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romeokienzlerromeokienzler
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Merge pull request claimed-framework#268 from creatermaker/main
This is the improved version of image-tiling.
2 parents 8a05abd + 3a1008f commit 2dcb166

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‎component-library/input/image-tiling.cwl‎

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cwlVersion: v1.2
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class: CommandLineTool
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baseCommand: "claimed"
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inputs:
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component:
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type: string
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default: docker.io/mdorzweiler/claimed-image-tiling:0.1
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inputBinding:
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position: 1
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prefix: --component
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log_level:
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type: string
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default: "INFO"
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inputBinding:
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position: 2
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prefix: --log_level
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directory_path:
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type: string
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default: None
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inputBinding:
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position: 3
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prefix: --directory_path
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destination:
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type: string
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default: None
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inputBinding:
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position: 4
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prefix: --destination
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tile_size_x:
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type: string
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default: None
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inputBinding:
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position: 5
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prefix: --tile_size_x
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tile_size_y:
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type: string
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default: None
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inputBinding:
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position: 6
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prefix: --tile_size_y
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stride_x:
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type: string
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default: None
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inputBinding:
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position: 7
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prefix: --stride_x
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stride_y:
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type: string
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default: None
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inputBinding:
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position: 8
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prefix: --stride_y
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outputs: []

‎component-library/input/image-tiling.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "2e8a0fac-adbd-4428-90ea-869aee2b95bf",
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"metadata": {},
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"source": [
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"## Xview Dataset clipping\n",
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"This is a component designed to clip the dataset provided by xview. "
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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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"id": "c0421aaf-4da4-4a66-b626-e8962315afe8",
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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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"Requirement already satisfied: Pillow in /Users/maxdorzweiler/anaconda3/lib/python3.11/site-packages (9.4.0)\n"
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]
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}
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],
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"source": [
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"!pip install Pillow"
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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": 2,
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"id": "0b7ad533-dabc-488e-bf65-59a54a85f3f9",
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"import os\n",
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"from PIL import Image\n"
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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": 4,
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"id": "c8df047b-6167-43f1-9a31-d836580180ac",
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"#directory_path is the path to the folder with the unzipped .tif images from xview dataset \n",
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"directory_path = os.environ.get(\"directory_path\")\n",
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"\n",
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"#destination is the path to the folder which saves all the extracted tiles. \n",
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"destination = os.environ.get(\"destination\")\n",
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"\n",
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"#Each image is cropped using a rectangular window with edge_length tile_size_x and tile_size_y which has to be given in number of pixels \n",
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"tile_size_x = os.environ.get(\"tile_size_x\")\n",
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"tile_size_y = os.environ.get(\"tile_size_y\")\n",
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"\n",
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"#stride_x is the length in pixels the sliding window is moved to the right after each step\n",
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"#stride_y is the length in pixels the sliding window is moved down after completing a row\n",
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"#For tumbling window stride_x must equal tile_size_x and stride_y must equal tile_size_y\n",
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"stride_x = os.environ.get(\"stride_x\")\n",
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"stride_y = os.environ.get(\"stride_y\")\n"
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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": "8ed74228-937d-4d5d-b6d9-97026af3eb50",
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"def clear_directory(directory):\n",
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" for item in os.listdir(directory):\n",
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" item_path = os.path.join(directory, item)\n",
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" # Check if the item is a file\n",
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" if os.path.isfile(item_path):\n",
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" # If it's a file, remove it\n",
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" os.remove(item_path)\n",
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" # If it's a directory, recursively clear it\n",
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" elif os.path.isdir(item_path):\n",
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" clear_directory(item_path)\n",
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" os.rmdir(item_path)\n",
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" "
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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": 9,
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"id": "d6e89f94-490a-4c1a-80cd-f2ab30adb374",
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"def sliding_window(directory_path, destination, tile_size_x, tile_size_y, stride_x, stride_y):\n",
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" \n",
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" if os.path.isdir(destination):\n",
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" clear_directory(destination)\n",
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" else: \n",
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" os.makedirs(destination)\n",
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" \n",
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" \n",
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" for item in os.listdir(directory_path):\n",
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" if item == \".DS_Store\":\n",
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" continue\n",
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" item_path = os.path.join(directory_path, item)\n",
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" clipped_item = os.path.join(destination, item)\n",
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" os.makedirs(clipped_item)\n",
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" \n",
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" image = Image.open(item_path)\n",
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" width, height = image.size\n",
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" \n",
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" x_range = [0]\n",
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" while(x_range[-1] + stride_x + tile_size_x < width):\n",
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" x_range += [x_range[-1] + stride_x]\n",
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" \n",
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" y_range = [0]\n",
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" while(y_range[-1] + stride_y + tile_size_y < height):\n",
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" y_range += [y_range[-1] + stride_y]\n",
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" \n",
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" counter = 0\n",
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" for x in x_range:\n",
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" for y in y_range:\n",
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" cropped = image.crop((x,y, x+tile_size_x, y+tile_size_y))\n",
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"\n",
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" file_name = \"{}\".format(y)\n",
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" file_name += \"_{}\".format(x) + \".tif\"\n",
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" path = os.path.join(clipped_item, file_name)\n",
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" \n",
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" cropped.save(path)\n",
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" \n"
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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": 10,
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"id": "ce60bf47-7235-43a1-a4f7-5b81080d617d",
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"metadata": {},
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"outputs": [
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{
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"ename": "TypeError",
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"evalue": "stat: path should be string, bytes, os.PathLike or integer, not NoneType",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[10], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m sliding_window(directory_path, destination, tile_size_x, tile_size_y, stride_x, stride_y)\n",
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"Cell \u001b[0;32mIn[9], line 3\u001b[0m, in \u001b[0;36msliding_window\u001b[0;34m(directory_path, destination, tile_size_x, tile_size_y, stride_x, stride_y)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msliding_window\u001b[39m(directory_path, destination, tile_size_x, tile_size_y, stride_x, stride_y):\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39misdir(destination):\n\u001b[1;32m 4\u001b[0m clear_directory(destination)\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m: \n",
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"File \u001b[0;32m<frozen genericpath>:42\u001b[0m, in \u001b[0;36misdir\u001b[0;34m(s)\u001b[0m\n",
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"\u001b[0;31mTypeError\u001b[0m: stat: path should be string, bytes, os.PathLike or integer, not NoneType"
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]
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}
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],
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"source": [
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"sliding_window(directory_path, destination, tile_size_x, tile_size_y, stride_x, stride_y)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.11.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎component-library/input/image-tiling.job.yaml‎

