Changelog plus tidy of code/docs for convolve operation

docs/api.md

@@ -383,18 +383,27 @@ When a `sigma` is provided, performs a slower, more accurate Gaussian blur. This
 
 #### convolve(kernel)
 
-Convolve the image with the specified `kernel`. The kernel specification takes the following form:
+Convolve the image with the specified `kernel`, an Object with the following attributes:
 
-* `kernel = `
-  `{ 'width': N`
-  `, 'height': M`
-  `, 'scale': Z`
-  `, 'offset': Y`
-  `, 'kernel':`
-  `   [ 1, 2, 3,`
-  `     4, 5, 6,`
-  `     7, 8, 9 ]`
-  `}`
+* `width` is an integral Number representing the width of the kernel in pixels.
+* `height` is an integral Number representing the width of the kernel in pixels.
+* `kernel` is an Array of length `width*height` containing the kernel values.
+* `scale`, if present, is a Number representing the scale of the kernel in pixels, defaulting to the sum of the kernel's values.
+* `offset`, if present, is a Number representing the offset of the kernel in pixels, defaulting to 0.
+
+```javascript
+sharp(input)
+  .convolve({
+    width: 3,
+    height: 3,
+    kernel: [-1, 0, 1, -2, 0, 2, -1, 0, 1]
+  })
+  .raw()
+  .toBuffer(function(err, data, info) {
+    // data contains the raw pixel data representing the input image
+    // convolved with the horizontal Sobel operator
+  });
+```
 
 #### sharpen([sigma], [flat], [jagged])
 

docs/changelog.md

@@ -30,6 +30,10 @@ Requires libvips v8.3.1
   [#456](https://github.com/lovell/sharp/pull/456)
   [@kapouer](https://github.com/kapouer)
 
+* Add convolve operation for kernel-based convolution.
+  [#479](https://github.com/lovell/sharp/pull/479)
+  [@mhirsch](https://github.com/mhirsch)
+
 * Add greyscale option to threshold operation for colourspace conversion control.
   [#480](https://github.com/lovell/sharp/pull/480)
   [@mhirsch](https://github.com/mhirsch)

index.js

@@ -450,18 +450,7 @@ Sharp.prototype.blur = function(sigma) {
 
 /*
   Convolve the image with a kernel.
-  Call with an object of the following form:
-  { 'width': N
-  , 'height': M
-  , 'scale': Z
-  , 'offset': Y
-  , 'kernel':
-             [ 1, 2, 3,
-               4, 5, 6,
-               7, 8, 9 ]
-  }
 */
-
 Sharp.prototype.convolve = function(kernel) {
   if (!isDefined(kernel) || !isDefined(kernel.kernel) ||
       !isDefined(kernel.width) || !isDefined(kernel.height) ||

src/operations.cc

@@ -215,8 +215,10 @@ namespace sharp {
   /*
    * Convolution with a kernel.
    */
-  VImage Convolve(VImage image, int width, int height, double scale, double offset,
-                  const std::unique_ptr<double[]> &kernel_v) {
+  VImage Convolve(VImage image, int const width, int const height,
+    double const scale, double const offset,
+    std::unique_ptr<double[]> const &kernel_v
+  ) {
     VImage kernel = VImage::new_from_memory(
       kernel_v.get(),
       width * height * sizeof(double),

src/operations.h

@@ -38,8 +38,8 @@ namespace sharp {
   /*
    * Convolution with a kernel.
    */
-  VImage Convolve(VImage image, int width, int height, double scale, double offset,
-                  const std::unique_ptr<double[]> &kernel_v);
+  VImage Convolve(VImage image, int const width, int const height,
+    double const scale, double const offset, std::unique_ptr<double[]> const &kernel_v);
 
   /*
    * Sharpen flat and jagged areas. Use sigma of -1.0 for fast sharpen.

src/pipeline.cc

@@ -640,9 +640,10 @@ class PipelineWorker : public AsyncWorker {
       // Convolve
       if (shouldConv) {
         image = Convolve(image,
-                            baton->convKernelWidth, baton->convKernelHeight,
-                            baton->convKernelScale, baton->convKernelOffset,
-                            baton->convKernel);
+          baton->convKernelWidth, baton->convKernelHeight,
+          baton->convKernelScale, baton->convKernelOffset,
+          baton->convKernel
+        );
       }
 
       // Sharpen
@@ -1165,13 +1166,12 @@ NAN_METHOD(pipeline) {
   // Convolution Kernel
   if(Has(options, New("convKernel").ToLocalChecked()).FromJust()) {
     Local<Object> kernel = Get(options, New("convKernel").ToLocalChecked()).ToLocalChecked().As<Object>();
-    baton->convKernelWidth = attrAs<int32_t>(kernel, "width");
-    baton->convKernelHeight = attrAs<int32_t>(kernel, "height");
+    baton->convKernelWidth = attrAs<uint32_t>(kernel, "width");
+    baton->convKernelHeight = attrAs<uint32_t>(kernel, "height");
     baton->convKernelScale = attrAs<double>(kernel, "scale");
     baton->convKernelOffset = attrAs<double>(kernel, "offset");
 
-    size_t kernelSize = baton->convKernelWidth * baton->convKernelHeight;
-
+    size_t const kernelSize = static_cast<size_t>(baton->convKernelWidth * baton->convKernelHeight);
     baton->convKernel = std::unique_ptr<double[]>(new double[kernelSize]);
     Local<Array> kdata = Get(kernel, New("kernel").ToLocalChecked()).ToLocalChecked().As<Array>();
     for(unsigned int i = 0; i < kernelSize; i++) {