GPS Within 10 Feet checking...

coordinates.py

@@ -1,6 +1,7 @@
 from PIL import Image
 from PIL.ExifTags import TAGS, GPSTAGS
 import os
+import math
 
 """
 Copyright (c) 2025 by Robert Strutts
@@ -78,33 +79,34 @@ def get_lat_lon(gps_info):
     
 import math
 
-def haversine(lat1, lon1, lat2, lon2):
+def haversine_distance_feet(coord1, coord2):
     """
-    Calculate the great circle distance between two points 
+    Calculate the Haversine distance between two coordinates in feet.
-    on the earth (specified in decimal degrees)
+    Returns:
-    Returns distance in miles
+    float: distance in feet
     """
-    # Convert decimal degrees to radians 
+    # Earth radius in meters
-    lat1, lon1, lat2, lon2 = map(math.radians, [lat1, lon1, lat2, lon2])
+    R = 6371000
+    
+    lat1, lon1 = math.radians(coord1[0]), math.radians(coord1[1])
+    lat2, lon2 = math.radians(coord2[0]), math.radians(coord2[1])
     
-    # Haversine formula 
-    dlon = lon2 - lon1 
     dlat = lat2 - lat1
-    a = math.sin(dlat/2)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon/2)**2
+    dlon = lon2 - lon1
-    c = 2 * math.asin(math.sqrt(a)) 
+    
+    a = (math.sin(dlat/2)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon/2)**2)
+    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1-a))
     
-    # Radius of earth in miles (3956 for miles, 6371 for kilometers)
+    # Distance in meters
-    r = 3956
+    distance_meters = R * c
-    return c * r
     
-def are_within_one_mile(lat1, lon1, lat2, lon2):
+    # Convert to feet
-    distance = haversine(lat1, lon1, lat2, lon2)
+    return distance_meters * 3.28084
-    return distance <= 1
 
 """
 Example points:
-point1 = (40.7128, -74.0060)  # New York City
+point1 = (40.7484, -73.9857)  # Empire State Building coordinates (approximately)
-point2 = (40.7200, -74.0100)   # About 0.5 miles from NYC
+point2 = (40.748405, -73.985685)  # about 10 feet northeast of point1
 """
 
 def get_coordinates_from_image(image_path):

dedup.py

@@ -28,40 +28,52 @@ Processing time scales with area, so 4x downscale = ~16x faster initial alignmen
 Memory usage significantly reduced
 """
 
-within_one_mile_check = False
+within_feet_check = True
+withinFeet = 10 # < 10 feet
+# Photo File Size Limits:
 too_small = 1024 # 1KB
 too_large = 10 * 1024 * 1024 # 10MB
 
-def handle_GPS(location1, location2):
+def camera_check(camera_info1, camera_info2, diff_location = False):
-    camera_info1, latitude1, longitude1 = location1
     make1 = camera_info1['Make']
     model1 = camera_info1['Model']
-    
-    camera_info2, latitude2, longitude2 = location2
     make2 = camera_info2['Make']
     model2 = camera_info2['Model']
-    
+    if diff_location == True:
-    point1 = (latitude1, longitude1)
+        print("Images are from different Locations")
-    point2 = (latitude2, longitude2)
-    
-    if point1 == point2:
-        print("Images are both from same exact Location")
-        if make1 == make2 and model1 == model2:
-            print("Cameras are the same.")
-            print("✅Possible duplicate")
-            delibs.exit_timer(5)
-    elif coordinates.are_within_one_mile(*point1, *point2) and within_one_mile_check == True:
         if make1 == make2 and model1 == model2:
-            print("Images are within one mile")
             print("Cameras are the same.")
             delibs.exit_timer(6)
+        else:
+            print("Different Cameras detected.")
+            print("👌Not a Duplicate")
+            delibs.exit_timer(0)
     else:
-        print("Images are from different Locations")
         if make1 != make2 or model1 != model2:
             print("Different Cameras detected.")
             print("👌Not a Duplicate")
             delibs.exit_timer(0)
 
+def handle_GPS(location1, location2):
+    camera_info1, latitude1, longitude1 = location1
+    camera_info2, latitude2, longitude2 = location2
+    point1 = (latitude1, longitude1)
+    point2 = (latitude2, longitude2)
+    
+    if point1 == point2:
+        print("Images are both from same exact Location")
+        camera_check(camera_info1, camera_info2)
+    elif within_feet_check == True:
+        feet = coordinates.haversine_distance_feet(point1, point2)
+        print(f"Images distance in feet: {feet:.2f}")
+        if feet < withinFeet:
+            print(f"With in requirements of {withinFeet}")
+            camera_check(camera_info1, camera_info2)
+        else:
+            camera_check(camera_info1, camera_info2, True)
+    else:
+         camera_check(camera_info1, camera_info2, True)
+                
 def is_module_imported(module_name):
     return module_name in sys.modules