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‎.devcontainer/Dockerfile

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# Use the official Python image
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FROM python:3.10-slim
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# Set the working directory in the container
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WORKDIR /workspace
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# Copy your project files to the container
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COPY . /workspace
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# Install any additional dependencies required by your project
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RUN pip install --no-cache-dir -r .devcontainer/requirements.txt
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# Expose port 8000 (or whatever port your application uses)
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EXPOSE 8000
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# Set the default command to run your Python application
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CMD ["python3", "main.py"]

‎.devcontainer/devcontainer.json

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{
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"name": "Python Dev Container",
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"build": {
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"dockerfile": "Dockerfile",
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"context": ".."
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},
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"customizations": {
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"vscode": {
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"extensions": [
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"ms-python.python",
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"ms-python.vscode-pylance",
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"akamud.vscode-theme-onedark",
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"vscode-icons-team.vscode-icons",
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"ms-azuretools.vscode-docker",
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"github.copilot",
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"ms-toolsai.jupyter",
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"mechatroner.rainbow-csv"
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],
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"settings": {
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"terminal.integrated.shell.linux": "/bin/bash",
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"workbench.colorTheme": "Atom One Dark",
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"workbench.iconTheme": "vscode-icons"
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}
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}
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},
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"forwardPorts": [8000],
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"postCreateCommand": "pip install -r .devcontainer/requirements.txt",
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"remoteUser": "root"
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}

‎.devcontainer/requirements.txt

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opencv-python

‎datasets/aalesund/1504200/200.jpg

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‎datasets/aalesund/1504200/200.sos

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.HODE
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..PRODUSENT "Bravida Geomatikk AS"
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..EIER "�lesund kommune"
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..KOMM 1504
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..TEGNSETT ISO8859-10
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..TRANSPAR
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...KOORDSYS 110
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...ORIGO-N� 0 0
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...ENHET 1.000
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..OMR�DE
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...MIN-N� 496779 13727
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...MAX-N� 497712 15419
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..SOSI-VERSJON 3.3
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..SOSI-NIV� 2
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..DATO 20040929
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..KVALITET 79
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.RASTER 1:
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..BILDE
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...BILDE-SYS 110
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...BILDE-TYPE JPEG
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...BILDE-FIL "200.jpg"
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..PIXEL-ST�RR 0.1000000000 0.1000000000
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! Antall pixler i N , � : 9325 , 16908
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..N�
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496779 13727
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497712 15418
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.SLUTT

‎datasets/aalesund/1504200/200_tegnforklaring.pdf

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‎datasets/aalesund/1504201/201.jpg

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‎datasets/aalesund/1504201/201.sos

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.HODE
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..PRODUSENT "Bravida Geomatikk AS"
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..EIER "�lesund Kommune"
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..KOMM 1504
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..TEGNSETT ISO8859-10
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..TRANSPAR
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...KOORDSYS 110
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...ORIGO-N� 0 0
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...ENHET 1.000
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..OMR�DE
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...MIN-N� 497197 16072
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...MAX-N� 498311 16977
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..SOSI-VERSJON 3.3
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..SOSI-NIV� 2
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..DATO 20041001
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..KVALITET 79
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.RASTER 1:
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..BILDE
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...BILDE-SYS 110
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...BILDE-TYPE JPEG
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...BILDE-FIL "201.jpg"
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..PIXEL-ST�RR 0.1000000000 0.1000000000
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! Antall pixler i N , � : 11132 , 9036
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..N�
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497197 16073
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498310 16976
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.SLUTT

‎datasets/aalesund/1504201/201_tegnforklaring.pdf

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‎datasets/molde/0488/0488_plankart.tif

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‎datasets/molde/0488/0488_tegnforklaring.jpg

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‎datasets/molde/2102/2102_plankart.pdf

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‎datasets/molde/2102/2102_tegnforklaring.jpg

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‎how-to-segment-anything-with-sam.ipynb

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‎src/sam_segmentation.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"ename": "error",
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"evalue": "OpenCV(4.10.0) D:\\a\\opencv-python\\opencv-python\\opencv\\modules\\imgproc\\src\\smooth.dispatch.cpp:617: error: (-215:Assertion failed) !_src.empty() in function 'cv::GaussianBlur'\n",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31merror\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[1;32mIn[3], line 7\u001b[0m\n\u001b[0;32m 4\u001b[0m img \u001b[38;5;241m=\u001b[39m cv2\u001b[38;5;241m.\u001b[39mimread(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdatasets\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124maalesund\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124m1504200\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124m200.jpg\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;241m0\u001b[39m)\n\u001b[0;32m 6\u001b[0m \u001b[38;5;66;03m# Apply Gaussian Blur to reduce noise\u001b[39;00m\n\u001b[1;32m----> 7\u001b[0m blurred_img \u001b[38;5;241m=\u001b[39m \u001b[43mcv2\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mGaussianBlur\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m 9\u001b[0m \u001b[38;5;66;03m# Apply adaptive thresholding to separate background and foreground\u001b[39;00m\n\u001b[0;32m 10\u001b[0m threshold_img \u001b[38;5;241m=\u001b[39m cv2\u001b[38;5;241m.\u001b[39madaptiveThreshold(blurred_img, \u001b[38;5;241m255\u001b[39m, cv2\u001b[38;5;241m.\u001b[39mADAPTIVE_THRESH_GAUSSIAN_C, \n\u001b[0;32m 11\u001b[0m cv2\u001b[38;5;241m.\u001b[39mTHRESH_BINARY, \u001b[38;5;241m11\u001b[39m, \u001b[38;5;241m2\u001b[39m)\n",
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"\u001b[1;31merror\u001b[0m: OpenCV(4.10.0) D:\\a\\opencv-python\\opencv-python\\opencv\\modules\\imgproc\\src\\smooth.dispatch.cpp:617: error: (-215:Assertion failed) !_src.empty() in function 'cv::GaussianBlur'\n"
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]
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}
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],
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"source": [
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"import cv2\n",
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"\n",
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"# Load the scanned map\n",
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"img = cv2.imread('datasets\\\\aalesund\\\\1504200\\\\200.jpg', 0)\n",
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"\n",
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"# Apply Gaussian Blur to reduce noise\n",
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"blurred_img = cv2.GaussianBlur(img, (5, 5), 0)\n",
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"\n",
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"# Apply adaptive thresholding to separate background and foreground\n",
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"threshold_img = cv2.adaptiveThreshold(blurred_img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, \n",
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" cv2.THRESH_BINARY, 11, 2)\n",
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"\n",
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"# Display the processed image\n",
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"cv2.imshow('Processed Image', threshold_img)\n",
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"cv2.waitKey(0)\n",
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"cv2.destroyAllWindows()\n"
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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",
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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": "3.12.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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