From 95cd8d5f36249fa306f1a0e1d51b5e9bbcf7bc6c Mon Sep 17 00:00:00 2001 From: JerelHJ <115962731+JerelHJ@users.noreply.github.com> Date: Thu, 1 Feb 2024 20:56:13 +0800 Subject: [PATCH] Splitting the SecGuardID gps pathway --- Images/Individual_Plots/plot_SecGuardID_1.png | Bin 0 -> 357238 bytes Images/Individual_Plots/plot_SecGuardID_2.png | Bin 0 -> 357238 bytes Images/plot.png | Bin 242303 -> 0 bytes Images/plot_SecGuardID_1.png | Bin 0 -> 245364 bytes Images/plot_SecGuardID_2.png | Bin 0 -> 272368 bytes index.php | 30 +---- python/seer2.py | 121 ++++++++++-------- 7 files changed, 72 insertions(+), 79 deletions(-) create mode 100644 Images/Individual_Plots/plot_SecGuardID_1.png create mode 100644 Images/Individual_Plots/plot_SecGuardID_2.png delete mode 100644 Images/plot.png create mode 100644 Images/plot_SecGuardID_1.png create mode 100644 Images/plot_SecGuardID_2.png diff --git a/Images/Individual_Plots/plot_SecGuardID_1.png b/Images/Individual_Plots/plot_SecGuardID_1.png new file 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    - - Select Security Guard's name to track pathway - + - Security Guard's pathway -


