{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Convolution\n", "There are multiple ways for convolving images using pyclesperanto - intentionally. We will compare their performance to each other and also to an implementation in scikit-image.\n", "\n", "See also: https://en.wikipedia.org/wiki/Convolution\n", "\n", "Let's start by initializing the GPU" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pyclesperanto_prototype as cle\n", "from skimage import filters\n", "from skimage.morphology import ball\n", "import time\n", "\n", "# to measure kernel execution duration properly, we need to set this flag. It will slow down exection of workflows a bit though\n", "cle.set_wait_for_kernel_finish(True)\n", "\n", "# selet a GPU with the following in the name. This will fallback to any other GPU if none with this name is found\n", "cle.select_device('RTX')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Convolution kernel\n", "To visualize the weights used by the convolution to multiply pixels with surrounding pixel values, we create an image with a single pixel set to 1 (all others are 0) and convolve it. The resulting `kernel` image is also called the `structuring element`." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def create_kernel(radius = 10):\n", "\n", " diameter = radius * 2 + 1\n", " spot = cle.create([diameter, diameter])\n", " cle.set(spot, 0)\n", " cle.draw_box(spot, radius, radius, 0, 0, 0, 0)\n", "\n", " kernel = cle.create([diameter, diameter])\n", " cle.mean_sphere(spot, kernel, radius, radius)\n", "\n", " return kernel\n", "\n", "kernel = create_kernel(10)\n", "cle.imshow(kernel)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now generate an image with random pixel values to convolve it" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "\n", "test_image = cle.push(np.random.random([1000, 1000]))\n", "\n", "cle.imshow(test_image) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Quick benchmarking different convolution strategies\n", "We start by convolving the image with the kernel created above" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Convolve custom duration: 0.006981611251831055\n", "Convolve custom duration: 0.0029916763305664062\n", "Convolve custom duration: 0.002989530563354492\n", "Convolve custom duration: 0.0029921531677246094\n", "Convolve custom duration: 0.0029909610748291016\n", "Convolve custom duration: 0.002992868423461914\n", "Convolve custom duration: 0.002992391586303711\n", "Convolve custom duration: 0.0029921531677246094\n", "Convolve custom duration: 0.0029916763305664062\n", "Convolve custom duration: 0.002990245819091797\n" ] } ], "source": [ "kernel = create_kernel(10)\n", "\n", "import time\n", "result_image = None\n", "\n", "for i in range(0, 10):\n", " start_time = time.time()\n", " result_image = cle.convolve(test_image, kernel, result_image)\n", " print(\"Convolve custom duration: \" + str(time.time() - start_time))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Another strategy is calling the mean_sphere function. This means, we don't us a kernel image internally." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Convolve sphere duration: 0.004986763000488281\n", "Convolve sphere duration: 0.004985332489013672\n", "Convolve sphere duration: 0.003988981246948242\n", "Convolve sphere duration: 0.003986835479736328\n", "Convolve sphere duration: 0.003989696502685547\n", "Convolve sphere duration: 0.0049839019775390625\n", "Convolve sphere duration: 0.004991292953491211\n", "Convolve sphere duration: 0.003987550735473633\n", "Convolve sphere duration: 0.003986835479736328\n", "Convolve sphere duration: 0.004986286163330078\n" ] } ], "source": [ "result_image = None\n", "\n", "for i in range(0, 10):\n", " start_time = time.time()\n", " result_image = cle.mean_sphere(test_image, result_image, 10, 10)\n", " print(\"Convolve sphere duration: \" + str(time.time() - start_time))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A faster version uses mean_box. Note: The structuring element is a rectangle, and not a sphere anymore. This operation is typically faster because this is a separable implementation." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Convolve box duration: 0.00698089599609375\n", "Convolve box duration: 0.002989530563354492\n", "Convolve box duration: 0.002991914749145508\n", "Convolve box duration: 0.0029959678649902344\n", "Convolve box duration: 0.00299072265625\n", "Convolve box duration: 0.0029947757720947266\n", "Convolve box duration: 0.002986907958984375\n", "Convolve box duration: 0.002996683120727539\n", "Convolve box duration: 0.0029904842376708984\n", "Convolve box duration: 0.002994060516357422\n" ] } ], "source": [ "result_image = None\n", "\n", "for i in range(0, 10):\n", " start_time = time.time()\n", " result_image = cle.mean_box(test_image, result_image, 10, 10)\n", " print(\"Convolve box duration: \" + str(time.time() - start_time))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Convolution in 3D" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[[0. , 0. , 0. , 0. , 0. ],\n", " [0. , 0. , 0. , 0. , 0. ],\n", " [0. , 0. , 0.03030303, 0. , 0. ],\n", " [0. , 0. , 0. , 0. , 0. ],\n", " [0. , 0. , 0. , 0. , 0. ]],\n", "\n", " [[0. , 0. , 0. , 0. , 0. ],\n", " [0. , 0.03030303, 0.03030303, 0.03030303, 0. ],\n", " [0. , 0.03030303, 0.03030303, 0.03030303, 0. ],\n", " [0. , 0.03030303, 0.03030303, 0.03030303, 0. ],\n", " [0. , 0. , 0. , 0. , 0. ]],\n", "\n", " [[0. , 0. , 0.03030303, 0. , 0. ],\n", " [0. , 0.03030303, 0.03030303, 0.03030303, 0. ],\n", " [0.03030303, 0.03030303, 0.03030303, 0.03030303, 0.03030303],\n", " [0. , 