fixes to matching and utils

ronshnapp · Oct 23, 2024 · f3d8e8c · f3d8e8c
1 parent 9c7d966
commit f3d8e8c
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Showing 2 changed files with 22 additions and 11 deletions.
diff --git a/myptv/particle_matching_mod.py b/myptv/particle_matching_mod.py
@@ -331,19 +331,9 @@ def find_candidates_with_two_cameras(self, camNum1, camNum2, frame):
         blob pairs in two given cameras. The points that are found are then
         returned.
         '''
-<<<<<<< HEAD
-
-        # if there are no blobs in this frame, return empty list
-        if frame not in self.blobs[camNum1].keys():
-            return []
-
-        if frame not in self.blobs[camNum2].keys():
-            return []
-=======
         # ensure the cameras have blobs in this frame
         if frame not in list(self.blobs[camNum1].keys()): return []
         if frame not in list(self.blobs[camNum2].keys()): return []
->>>>>>> bug fix regarding frames with no blobs in  matching
 
         # fetching the cameras and the blobs
         cam1 = self.imsys.cameras[camNum1] ; cam2 = self.imsys.cameras[camNum2]

diff --git a/myptv/utils.py b/myptv/utils.py
@@ -230,6 +230,7 @@ def __init__(self, camera, blob_fname, target_file_fname):
         self.cam = camera
         self.blobs = loadtxt(blob_fname)
         self.targets = loadtxt(target_file_fname)
+        self.get_neighbor_separation()
 
 
     def pair_points(self):
@@ -250,14 +251,34 @@ def pair_points(self):
                     d_min = d
                     j_min = j
 
-            if d_min < 30:
+            if d_min < self.dmin/2:
                 blob_point_pair = NPappend(self.blobs[i][1::-1],
                                             self.targets[j_min])
                 point_pairs.append(blob_point_pair)
 
         self.point_pairs = point_pairs
 
 
+    def get_neighbor_separation(self):
+        '''
+        returns an estimate for the minimum separation distance between blobs.
+        '''
+        bxy = self.blobs[:,1::-1]
+        dmin = 1e20
+        N = len(bxy)
+        i=0
+
+        for i in range(min([N,20])):
+            for j in range(N):
+                if j==i: continue
+                d = sum((bxy[i] - bxy[j])**2)**0.5
+                if d<dmin:
+                    dmin = d
+        print('dmin: ', dmin)
+        self.dmin = dmin
+
+
+
     def save_results(self, fname):
         '''
         Saves the pairs of blobs and target points in a given file name.