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@ -28,7 +28,7 @@ Processing time scales with area, so 4x downscale = ~16x faster initial alignmen |
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Memory usage significantly reduced |
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""" |
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within_one_mile_check = True |
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within_one_mile_check = False |
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too_small = 1024 # 1KB |
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too_large = 10 * 1024 * 1024 # 10MB |
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@ -46,9 +46,9 @@ def handle_GPS(location1, location2): |
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if point1 == point2: |
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print("Images are both from same exact Location") |
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print("✅Possible duplicate") |
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if make1 == make2 and model1 == model2: |
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print("Cameras are the same.") |
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print("✅Possible duplicate") |
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delibs.exit_timer(5) |
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elif coordinates.are_within_one_mile(*point1, *point2) and within_one_mile_check == True: |
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if make1 == make2 and model1 == model2: |
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@ -57,9 +57,9 @@ def handle_GPS(location1, location2): |
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delibs.exit_timer(6) |
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else: |
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print("Images are from different Locations") |
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print("👌Not a Duplicate") |
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if make1 != make2 or model1 != model2: |
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print("Different Cameras detected.") |
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print("👌Not a Duplicate") |
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delibs.exit_timer(0) |
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def is_module_imported(module_name): |
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@ -92,7 +92,6 @@ def main(): |
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if (hash1 == hash2): |
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print("xxHash found duplicates") |
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print("❌ Perfect match - images are identical - Duplicate Found!") |
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print("No transformation needed") |
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delibs.exit_timer(1) |
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else: |
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print("Done hashing...") |
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@ -166,8 +165,8 @@ def main(): |
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# Check for perfect alignment |
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if matrix_score == 1.0 and decomposed_score == 1.0 and combined_score == 1.0: |
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print("❌ Perfect match - images are identical - Duplicate Found!") |
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print("No transformation needed") |
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print("❌ Perfect match - images are identical - Duplicate Found!") |
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exit_code = 1 |
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elif matrix_score > 0.9 and decomposed_score > 0.9 and combined_score > 0.7: |
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print("✅ Near-perfect alignment - minor differences detected") |
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