rejectLevelsPtr; double * levelWeightsPtr = new double [levelWeights.size()]; *$(double * * levelWeightsPtrPtr) = levelWeightsPtr; for (std::vector::size_type i = 0; i != rects.size(); i++) { rectsPtr[i] = new cv::Rect(rects[i]); rejectLevelsPtr[i] = rejectLevels[i]; levelWeightsPtr[i] = levelWeights[i]; } } |] numRects <- fromIntegral <$> peek numRectsPtr rectsPtr <- peek rectsPtrPtr rejectLevelsPtr <- peek rejectLevelsPtrPtr levelWeightsPtr <- peek levelWeightsPtrPtr rects :: [Rect Int32] <- peekArray numRects rectsPtr >>= mapM (fromPtr . return) rejectLevels :: [Int32] <- peekArray numRects rejectLevelsPtr -- >>= mapM (fromPtr . return) levelWeights :: [Double] <- map realToFrac <$> peekArray numRects levelWeightsPtr [CU.block| void { delete [] *$(Rect2i * * * rectsPtrPtr); delete [] *$(int32_t * * rejectLevelsPtrPtr); delete [] *$(double * * levelWeightsPtrPtr); }|] return (V.fromList $ zip3 rects rejectLevels levelWeights) where c'scaleFactor = maybe 1.1 realToFrac scaleFactor c'minNeighbours = maybe 3 fromIntegral minNeighbours c'minSize = maybe (toSize (V2 0 0)) toSize minSize c'maxSize = maybe (toSize (V2 0 0)) toSize maxSize