opencv - haskell-opencv 中的 GaussianBlurImage(Haskell 绑定(bind)到 OpenCV-3.1)

Question

啊!

我正在使用 haskell-opencv图书馆。我不知道是否有其他人在使用它，或者对它有所了解。

我尝试使用 gaussianBlurImage，但出现了一个我无法识别的错误。

我有这个:

cropped image = do 
     resized <- resizeImage image
     gaussianBlurred <- gaussianBlurImage ((M.unsafeCoerceMat . getImageFromEither) resized)

resized 是 Either CV.Exception (M.Mat shape channels depth) 我从这里得到 ((M.unsafeCoerceMat . getImageFromEither) resized ) 一个 Mat shape (S channels) (S depth) as gaussianBlurImage function needs.

我定义的 gaussianBlurImage 是这样的:

gaussianBlurImage image = runExceptT $ CV.pureExcept $ CV.gaussianBlur (V2 13 13::V2 Int32) 0 0 图像

对我来说，它看起来不错。与此处类似:blur .但是我得到这个错误:

Couldn't match expected type ‘'True’ with actual type ‘Elem depth0 '[Word8, Word16, Float, Double]’

我注意到，我的 gaussianBlurImage 有这种类型:

gaussianBlurImage :: (M.Mat shape0 ('S channels0) ('S depth0)) -> Either CV.CvException (Either CV.CvException (M.Mat shape0 ('S channels0) ('S depth0)))

我喜欢这个:

gaussianBlurImage :: (M.Mat shape0 ('S channels0) ('S depth0)) -> Either CV.CvException (M.Mat shape0 ('S channels0) ('S depth0))

也许它有什么作用。

我用 medianBlur、blur 和 gaussianBlur 试过了。我使用了一个未调整大小的图像，一个具有三个 channel 的图像和另一个具有 2 个 channel (颜色和灰色)的图像，但我总是遇到相同的错误。我想知道错误是否在 M.unsafeCoerceMat image 中。为什么 'True 是预期的类型？我不知道

Answer 1

haskell-opencv是一个优秀的库，但有时很难使用，因为有很多文档，但很难理解，而且没有太多示例。

在那里，每个模糊函数都需要一个(M.Mat shape ('S channels) ('S depth))矩阵，但矩阵通常是这样的:(M.Mat shape channel 深度)，其中 'S 表示它是静态的。

我使用这个函数:

M.coerceMat 有这样一个矩阵。

coerceMAt :: (ToShapeDS (Proxy shapeOut), ToChannelsDS (Proxy 
    channelsOut), ToDepthDS (Proxy depthOut))    
    => Mat shapeIn channelsIn depthIn    
    -> CvExcept (Mat shapeOut channelsOut depthOut)

当它返回 CVExcept 时，我使用 exceptError::CvExcept a -> a 来获取图像。

但最重要的是函数的定义。我的代码有问题。depth 不能含糊不清，这就是我写的原因:

forall height0 width0 channels depth . ( depth `In` '[Word8, Word16, Float, Double] , channels `In` '[1, 3, 4]) => M.Mat ('S '[height0, width0]) ('S channels) ('S depth) -> IO (M.Mat ('S '[height0, width0]) ('S channels) ('S depth))

这是一个完整的例子。我得到一张图片，调整它的大小，模糊它并显示它。

主要内容:

module Main where

import Lib
import qualified OpenCV.Internal.Core.Types.Mat as M
import Control.Monad ( void )
import qualified OpenCV as CV
import qualified Data.ByteString as B

main :: IO ()
main = do
    test <- controller
    CV.withWindow "test" $ \window -> do
        CV.imshow window test  
        void $ CV.waitKey 10000

库:

{-# LANGUAGE TypeFamilies #-}

module Lib
    ( controller
    ) where

import BlurImage
import ResizeImage
import Utils
import Control.Monad ( void )
import Data.Word
import qualified OpenCV.Internal.Core.Types.Mat as M
import qualified OpenCV as CV
import qualified Data.ByteString as B

controller :: IO (CV.Mat (CV.S '[CV.D, CV.D]) (CV.S 1) (CV.S Word8))
controller = do
    file <- B.readFile "path/to/image.jpg"
    img <- return $ CV.imdecode CV.ImreadGrayscale file
    resized_little_img <- resizeImage img --little image for making a blur in and find the receipt
    blurImage ((CV.exceptError $ M.coerceMat resized_little_img) :: M.Mat (CV.S '[ CV.D, CV.D]) (CV.S 1) (CV.S Word8))

调整图像大小:

{-# LANGUAGE TypeFamilies #-}
{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE AllowAmbiguousTypes #-}

module ResizeImage
    ( 
    resizeImage
    ) where

import Utils
import Control.Monad ( void )
import Control.Monad.Except
import Data.Functor.Identity
import Data.Word
import Data.Proxy
import qualified OpenCV as CV
import Linear.V2
import OpenCV.TypeLevel
import qualified OpenCV.Internal.Core.Types.Mat as M
import qualified OpenCV.Core.Types.Size as S
import qualified OpenCV.ImgProc.GeometricImgTransform as GIT
import GHC.Int (Int32)

resizingImage :: (M.Mat (CV.S [CV.D, CV.D]) CV.D CV.D) -> CV.CvExcept (M.Mat (CV.S [CV.D, CV.D]) CV.D CV.D)
resizingImage image = GIT.resize (GIT.ResizeAbs $ S.toSize $ (getSize w h Nothing (Just 500))) CV.InterCubic image
    where
        [h, w] = getHandW image

resizeImage :: (M.Mat (S '[CV.D, CV.D]) CV.D CV.D) -> IO(M.Mat (CV.S [CV.D, CV.D]) CV.D CV.D)
resizeImage image = do        
    resized <- return $ resizingImage image
    return $ CV.exceptError $ resized

模糊图像:

{-# LANGUAGE TypeFamilies #-}
{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE AllowAmbiguousTypes #-}

module BlurImage
    ( 
    blurImage
    ) where

import Utils
import Control.Monad ( void )
import Control.Monad.Except
import qualified Data.ByteString as B
import Data.Word
import Data.Proxy
import qualified OpenCV as CV
import Linear.V2
import OpenCV.TypeLevel
import qualified OpenCV.Internal.Core.Types.Mat as M
import qualified OpenCV.Core.Types.Size as S
import qualified OpenCV.ImgProc.GeometricImgTransform as GIT
import GHC.Int (Int32)


medianBlurImage :: (depth `In` '[Word8, Word16, Float], channels `In` '[1, 3, 4]) => (M.Mat shape ('S channels) ('S depth)) -> CV.CvExcept (M.Mat shape ('S channels) ('S depth)) 
medianBlurImage image = CV.medianBlur image 13 

gaussianBlurImage :: (depth `In` '[Word8, Word16, Float, Double], channels `In` '[1, 3, 4]) => (M.Mat shape ('S channels) ('S depth)) -> CV.CvExcept (M.Mat shape ('S channels) ('S depth)) 
gaussianBlurImage image = CV.gaussianBlur (V2 13 13 :: V2 Int32) 0 0 image

blurImage :: forall height0 width0 channels depth . ( depth `In` '[Word8, Word16, Float, Double] , channels `In` '[1, 3, 4]) => M.Mat ('S '[height0, width0]) ('S channels) ('S depth) -> IO (M.Mat ('S '[height0, width0]) ('S channels) ('S depth))
blurImage image = do
    gaussianBlurred   <- return $ gaussianBlurImage image     
    return $ CV.exceptError $ gaussianBlurred

就是这样。 :) 我希望它可以帮助别人。