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examples of functional parameters
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‎image_processing/analyse_banana_data_set.ipynb‎

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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 10,
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"id": "coral-quantum",
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"metadata": {},
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"outputs": [],
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"source": [
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"data_folder = '../data/banana/'\n",
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"\n"
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"from skimage.filters import threshold_otsu, threshold_yen\n",
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"\n",
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"data_folder = '../data/banana/'"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 20,
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"id": "dutch-artwork",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"../data/banana/ [] ['banana0002.tif', 'banana0003.tif', 'banana0004.tif', 'banana0005.tif', 'banana0006.tif', 'banana0007.tif', 'banana0008.tif', 'banana0009.tif', 'banana0010.tif', 'banana0011.tif', 'banana0012.tif', 'banana0013.tif', 'banana0014.tif', 'banana0015.tif', 'banana0016.tif', 'banana0017.tif', 'banana0018.tif', 'banana0019.tif', 'banana0020.tif', 'banana0021.tif', 'banana0022.tif', 'banana0023.tif', 'banana0024.tif', 'banana0025.tif', 'banana0026.tif', 'image_source.txt']\n"
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]
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"data": {
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"text/plain": [
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"['banana0002.tif',\n",
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" 'banana0003.tif',\n",
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" 'banana0004.tif',\n",
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" 'banana0005.tif',\n",
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" 'banana0006.tif',\n",
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" 'banana0007.tif',\n",
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" 'banana0008.tif',\n",
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" 'banana0009.tif',\n",
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" 'banana0010.tif',\n",
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" 'banana0011.tif',\n",
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" 'banana0012.tif',\n",
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" 'banana0013.tif',\n",
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" 'banana0014.tif',\n",
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" 'banana0015.tif',\n",
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" 'banana0016.tif',\n",
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" 'banana0017.tif',\n",
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" 'banana0018.tif',\n",
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" 'banana0019.tif',\n",
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" 'banana0020.tif',\n",
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" 'banana0021.tif',\n",
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" 'banana0022.tif',\n",
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" 'banana0023.tif',\n",
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" 'banana0024.tif',\n",
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" 'banana0025.tif',\n",
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" 'banana0026.tif']"
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]
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},
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"execution_count": 20,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import os\n",
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"for root, dirs, files in os.walk(data_folder):\n",
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" print(root, dirs, files)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "still-taiwan",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"../data/banana/ [] banana0002.tif\n",
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"../data/banana/ [] banana0003.tif\n",
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"../data/banana/ [] banana0004.tif\n",
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"../data/banana/ [] banana0005.tif\n",
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"../data/banana/ [] banana0006.tif\n",
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"../data/banana/ [] banana0007.tif\n",
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"../data/banana/ [] banana0008.tif\n",
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"../data/banana/ [] banana0009.tif\n",
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"../data/banana/ [] banana0010.tif\n",
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"../data/banana/ [] banana0011.tif\n",
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"../data/banana/ [] banana0012.tif\n",
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"../data/banana/ [] banana0013.tif\n",
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"../data/banana/ [] banana0014.tif\n",
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"../data/banana/ [] banana0015.tif\n",
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"../data/banana/ [] banana0016.tif\n",
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"../data/banana/ [] banana0017.tif\n",
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"../data/banana/ [] banana0018.tif\n",
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"../data/banana/ [] banana0019.tif\n",
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"../data/banana/ [] banana0020.tif\n",
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"../data/banana/ [] banana0021.tif\n",
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"../data/banana/ [] banana0022.tif\n",
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"../data/banana/ [] banana0023.tif\n",
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"../data/banana/ [] banana0024.tif\n",
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"../data/banana/ [] banana0025.tif\n",
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"../data/banana/ [] banana0026.tif\n",
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"../data/banana/ [] image_source.txt\n"
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]
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}
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],
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"source": [
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"for root, dirs, files in os.walk(data_folder):\n",
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" for file in files:\n",
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" print(root, dirs, file)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "consecutive-landscape",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"../data/banana/ [] banana0002.tif\n",
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"../data/banana/ [] banana0003.tif\n",
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"../data/banana/ [] banana0004.tif\n",
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"../data/banana/ [] banana0005.tif\n",
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"../data/banana/ [] banana0006.tif\n",
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"../data/banana/ [] banana0007.tif\n",
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"../data/banana/ [] banana0008.tif\n",
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"../data/banana/ [] banana0009.tif\n",
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"../data/banana/ [] banana0010.tif\n",
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"../data/banana/ [] banana0011.tif\n",
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"../data/banana/ [] banana0012.tif\n",
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"../data/banana/ [] banana0013.tif\n",
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"../data/banana/ [] banana0014.tif\n",
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"../data/banana/ [] banana0015.tif\n",
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"../data/banana/ [] banana0016.tif\n",
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"../data/banana/ [] banana0017.tif\n",
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"../data/banana/ [] banana0018.tif\n",
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"../data/banana/ [] banana0019.tif\n",
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"../data/banana/ [] banana0020.tif\n",
