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@pontikos
pontikos committed May 8, 2020
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{
"nbformat": 4,
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"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
},
"colab": {
"name": "create_filters.ipynb",
"provenance": [],
"include_colab_link": true
}
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"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/pontikos/retinal_imaging/blob/master/create_filters.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"id": "f3gYl7iDPU4i",
"colab_type": "code",
"colab": {}
},
"source": [
"import cv2\n",
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import pickle"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "GZKHkzwfPU4n",
"colab_type": "code",
"colab": {}
},
"source": [
"imgpath = './combine/female_correct.png'"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "0fxbRxw9PU4q",
"colab_type": "code",
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},
"source": [
"scale = (450,450)\n",
"cropcenter = (scale[0]/2, scale[1]/2)\n",
"bopcenter = cropcenter\n",
"clicking = False\n",
"zoomed = False\n",
"library = []"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "2PGZHfvlPU4t",
"colab_type": "code",
"colab": {}
},
"source": [
"def click_and_zoom(event, x, y, flags, param):\n",
" global cropcenter, clicking, zoomed\n",
" \n",
" if event == cv2.EVENT_LBUTTONDOWN:\n",
" if not zoomed:\n",
" cropcenter = (x,y)\n",
" clicking = True\n",
"\n",
" \n",
" elif event == cv2.EVENT_LBUTTONUP:\n",
" clicking = False"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "0BXQVXEWPU4w",
"colab_type": "code",
"colab": {}
},
"source": [
"img = cv2.imread(imgpath,1)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "zqyAtiSdPU4z",
"colab_type": "code",
"colab": {}
},
"source": [
"cv2.namedWindow('Microaneurysm_Labelling')\n",
"cv2.setMouseCallback('Microaneurysm_Labelling', click_and_zoom)\n",
"\n",
"height, width, channels = img.shape\n",
"missalignment = width-height\n",
"offset = int(missalignment/2)\n",
"\n",
"radiusXFilter = 5\n",
"radiusYFilter = 5\n",
"\n",
"radiusXCrop = 20\n",
"radiusYCrop = 20\n",
"\n",
"radiusXZoom = ((radiusXFilter/radiusXCrop) * scale[0]) /2\n",
"radiusYZoom = ((radiusYFilter/radiusYCrop) * scale[0]) /2\n",
"\n",
"if(missalignment < 0):\n",
" print(\"ERROR: negative missalignment\")\n",
"if(missalignment % 2 == 1):\n",
" print(\"ERROR: Uneven missalignment\")\n",
" \n",
"\n",
"\n",
"img = img[0:height, offset:(width-offset)]\n",
"img = cv2.resize(img, scale)\n",
"bimg = img.copy()\n",
"zimg = img.copy()\n",
"\n",
"while True:\n",
" \n",
" if not zoomed:\n",
" img = bimg.copy()\n",
" else:\n",
" img = zimg.copy()\n",
" \n",
" centerX,centerY = cropcenter\n",
" \n",
" #TODO: Check Borders\n",
" \n",
" if not zoomed:\n",
" minXFilter,maxXFilter = int(centerX-radiusXFilter), int(centerX+radiusXFilter)\n",
" minYFilter,maxYFilter = int(centerY-radiusYFilter), int(centerY+radiusYFilter)\n",
" else:\n",
" minXFilter,maxXFilter = int(centerX-radiusXZoom), int(centerX+radiusXZoom)\n",
" minYFilter,maxYFilter = int(centerY-radiusYZoom), int(centerY+radiusYZoom)\n",
" \n",
" \n",
" \n",
" imgRec = cv2.rectangle(img, (minXFilter,minYFilter), (maxXFilter,maxYFilter), (0,255,0), 2)\n",
" \n",
" cv2.imshow('Microaneurysm_Labelling', imgRec)\n",
" \n",
" key = cv2.waitKeyEx(1) #& 0xFF\n",
" \n",
" #TODO: Zoom functionality\n",
" \n",
" if key == ord('i'):\n",
" print('i')\n",
" zoomed = True\n",
"\n",
" #TODO: Check Borders\n",
" minXCrop, maxXCrop = centerX - radiusXCrop, centerX + radiusXCrop\n",
" minYCrop, maxYCrop = centerY - radiusYCrop, centerY + radiusYCrop\n",
" img = bimg.copy()\n",
" img = img[minYCrop:maxYCrop, minXCrop:maxXCrop]\n",
" img = cv2.resize(img, scale)\n",
" \n",
" zimg = img.copy()\n",
" \n",
" bopcenter = cropcenter\n",
" cropcenter = (scale[0]/2, scale[1]/2)\n",
" \n",
" \n",
" if key == ord('o'):\n",
" print('o')\n",
" zoomed = False\n",
" \n",
" img = bimg.copy()\n",
" cropcenter = bopcenter\n",
" \n",
" if key == ord('r'):\n",
" print('r')\n",
" minXFilter,maxXFilter = int(centerX-radiusXFilter), int(centerX+radiusXFilter)\n",
" minYFilter,maxYFilter = int(centerY-radiusYFilter), int(centerY+radiusYFilter)\n",
" \n",
" reference = bimg[minYFilter:maxYFilter, minXFilter:maxXFilter]\n",
" \n",
" library.append(reference)\n",
" \n",
" if key == 2424832: #Left on Windows\n",
" print('Left')\n",
" cropcenter = cropcenter[0]-1, cropcenter[1]\n",
" \n",
" if key == 2555904: #Right on Windows\n",
" print('Right')\n",
" cropcenter = cropcenter[0]+1, cropcenter[1]\n",
" \n",
" if key == 2490368: #Up on Windows\n",
" print('Up')\n",
" cropcenter = cropcenter[0], cropcenter[1]-1\n",
" \n",
" if key == 2621440: #Down on Windows\n",
" print('Down')\n",
" cropcenter = cropcenter[0], cropcenter[1]+1\n",
" \n",
" if key == 27: #Esc\n",
" break\n",
" \n",
" #Use this code to check for correct keycodes on your system \n",
" #if(key == -1):\n",
" # continue\n",
" #else:\n",
" # print(key)\n",
" \n",
"with open('referenceLib.pkl', 'wb') as f:\n",
" pickle.dump(library, f)\n",
" \n",
"cv2.destroyAllWindows()"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "tJTY_VVOPU44",
"colab_type": "code",
"colab": {}
},
"source": [
""
],
"execution_count": 0,
"outputs": []
}
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}

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