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apiVersion: batch/v1
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kind: Job
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metadata:
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name: image-tiling
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spec:
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template:
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spec:
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containers:
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- name: image-tiling
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image: docker.io/mdorzweiler/claimed-image-tiling:0.1
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workingDir: /opt/app-root/src/
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command: ["/opt/app-root/bin/ipython","claimed_image-tiling.ipynb"]
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env:
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- name: log_level
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value: value_of_log_level
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- name: directory_path
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value: value_of_directory_path
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- name: destination
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value: value_of_destination
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- name: tile_size_x
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value: value_of_tile_size_x
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- name: tile_size_y
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value: value_of_tile_size_y
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- name: stride_x
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value: value_of_stride_x
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- name: stride_y
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value: value_of_stride_y
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restartPolicy: OnFailure
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imagePullSecrets:
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- name: image_pull_secret

‎component-library/input/image-tiling.yaml‎

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name: image-tiling
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description: "## Xview Dataset clipping – CLAIMED V0.1"
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inputs:
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- {name: log_level, type: String, description: "update log level", default: "INFO"}
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- {name: directory_path, type: String, description: "directory_path is the path to the folder with the unzipped .tif images from xview dataset"}
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- {name: destination, type: String, description: "destination is the path to the folder which saves all the extracted tiles."}
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- {name: tile_size_x, type: String, description: "Each image is cropped using a rectangular window with edge_length tile_size_x and tile_size_y which has to be given in number of pixels"}
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- {name: tile_size_y, type: String, description: ""}
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- {name: stride_x, type: String, description: "For tumbling window stride_x must equal tile_size_x and stride_y must equal tile_size_y"}
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- {name: stride_y, type: String, description: ""}
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outputs:
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implementation:
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container:
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image: docker.io/mdorzweiler/claimed-image-tiling:0.1
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command:
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- sh
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- -ec
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- |
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ipython ./claimed_image-tiling.ipynb log_level="${0}" directory_path="${1}" destination="${2}" tile_size_x="${3}" tile_size_y="${4}" stride_x="${5}" stride_y="${6}"
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- {inputValue: log_level}
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- {inputValue: directory_path}
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- {inputValue: destination}
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- {inputValue: tile_size_x}
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- {inputValue: tile_size_y}
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- {inputValue: stride_x}
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- {inputValue: stride_y}

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