add: [core] Adding a distance only algorithm, using already present features. COMMIT EXAMPLE OF HOW TO DO IT ! Very useful ! Algorithm : RANSAC + ORB + Geometrical verifications

Author: Vincent-CIRCL

carlhauser_server/Configuration/distance_engine_conf.py

@@ -9,6 +9,12 @@ class BOW_CMP_HIST(JSON_parsable_Enum, Enum):
     BHATTACHARYYA = auto()
 
 
+
+class RANSAC_METHOD(JSON_parsable_Enum, Enum):
+    CORREL = auto()  # Standard
+    BHATTACHARYYA = auto()
+
+
 class Default_distance_engine_conf(JSON_parsable_Dict):
     def __init__(self):
         # Inputs
@@ -23,9 +29,13 @@ def __init__(self):
         # ORB PARAMETERS
         self.CROSSCHECK: bool = True
 
-        # Bow_ORB PARAMETERS
+        # BOW_ORB PARAMETERS
         self.BOW_CMP_HIST = BOW_CMP_HIST.CORREL.name
 
+        # RANSAC_ORB
+        self.MATCHES_THRESHOLD_TO_ACCELERATE = 0.65
+        self.MIN_NB_MATCHES_TO_FIND_HOMOGRAPHY = 10
+
 
 def parse_from_dict(conf):
     tmp_conf = Default_distance_engine_conf()

carlhauser_server/Configuration/feature_extractor_conf.py

@@ -35,27 +35,30 @@ def __init__(self):
 
         # HASH parameters
         self.A_HASH: Algo_conf = Algo_conf("A_HASH", False, 0.02, 0.08, distance_weight=1)
-        self.P_HASH: Algo_conf = Algo_conf("P_HASH", True, 0.08, 0.08, distance_weight=1)  # True
+        self.P_HASH: Algo_conf = Algo_conf("P_HASH", False, 0.08, 0.08, distance_weight=1)  # True
         self.P_HASH_SIMPLE: Algo_conf = Algo_conf("P_HASH_SIMPLE", False, 0.04, 0.06, distance_weight=1)
-        self.D_HASH: Algo_conf = Algo_conf("D_HASH", True, 0.04, 0.08, distance_weight=1)  # True
+        self.D_HASH: Algo_conf = Algo_conf("D_HASH", False, 0.04, 0.08, distance_weight=1)  # True
         self.D_HASH_VERTICAL: Algo_conf = Algo_conf("D_HASH_VERTICAL", False, 0.04, 0.04, distance_weight=1)
         self.W_HASH: Algo_conf = Algo_conf("W_HASH", False, 0.06, 0.08, distance_weight=1)
-        self.TLSH: Algo_conf = Algo_conf("TLSH", True, 0.16, 0.18, distance_weight=1)  # True
+        self.TLSH: Algo_conf = Algo_conf("TLSH", False, 0.16, 0.18, distance_weight=1)  # True
 
         # Visual Descriptors parameters
-        self.ORB: Algo_conf = Algo_conf("ORB", False, 0.0, 0.2, distance_weight=5)  # True
+        self.ORB: Algo_conf = Algo_conf("ORB", False, 0.0, 0.2, distance_weight=5)  # False
         self.ORB_KEYPOINTS_NB: int = 500
 
-        self.BOW_ORB: Algo_conf = Algo_conf("BOW_ORB", True, 0.08, 0.32, distance_weight=5)  # True
+        self.BOW_ORB: Algo_conf = Algo_conf("BOW_ORB", False, 0.08, 0.32, distance_weight=5)  # True
         self.BOW_VOCAB_PATH: pathlib.Path = get_homedir() / "vocab.npy"
 
+        self.RANSAC_ORB: Algo_conf = Algo_conf("RANSAC_ORB", True, 0.08, 0.32, distance_weight=10)  # False
+
         # Algo list # /! IMPORTANT !\ BE-AWARE THAT /! IMPORTANT !\
         # IF YOU MODIFY PROGRAMMATICALLY ONE ELEMENT LATER, YOU NEED TO CHANGE IT IN THIS LIST TOO !
         self.list_algos: List[Algo_conf] = [self.A_HASH, self.P_HASH, self.P_HASH_SIMPLE,
                                             self.D_HASH, self.D_HASH_VERTICAL, self.W_HASH,
                                             self.TLSH,
                                             self.ORB,
-                                            self.BOW_ORB]
+                                            self.BOW_ORB,
+                                            self.RANSAC_ORB]
 
         # Merging method
         self.DISTANCE_MERGING_METHOD: Distance_MergingMethod = Distance_MergingMethod.WEIGHTED_MEAN.name

carlhauser_server/DistanceEngine/distance_engine.py

@@ -12,6 +12,7 @@
 import carlhauser_server.DistanceEngine.distance_hash as distance_hash
 import carlhauser_server.DistanceEngine.distance_orb as distance_orb
 import carlhauser_server.DistanceEngine.distance_bow_orb as distance_bow_orb
+import carlhauser_server.DistanceEngine.distance_ransac_orb as distance_ransac_orb
 import carlhauser_server.DistanceEngine.merging_engine as merging_engine
 import carlhauser_server.DistanceEngine.scoring_datastrutures as scoring_datastrutures
 from common.CustomException import AlgoFeatureNotPresentError
@@ -43,6 +44,9 @@ def __init__(self, parent: database_worker, db_conf: database_conf.Default_datab
         self.distance_hash = distance_hash.Distance_Hash(db_conf, dist_conf, fe_conf)
         self.distance_orb = distance_orb.Distance_ORB(db_conf, dist_conf, fe_conf)
         self.distance_bow_orb = distance_bow_orb.Distance_BoW_ORB(db_conf, dist_conf, fe_conf)
+        self.distance_ransac_orb = distance_ransac_orb.Distance_RANSAC_ORB(db_conf, dist_conf, fe_conf)
+
+        # Create merging engine
         self.merging_engine = merging_engine.Merging_Engine(db_conf, dist_conf, fe_conf)
 
     # ==================== ------ INTER ALGO DISTANCE ------- ====================
@@ -80,6 +84,14 @@ def get_dist_and_decision_algos_to_algos(self, pic_package_from: Dict, pic_packa
         except AlgoFeatureNotPresentError as e:
             self.logger.warning(f"No feature present for bow-orbing algorithms.Normal if BOW-ORB is not activated in configuration. Error : {e}")
 
+        # Get RANSAC-ORB distances
+        try:
+            ransac_orb_dict = self.distance_ransac_orb.ransac_orb_distance(pic_package_from, pic_package_to)
+            self.logger.debug(f"Computed RANSAC-orb distance : {ransac_orb_dict}")
+            merged_dict.update(ransac_orb_dict)
+        except AlgoFeatureNotPresentError as e:
+            self.logger.warning(f"No feature present for RANSAC-orbing algorithms. Normal if RANSAC-ORB is not activated in configuration. Error : {e}")
+
         self.logger.debug(f"Distance dict : {merged_dict}")
         return merged_dict