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add rich text to image demo (#73)
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@aaronj0
aaronj0 authored Oct 9, 2023
1 parent 6219f7f commit aeb22a7
Showing 1 changed file with 159 additions and 51 deletions.
210 changes: 159 additions & 51 deletions notebooks/image_CUDA_demo/threshold_test.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "45fd5ee6-9514-4fc2-8561-ec3aaec330a0",
"metadata": {},
"source": [
"## Parallel Image thresholding using CUDA C++ and Python PIL"
]
},
{
"cell_type": "markdown",
"id": "4947f8aa-ba7b-4755-9373-5bc23cc013fd",
"metadata": {},
"source": [
"### We aim to threshold this image of CERN, to enhance focus on the Alps and white text"
]
},
{
"cell_type": "markdown",
"id": "f1ac7a20-ddc1-408f-a42b-599f724c295b",
"metadata": {},
"source": [
"<img src=\"img_in.jpg\" align=left width=\"400\">"
]
},
{
"cell_type": "code",
"execution_count": 1,
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"#include <iostream>\n",
"#include <cmath>\n",
"#include <cuda_runtime.h>\n",
"#include<vector>\n"
"#include<vector>"
]
},
{
"cell_type": "markdown",
"id": "482eb964-0d48-422d-8f67-fcd9fb785f89",
"metadata": {},
"source": [
"### We define a CUDA kernel that brightens or underexposes pixels based on a threshold value:"
]
},
{
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"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: Pillow in /opt/conda/envs/.venv/lib/python3.10/site-packages (10.0.1)\n"
"Collecting Pillow\n",
" Obtaining dependency information for Pillow from https://files.pythonhosted.org/packages/7a/07/e896b096a77375e78e02ce222ae4fd6014928cd76c691d312060a1645dfa/Pillow-10.0.1-cp310-cp310-manylinux_2_28_x86_64.whl.metadata\n",
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"Installing collected packages: Pillow\n",
"Successfully installed Pillow-10.0.1\n"
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"Installing collected packages: numpy\n",
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"name": "stdout",
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"Requirement already satisfied: matplotlib in /opt/conda/envs/.venv/lib/python3.10/site-packages (3.8.0)\n",
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" Obtaining dependency information for matplotlib from https://files.pythonhosted.org/packages/b5/24/aaccf324ce862bb82277e8814d2aebbb2a2c160d04e95aa2b8c9dc3137a9/matplotlib-3.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata\n",
" Downloading matplotlib-3.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (5.8 kB)\n",
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" Obtaining dependency information for contourpy>=1.0.1 from https://files.pythonhosted.org/packages/f1/6b/e4b0f8708f22dd7c321f87eadbb98708975e115ac6582eb46d1f32197ce6/contourpy-1.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata\n",
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" Obtaining dependency information for cycler>=0.10 from https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl.metadata\n",
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" Obtaining dependency information for fonttools>=4.22.0 from https://files.pythonhosted.org/packages/ac/ed/9a33eca5e2cc35dc1fea0a968509c653db9a99a5979656ae57c6c019d66b/fonttools-4.43.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata\n",
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"Installing collected packages: pyparsing, kiwisolver, fonttools, cycler, contourpy, matplotlib\n",
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]
}
],
"source": [
"!pip install matplotlib"
]
},
{
"cell_type": "markdown",
"id": "6d6a53e4-c2a1-49ad-9f76-90a86bf022b8",
"metadata": {},
"source": [
"### Read the image in Python using PIL and convert to grayscale"
]
},
{
"cell_type": "code",
"execution_count": 8,
Expand All @@ -143,32 +222,6 @@
{
"cell_type": "code",
"execution_count": 9,
