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add rich text to image demo (#73)
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‎notebooks/image_CUDA_demo/threshold_test.ipynb

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{
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"cells": [
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"cell_type": "markdown",
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"id": "45fd5ee6-9514-4fc2-8561-ec3aaec330a0",
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"metadata": {},
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"source": [
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"## Parallel Image thresholding using CUDA C++ and Python PIL"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4947f8aa-ba7b-4755-9373-5bc23cc013fd",
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"metadata": {},
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"source": [
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"### We aim to threshold this image of CERN, to enhance focus on the Alps and white text"
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]
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},
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"cell_type": "markdown",
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"id": "f1ac7a20-ddc1-408f-a42b-599f724c295b",
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"metadata": {},
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"source": [
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"<img src=\"img_in.jpg\" align=left width=\"400\">"
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},
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"#include <iostream>\n",
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"#include <cmath>\n",
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"#include <cuda_runtime.h>\n",
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"#include<vector>\n"
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"#include<vector>"
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]
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"id": "482eb964-0d48-422d-8f67-fcd9fb785f89",
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"metadata": {},
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"source": [
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"### We define a CUDA kernel that brightens or underexposes pixels based on a threshold value:"
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"source": [
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"!pip install matplotlib"
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"id": "6d6a53e4-c2a1-49ad-9f76-90a86bf022b8",
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"metadata": {},
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"source": [
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"### Read the image in Python using PIL and convert to grayscale"
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"}"
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"id": "6eb60938-dbd8-49f4-8e3b-23a975f36143",
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"metadata": {},
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"source": [
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"### Converting the python image into a std::vector using Cppyy:"
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},
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"img_vector = cppyy.gbl.std.vector['float'](img_list)"
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"id": "cd6d8d32-6175-4af3-a0eb-7d563e142f1e",
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"metadata": {},
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"source": [
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"### C++ function that recives the std::vector and passes it to the CUDA function host input:"
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"### C++ function to return the host output to the Python side:"
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"id": "fa4fb49f-ea0f-40c0-bf4d-92ad469e0426",
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"source": [
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"### Allocating CUDA memory and calling the kernel"
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"source": [
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"### Access the CUDA filter result on the Python side:"
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