0.03030303, 0.03030303, 0.03030303, 0. ],\n", " [0. , 0. , 0.03030303, 0. , 0. ]],\n", "\n", " [[0. , 0. , 0. , 0. , 0. ],\n", " [0. , 0.03030303, 0.03030303, 0.03030303, 0. ],\n", " [0. , 0.03030303, 0.03030303, 0.03030303, 0. ],\n", " [0. , 0.03030303, 0.03030303, 0.03030303, 0. ],\n", " [0. , 0. , 0. , 0. , 0. ]],\n", "\n", " [[0. , 0. , 0. , 0. , 0. ],\n", " [0. , 0. , 0. , 0. , 0. ],\n", " [0. , 0. , 0.03030303, 0. , 0. ],\n", " [0. , 0. , 0. , 0. , 0. ],\n", " [0. , 0. , 0. , 0. , 0. ]]],\n", " dtype=float32)" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "def create_kernel_3d(radius = 10):\n", "\n", " diameter = radius * 2 + 1\n", " spot = cle.create([diameter, diameter, diameter])\n", " cle.set(spot, 0)\n", " cle.draw_box(spot, radius, radius, radius, 0, 0, 0)\n", "\n", " kernel = cle.create([diameter, diameter, diameter])\n", " cle.mean_sphere(spot, kernel, radius, radius, radius)\n", "\n", " return kernel\n", "\n", "kernel = create_kernel_3d(2)\n", "kernel" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Quick benchmarking different convolution strategies in 3D\n", "We start by convolving the image with the kernel created above" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "\n", "test_image = cle.push_zyx(np.random.random([100, 100, 100]))\n", " " ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Convolve custom duration: 0.06682157516479492\n", "Convolve custom duration: 0.06083536148071289\n", "Convolve custom duration: 0.05086231231689453\n", "Convolve custom duration: 0.051862478256225586\n", "Convolve custom duration: 0.05185818672180176\n", "Convolve custom duration: 0.05285978317260742\n", "Convolve custom duration: 0.05185890197753906\n", "Convolve custom duration: 0.0528559684753418\n", "Convolve custom duration: 0.05286002159118652\n", "Convolve custom duration: 0.052855491638183594\n" ] } ], "source": [ "kernel = create_kernel_3d(10)\n", "\n", "import time\n", "result_image = None\n", "\n", "for i in range(0, 10):\n", " start_time = time.time()\n", " result_image = cle.convolve(test_image, kernel, result_image)\n", " print(\"Convolve custom duration: \" + str(time.time() - start_time))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Another strategy is calling the mean_sphere function. This means, we don't us a kernel image internally." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Convolve sphere duration: 0.04741215705871582\n", "Convolve sphere duration: 0.04587531089782715\n", "Convolve sphere duration: 0.04587697982788086\n", "Convolve sphere duration: 0.04587745666503906\n", "Convolve sphere duration: 0.045874834060668945\n", "Convolve sphere duration: 0.04687929153442383\n", "Convolve sphere duration: 0.04581880569458008\n", "Convolve sphere duration: 0.044886112213134766\n", "Convolve sphere duration: 0.045905351638793945\n", "Convolve sphere duration: 0.04549527168273926\n" ] } ], "source": [ "result_image = None\n", "\n", "for i in range(0, 10):\n", " start_time = time.time()\n", " result_image = cle.mean_sphere(test_image, result_image, 10, 10, 10)\n", " print(\"Convolve sphere duration: \" + str(time.time() - start_time))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A faster version uses mean_box. Note: The structuring element is a rectangle, and not a sphere anymore. This operation is typically faster because this is a separable implementation." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Convolve box duration: 0.02706146240234375\n", "Convolve box duration: 0.0038940906524658203\n", "Convolve box duration: 0.0034389495849609375\n", "Convolve box duration: 0.003582000732421875\n", "Convolve box duration: 0.003453969955444336\n", "Convolve box duration: 0.0039038658142089844\n", "Convolve box duration: 0.0032875537872314453\n", "Convolve box duration: 0.003624439239501953\n", "Convolve box duration: 0.003353118896484375\n", "Convolve box duration: 0.0037848949432373047\n" ] } ], "source": [ "result_image = None\n", "\n", "for i in range(0, 10):\n", " start_time = time.time()\n", " result_image = cle.mean_box(test_image, result_image, 10, 10, 10)\n", " print(\"Convolve box duration: \" + str(time.time() - start_time))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Mean filter in scikit-image" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "c:\\users\\rober\\miniconda3\\lib\\site-packages\\skimage\\filters\\rank\\generic.py:278: UserWarning: Possible precision loss converting image of type float32 to uint8 as required by rank filters. Convert manually using skimage.util.img_as_ubyte to silence this warning.\n", " image, selem, out, mask, n_bins = _handle_input_3D(image, selem, out, mask,\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "skimage rank.mean duration: 34.42355275154114\n", "skimage rank.mean duration: 33.18763279914856\n", "skimage rank.mean duration: 32.87314820289612\n", "skimage rank.mean duration: 33.66009593009949\n", "skimage rank.mean duration: 37.38083744049072\n", "skimage rank.mean duration: 35.021158933639526\n", "skimage rank.mean duration: 34.05577373504639\n", "skimage rank.mean duration: 35.13659048080444\n", "skimage rank.mean duration: 34.86917328834534\n", "skimage rank.mean duration: 35.529059410095215\n" ] } ], "source": [ "# mean filter with scikit-image\n", "result_image = None\n", "structuring_element = ball(10)\n", "\n", "for i in range(0, 10):\n", " start_time = time.time()\n", " result_image = filters.rank.mean(test_image, selem=structuring_element, out=result_image)\n", " print(\"skimage rank.mean duration: \" + str(time.time() - start_time))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.3" } }, "nbformat": 4, "nbformat_minor": 4 }