"id": "6a1cd914-db44-4e34-a9fb-5d2100b298b8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[126 126 125 ... 84 84 84]\n",
" [126 126 125 ... 84 84 84]\n",
" [127 126 126 ... 84 84 84]\n",
" ...\n",
" [ 58 55 63 ... 19 15 8]\n",
" [ 57 56 53 ... 23 17 16]\n",
" [ 55 50 58 ... 5 16 16]]\n"
]
}
],
"source": [
"%%python\n",
"\n",
"print(image_array)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "7545b5c9-c901-4599-abde-3ae5ac17e160",
"metadata": {},
"outputs": [],
Expand All @@ -186,9 +239,17 @@
"}"
]
},
{
"cell_type": "markdown",
"id": "6eb60938-dbd8-49f4-8e3b-23a975f36143",
"metadata": {},
"source": [
"### Converting the python image into a std::vector using Cppyy:"
]
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 10,
"id": "a3c74a47-399e-4454-89f6-f4e8b0376a68",
"metadata": {},
"outputs": [],
Expand All @@ -201,9 +262,17 @@
"img_vector = cppyy.gbl.std.vector['float'](img_list)"
]
},
{
"cell_type": "markdown",
"id": "cd6d8d32-6175-4af3-a0eb-7d563e142f1e",
"metadata": {},
"source": [
"### C++ function that recives the std::vector and passes it to the CUDA function host input:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 11,
"id": "ab6c16bd-c44a-4e4e-985a-12c5ca3256a8",
"metadata": {},
"outputs": [],
Expand All @@ -222,9 +291,17 @@
"}\n"
]
},
{
"cell_type": "markdown",
"id": "75a21ae2-cffa-4f34-9404-c59577d9b67f",
"metadata": {},
"source": [
"### C++ function to return the host output to the Python side:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 12,
"id": "a168bbab-fc67-41f5-85c1-f9980d75a00b",
"metadata": {},
"outputs": [],
Expand All @@ -240,7 +317,7 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": 13,
"id": "2eec8b62-5500-45e4-9c02-9bc587288206",
"metadata": {},
"outputs": [],
Expand All @@ -252,7 +329,7 @@
},
{
"cell_type": "code",
"execution_count": 15,
"execution_count": 14,
"id": "fd1bef06-d14e-4c82-8fa5-da14df696fe5",
"metadata": {},
"outputs": [
Expand All @@ -268,9 +345,17 @@
"displayImgArray(h_input);"
]
},
{
"cell_type": "markdown",
"id": "fa4fb49f-ea0f-40c0-bf4d-92ad469e0426",
"metadata": {},
"source": [
"### Allocating CUDA memory and calling the kernel"
]
},
{
"cell_type": "code",
"execution_count": 16,
"execution_count": 15,
"id": "ea90464f-ed8f-44f1-9336-99aa3dc85149",
"metadata": {},
"outputs": [],
Expand All @@ -294,9 +379,17 @@
"cudaFree(d_output)"
]
},
{
"cell_type": "markdown",
"id": "1edf472e-fe51-4fd1-a0e5-e30a2d092739",
"metadata": {},
"source": [
"### Verifying host output"
]
},
{
"cell_type": "code",
"execution_count": 17,
"execution_count": 16,
"id": "7bf09ac1-ac6b-45e9-93c2-d4ae50897c2d",
"metadata": {},
"outputs": [
Expand All @@ -314,17 +407,25 @@
},
{
"cell_type": "code",
"execution_count": 18,
"execution_count": 17,
"id": "3a97a53f-c2b7-4e24-a299-a6c0ec81b16e",
"metadata": {},
"outputs": [],
"source": [
"std::vector<float> blurredRes = getOutput();"
]
},
{
"cell_type": "markdown",
"id": "e22c59e0-019f-479f-8fa0-63e00b680702",
"metadata": {},
"source": [
"### Access the CUDA filter result on the Python side:"
]
},
{
"cell_type": "code",
"execution_count": 19,
"execution_count": 18,
"id": "2586f437-295d-4b33-b18e-6f28628a7f81",
"metadata": {},
"outputs": [],
Expand All @@ -337,7 +438,7 @@
},
{
"cell_type": "code",
"execution_count": 20,
"execution_count": 19,
"id": "a8104074-7398-4653-a81a-827dd81a16b3",
"metadata": {},
"outputs": [],
Expand All @@ -352,16 +453,23 @@
"id": "d0d2e15b-5a5f-4ed8-8f17-3fd1f3fc4daf",
"metadata": {},
"source": [
"<img src=\"img_out.jpg\" align=right width=\"400\">\n",
"<img src=\"img_in.jpg\" align=left width=\"400\">"
"<img src=\"img_out.jpg\" align=left width=\"400\">\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0969406d-0bab-4022-bbeb-0e2581035ef4",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "CUDA (C++17)",
"display_name": "CppInterOp (C++17)",
"language": "CUDA",
"name": "cuda-xcpp17"
"name": "cppinterop-xcpp17"
},
"language_info": {
"codemirror_mode": "text/x-c++src",
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