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"../data/banana/ [] banana0021.tif\n",
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"../data/banana/ [] banana0022.tif\n",
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"../data/banana/ [] banana0023.tif\n",
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"../data/banana/ [] banana0024.tif\n",
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"../data/banana/ [] banana0025.tif\n",
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"../data/banana/ [] banana0026.tif\n"
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]
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}
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],
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"source": [
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"for root, dirs, files in os.walk(data_folder):\n",
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" for file in files:\n",
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" if file.endswith('tif'):\n",
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" print(root, dirs, file)"
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"\n",
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"# get a list of files in that folder\n",
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"file_list = os.listdir(data_folder)\n",
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"\n",
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"# filter the list so that only tif images remain\n",
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"image_file_list = [file for file in file_list if file.endswith(\".tif\")]\n",
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"image_file_list"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 12,
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"id": "metallic-punch",
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"metadata": {},
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"outputs": [
@@ -133,20 +76,23 @@
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"840"
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]
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},
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"execution_count": 15,
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"def process_image(filename):\n",
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"def process_image(filename, threshold_function):\n",
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" \"\"\"\n",
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" Process a given image file name \n",
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" \"\"\"\n",
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" \n",
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" # load data\n",
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" from skimage.io import imread\n",
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" image = imread(filename)\n",
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" \n",
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" # segment it\n",
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" from skimage.filters import threshold_otsu\n",
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" binary_image = image > threshold_otsu(image)\n",
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" binary_image = image > threshold_function(image)\n",
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" \n",
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" from skimage.measure import label\n",
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" labels = label(binary_image)\n",
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" import numpy as np\n",
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" return np.max(areas)\n",
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"\n",
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"process_image('../data/banana/banana0026.tif')"
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"process_image('../data/banana/banana0026.tif', threshold_otsu)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": 17,
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"id": "answering-dispute",
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"metadata": {},
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"outputs": [
@@ -177,61 +123,33 @@
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}
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],
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"source": [
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"slice_areas = []\n",
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"for root, dirs, files in os.walk(data_folder):\n",
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" for file in files:\n",
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" if file.endswith('tif'):\n",
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" slice_areas.append(process_image(root + file))\n",
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"slice_areas = [process_image(data_folder + file, threshold_otsu) for file in image_file_list]\n",
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"print(slice_areas)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "raised-polls",
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"execution_count": 19,
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"id": "alien-choir",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[1302, 3072, 5127, 6486, 7208, 7540, 7689, 7761, 7800, 7767, 7793, 7812, 7908, 8145, 8367, 8581, 8744, 8989, 9010, 8618, 7682, 6012, 3846, 1468, 840]\n"
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"[1833, 4199, 6074, 7312, 8012, 8379, 8473, 8461, 8382, 8307, 8257, 8300, 8442, 8681, 8967, 9247, 9592, 9880, 9976, 9757, 8886, 7468, 5478, 2203, 1255]\n"
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]
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}
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],
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"source": [
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"slice_areas = []\n",
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"for root, dirs, files in os.walk(data_folder):\n",
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" for file in files:\n",
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" if file.endswith('tif'):\n",
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" \n",
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" # load data\n",
209-
" from skimage.io import imread\n",
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" image = imread(root + file)\n",
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"\n",
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" # segment it\n",
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" from skimage.filters import threshold_otsu\n",
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" binary_image = image > threshold_otsu(image)\n",
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"\n",
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" from skimage.measure import label\n",
217-
" labels = label(binary_image)\n",
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"\n",
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" # measure radius\n",
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" from skimage.measure import regionprops\n",
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" statistics = regionprops(labels)\n",
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" areas = [s.area for s in statistics]\n",
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"\n",
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" # store result in array\n",
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" import numpy as np\n",
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" slice_areas.append(np.max(areas))\n",
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" \n",
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"print(slice_areas)\n"
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"slice_areas = [process_image(data_folder + file, threshold_yen) for file in image_file_list]\n",
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"print(slice_areas)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "alien-choir",
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"id": "1322c391",
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"metadata": {},
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"outputs": [],
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"source": []
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.8"
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"version": "3.9.4"
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}
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},
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"nbformat": 4,

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