    - -
    - - -

    - + Image + Image



    diff --git a/python/seer2.py b/python/seer2.py index 281a653..7fb858c 100644 --- a/python/seer2.py +++ b/python/seer2.py @@ -1,18 +1,17 @@ import csv import numpy as np import cartopy.crs as ccrs -#%matplotlib import matplotlib.pyplot as plt import cartopy.io.img_tiles as cimgt from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter -import io,time +import io from urllib.request import urlopen, Request from PIL import Image plt.ion() import pandas as pd from sqlalchemy import create_engine -import sys - +import sys +import os # Replace the placeholder values with your actual database credentials servername = 'localhost' @@ -23,82 +22,96 @@ connection_string = f'mysql+mysqlconnector://root:@localhost:3306/geotrackdb' engine = create_engine(connection_string) qry = 'SELECT * FROM records;' -df = pd.read_sql_query(qry,engine) +df = pd.read_sql_query(qry, engine) # You can use the DataFrame columns to access specific data recordid = df['RecordID'].tolist() -secguard = df['SecGuardID'].tolist() +secguards = df['SecGuardID'].unique() # Get unique SecGuardIDs date = df['RecordTime'].tolist() alts = df['Altitude'].tolist() lats = df['Latitude'].tolist() lons = df['Longitude'].tolist() floors = df['Floor'].tolist() - def image_spoof(self, tile): - api_url = self._image_url(tile) # get the url of the street map API - req = Request(api_url) # start request - req.add_header('User-agent','Anaconda 3') # add user agent to request - response = urlopen(req) #Open the URL and get the response - im_data = io.BytesIO(response.read()) # Get image data - response.close() # Close the url - img = Image.open(im_data) # open image using PIL + api_url = self._image_url(tile) # get the url of the street map API + req = Request(api_url) # start request + req.add_header('User-agent', 'Anaconda 3') # add user agent to request + response = urlopen(req) # Open the URL and get the response + im_data = io.BytesIO(response.read()) # Get image data + response.close() # Close the url + img = Image.open(im_data) # open image using PIL img = img.convert(self.desired_tile_form) # Convert the image format - return img, self.tileextent(tile), 'lower' # Return the image, tile extent, and vertical alignment - - + return img, self.tileextent(tile), 'lower' # Return the image, tile extent, and vertical alignment -cimgt.GoogleTiles.get_image = image_spoof # Spoof the web request for street map -osm_img = cimgt.GoogleTiles() # Download the spoofed street map using the GoogleTiles class +cimgt.GoogleTiles.get_image = image_spoof # Spoof the web request for street map +osm_img = cimgt.GoogleTiles() # Download the spoofed street map using the GoogleTiles class lat_zoom = 0.0005 # Decreased zoom for latitude lon_zoom = 0.0025 # Decreased zoom for longitude -if lons and lats: - extent = [np.min(lons) - lon_zoom, np.max(lons) + lon_zoom, np.min(lats) - lat_zoom, np.max(lats) + lat_zoom] +# Create a directory for individual plots +individual_plots_directory = 'Images/Individual_Plots' +os.makedirs(individual_plots_directory, exist_ok=True) + +for secguard in secguards: + secguard_df = df[df['SecGuardID'] == secguard] + + if lons and lats: + extent = [ + np.min(secguard_df['Longitude']) - lon_zoom, + np.max(secguard_df['Longitude']) + lon_zoom, + np.min(secguard_df['Latitude']) - lat_zoom, + np.max(secguard_df['Latitude']) + lat_zoom + ] + + fig, ax1 = plt.subplots(figsize=(14, 12), facecolor='#FCFCFC', subplot_kw={'projection': osm_img.crs}) + ax1.set_title(f'GPS Tracker Map - SecGuardID {secguard}', fontsize=16) + + # Set the extents of the map + ax1.set_extent(extent) - fig = plt.figure(figsize=(14, 12), facecolor='#FCFCFC') - ax1 = plt.axes(projection=osm_img.crs) - ax1.set_title('GPS Tracker Map', fontsize=16) + # Set longitude and latitude indicators + ax1.set_xticks(np.linspace(extent[0], extent[1], 7), crs=ccrs.PlateCarree()) + ax1.set_yticks(np.linspace(extent[2], extent[3], 7)[1:], crs=ccrs.PlateCarree()) - # Set the extents of the map - ax1.set_extent(extent) + # Format the longitude and latitude tick labels + lon_format = LongitudeFormatter(number_format='0.1f', degree_symbol='', dateline_direction_label=True) + lat_format = LatitudeFormatter(number_format='0.1f', degree_symbol='') - # Set longitude and latitude indicators - ax1.set_xticks(np.linspace(extent[0], extent[1], 7), crs=ccrs.PlateCarree()) - ax1.set_yticks(np.linspace(extent[2], extent[3], 7)[1:], crs=ccrs.PlateCarree()) + # Set the major formatters for longitude and latitude + ax1.xaxis.set_major_formatter(lon_format) + ax1.yaxis.set_major_formatter(lat_format) - # Format the longitude and latitude tick labels - lon_format = LongitudeFormatter(number_format='0.1f', degree_symbol='', dateline_direction_label=True) - lat_format = LatitudeFormatter(number_format='0.1f', degree_symbol='') + # Set tick label font sizes + ax1.xaxis.set_tick_params(labelsize=14) + ax1.yaxis.set_tick_params(labelsize=14) - # Set the major formatters for longitude and latitude - ax1.xaxis.set_major_formatter(lon_format) - ax1.yaxis.set_major_formatter(lat_format) + # Empirical calculation of scale based on zoom + scale = np.ceil(-np.sqrt(2) * np.log(np.divide((extent[1] - extent[0]) / 2.0, 350.0))) - # Set tick label font sizes - ax1.xaxis.set_tick_params(labelsize=14) - ax1.yaxis.set_tick_params(labelsize=14) + # Ensure scale does not exceed 19 + scale = (scale < 20) and scale or 19 - # Empirical calculation of scale based on zoom - scale = np.ceil(-np.sqrt(2) * np.log(np.divide((extent[1] - extent[0]) / 2.0, 350.0))) + # Add the spoofed OSM image to the map with the specified zoom level + ax1.add_image(osm_img, int(scale + 1)) - # Ensure scale does not exceed 19 - scale = (scale < 20) and scale or 19 + for index in range(0, len(secguard_df['Longitude']), 5): + ax1.plot(secguard_df['Longitude'].iloc[index], secguard_df['Latitude'].iloc[index], markersize=10, + marker='o', linestyle='', color='Black', transform=ccrs.PlateCarree(), label='GPS Point') # plot points - # Add the spoofed OSM image to the map with the specified zoom level - ax1.add_image(osm_img, int(scale + 1)) + annotation_text = f'Alt: {secguard_df["Altitude"].iloc[index]:.2f} meters\nFloor: {secguard_df["Floor"].iloc[index]}' + ax1.text(secguard_df['Longitude'].iloc[index], secguard_df['Latitude'].iloc[index], annotation_text, + fontsize=10, color='red', transform=ccrs.PlateCarree(), ha='right', va='bottom') + plt.pause(0.1) + else: + print(f"Error: No data for SecGuardID {secguard}") -for index in range(0, len(lons), 5): - ax1.plot(lons[index], lats[index], markersize=10, marker='o', linestyle='', - color='Black', transform=ccrs.PlateCarree(), label='GPS Point') # plot points + # Save individual plots + plt.savefig(f'{individual_plots_directory}/plot_SecGuardID_{secguard}.png') + plt.show() - annotation_text = f'Alt: {alts[index]:.2f} meters\nFloor: {floors[index]}' - ax1.text(lons[index], lats[index], annotation_text, - fontsize=10, color='red', transform=ccrs.PlateCarree(), ha='right', va='bottom') + else: + print("Error: lons or lats list is empty.") - plt.pause(0.01) -else: - print("Error: lons or lats list is empty.") -plt.savefig('Images/plot.png') \ No newline at end of file

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