docs: Update documentation

README.md

@@ -40,6 +40,7 @@ Try the [live demo](https://ryan-millard.github.io/Img2Num/)!
 - [C++](https://ryan-millard.github.io/Img2Num/info/docs/next/cpp/)
 - [C](https://ryan-millard.github.io/Img2Num/info/docs/next/c/)
 - [JavaScript](https://ryan-millard.github.io/Img2Num/info/docs/next/js/)
+- [Python](https://ryan-millard.github.io/Img2Num/info/docs/next/python/)
 - [Internal docs](https://ryan-millard.github.io/Img2Num/info/docs/next/internal/) (for contributors)
 
 ### Community

bindings/c/include/cimg2num.h

@@ -19,7 +19,6 @@ extern "C" {
 /// @brief Configuration options for image_to_svg.
 /// @ingroup CIMG2NUM_H
 typedef struct img2num_ImageToSvgConfig {
-
     /// Configuration settings for the bilateral filter in image_to_svg.
     struct BilateralFilterConfig {
         /// Standard deviation for spatial Gaussian (proximity weight).

bindings/c/src/cimg2num.cpp

@@ -8,33 +8,19 @@
 extern "C" {
 
 static img2num::ImageToSvgConfig to_cpp(const img2num_ImageToSvgConfig &c) {
-    return {
-        .bilateral_filter{
-            .sigma_spatial = c.bilateral_filter.sigma_spatial,
-            .sigma_range = c.bilateral_filter.sigma_range
-        },
-        .kmeans{
-            .k = c.kmeans.k,
-            .max_iter = c.kmeans.max_iter
-        },
-        .min_cluster_area = c.min_cluster_area,
-        .color_space = c.color_space
-    };
+    return {.bilateral_filter{.sigma_spatial = c.bilateral_filter.sigma_spatial,
+                              .sigma_range = c.bilateral_filter.sigma_range},
+            .kmeans{.k = c.kmeans.k, .max_iter = c.kmeans.max_iter},
+            .min_cluster_area = c.min_cluster_area,
+            .color_space = c.color_space};
 }
 
 static img2num_ImageToSvgConfig to_c(const img2num::ImageToSvgConfig &cpp) {
-    return {
-        .bilateral_filter{
-            .sigma_spatial = cpp.bilateral_filter.sigma_spatial,
-            .sigma_range = cpp.bilateral_filter.sigma_range
-        },
-        .kmeans{
-            .k = cpp.kmeans.k,
-            .max_iter = cpp.kmeans.max_iter
-        },
-        .min_cluster_area = cpp.min_cluster_area,
-        .color_space = cpp.color_space
-    };
+    return {.bilateral_filter{.sigma_spatial = cpp.bilateral_filter.sigma_spatial,
+                              .sigma_range = cpp.bilateral_filter.sigma_range},
+            .kmeans{.k = cpp.kmeans.k, .max_iter = cpp.kmeans.max_iter},
+            .min_cluster_area = cpp.min_cluster_area,
+            .color_space = cpp.color_space};
 }
 
 img2num_ImageToSvgConfig img2num_ImageToSvgConfig_default(void) {
@@ -101,16 +87,15 @@ char *img2num_image_to_svg(const uint8_t *data, const int width, const int heigh
 
     img2num::clear_last_error_and_catch(
         [&](const uint8_t *d, const int w, const int h) {
-            std::string svg{ img2num::image_to_svg(d, w, h, to_cpp(cfg)) };
+            std::string svg{img2num::image_to_svg(d, w, h, to_cpp(cfg))};
 
             result = static_cast<char *>(std::malloc(svg.size() + 1));
             if (!result) {
                 return;  // Allocation failed
             }
             std::memcpy(result, svg.c_str(), svg.size() + 1);
         },
-        data, width, height
-    );
+        data, width, height);
 
     return result;
 }

bindings/js/doxygen/home_page.dox

@@ -23,7 +23,7 @@
  * To build the JavaScript/WASM bindings, follow these steps:
  *
  * \code{.sh}
- * emcmake cmake -B build-wasm
+ * emcmake cmake -DCMAKE_BUILD_TYPE=Release -B build-wasm
  * cmake --build build-wasm
  * \endcode
  *

bindings/py/Doxyfile.internal

@@ -0,0 +1,14 @@
+@INCLUDE = ../../doxygen/Doxyfile.base
+
+PROJECT_NAME     = "Img2Num Python Bindings (Internal Developer Docs)"
+
+PROJECT_NUMBER   = dev
+
+INPUT            = src ../../doxygen/*.dox doxygen/home_page.dox
+OUTPUT_DIRECTORY = ../../docs/static/docs/internal/bindings/py/api
+
+RECURSIVE        = YES
+
+EXTRACT_PRIVATE  = YES
+EXTRACT_STATIC   = YES
+INTERNAL_DOCS    = YES

bindings/py/doxygen/home_page.dox

@@ -0,0 +1,95 @@
+/*! \mainpage Img2Num Python Bindings
+ *
+ * \section intro_sec Introduction
+ *
+ * The **Img2Num Python Bindings** provide a Python interface to the core Img2Num
+ * image processing library via pybind11. These bindings wrap the underlying C++
+ * functionality, exposing image processing operations such as filtering, clustering,
+ * thresholding, and SVG conversion to Python code.
+ *
+ * All functions operate on `numpy.ndarray` buffers and return new image data, making
+ * them easy to integrate into Python-based image processing pipelines.
+ *
+ * \section features_sec Key Features
+ *
+ * The Python bindings expose the following core capabilities:
+ * - **FFT-based Gaussian blur** — Fast frequency-domain blurring
+ * - **Image inversion** — Invert pixel values
+ * - **Thresholding** — Standard and black-thresholding operations
+ * - **K-means clustering** — Pixel clustering for color quantization
+ * - **Bilateral filtering** — Edge-preserving smoothing
+ * - **Label-to-SVG conversion** — Convert labeled images to SVG strings
+ * - **Image-to-SVG conversion** — Full image vectorization with configurable parameters
+ * - **ImageToSvgConfig** — Python-accessible configuration for SVG generation
+ *
+ * \section building_sec Building the Python Bindings
+ *
+ * The Python bindings are built using CMake from the project root:
+ *
+ * \code{.sh}
+ * cmake -B build .
+ * cmake --build build
+ * \endcode
+ *
+ * \section install_sec Installation
+ *
+ * Install the bindings to your system:
+ *
+ * \code{.sh}
+ * cmake --install build
+ * \endcode
+ *
+ * The compiled `_img2num` module will be available for import in Python:
+ *
+ * \code{.py}
+ * import _img2num
+ * \endcode
+ *
+ * \section usage_sec Usage Example
+ *
+ * \code{.py}
+ * import numpy as np
+ * import _img2num
+ *
+ * # Load image as uint8 numpy array
+ * image = np.array([...], dtype=np.uint8).reshape((height, width, 3))
+ *
+ * # Apply Gaussian blur
+ * blurred = _img2num.gaussian_blur_fft(image, width, height, sigma=2.0)
+ *
+ * # Invert colors
+ * inverted = _img2num.invert_image(image, width, height)
+ *
+ * # Threshold
+ * thresholded = _img2num.threshold_image(image, width, height, num_thresholds=4)
+ *
+ * # K-means clustering
+ * clustered_data, labels = _img2num.kmeans(image, width, height, k=8, max_iter=50)
+ *
+ * # Bilateral filtering
+ * filtered = _img2num.bilateral_filter(image, width, height, sigma_spatial=3.0, sigma_range=50.0)
+ *
+ * # SVG conversion
+ * config = _img2num.ImageToSvgConfig()
+ * svg_str = _img2num.image_to_svg(image, width, height, config)
+ * \endcode
+ *
+ * \section api_sec API Reference
+ *
+ * Browse the detailed function and class documentation:
+ * - \ref img2num_functions "Core Image Processing Functions"
+ * - \ref img2num_classes "Configuration Classes"
+ */
+
+/** \defgroup img2num_functions Image Processing Functions
+ *  @ingroup mainpage
+ *  @brief Image processing functions exposed via Python bindings.
+ *  @{
+ */
+
+/** \defgroup img2num_classes Configuration Classes
+ *  @ingroup mainpage
+ *  @brief Configuration classes for image processing and SVG generation.
+ *  @{
+ */
+