Works on cropped videos.

Pose2Sim/Utilities/calib_qca_to_toml.py

@@ -54,9 +54,11 @@ def read_qca(qca_path, binning_factor):
     C, S, D, K, R, T = [], [], [], [], [], []
 
     # Camera name
-    for tag in root.findall('cameras/camera'):
+    for i, tag in enumerate(root.findall('cameras/camera')):
+        ret += [float(tag.attrib.get('avg-residual'))/1000]
+        C += [tag.attrib.get('serial')]
         if tag.attrib.get('model') in ('Miqus Video', 'Miqus Video UnderWater', 'none'):
-            C += [tag.attrib.get('serial')]
+            vid_id += [i]
 
     # Image size
     for tag in root.findall('cameras/camera/fov_video'):
@@ -65,7 +67,7 @@ def read_qca(qca_path, binning_factor):
         S += [[w, h]]
     
     # Intrinsic parameters: distorsion and intrinsic matrix
-    for tag in root.findall('cameras/camera/intrinsic'):
+    for i, tag in enumerate(root.findall('cameras/camera/intrinsic')):
         k1 = float(tag.get('radialDistortion1'))/64/binning_factor
         k2 = float(tag.get('radialDistortion2'))/64/binning_factor
         p1 = float(tag.get('tangentalDistortion1'))/64/binning_factor
@@ -74,15 +76,17 @@ def read_qca(qca_path, binning_factor):
         
         fu = float(tag.get('focalLengthU'))/64/binning_factor
         fv = float(tag.get('focalLengthV'))/64/binning_factor
-        cu = float(tag.get('centerPointU'))/64/binning_factor
-        cv = float(tag.get('centerPointV'))/64/binning_factor
+        cu = float(tag.get('centerPointU'))/64/binning_factor \
+            - float(root.findall('cameras/camera/fov_video')[i].attrib.get('left'))
+        cv = float(tag.get('centerPointV'))/64/binning_factor \
+            - float(root.findall('cameras/camera/fov_video')[i].attrib.get('top'))
         K += [np.array([fu, 0., cu, 0., fv, cv, 0., 0., 1.]).reshape(3,3)]
 
     # Extrinsic parameters: rotation matrix and translation vector
     for tag in root.findall('cameras/camera/transform'):
-        tx = float(tag.get('x'))
-        ty = float(tag.get('y'))
-        tz = float(tag.get('z'))
+        tx = float(tag.get('x'))/1000
+        ty = float(tag.get('y'))/1000
+        tz = float(tag.get('z'))/1000
         r11 = float(tag.get('r11'))
         r12 = float(tag.get('r12'))
         r13 = float(tag.get('r13'))
@@ -98,13 +102,16 @@ def read_qca(qca_path, binning_factor):
         T += [np.array([tx, ty, tz])]
    
     # Cameras names by natural order
-    C_index = [C.index(c) for c in natural_sort(C)]
-    C = [C[c] for c in C_index]
-    S = [S[c] for c in C_index]
-    D = [D[c] for c in C_index]
-    K = [K[c] for c in C_index]
-    R = [R[c] for c in C_index]
-    T = [T[c] for c in C_index]
+    C_vid = [C[v] for v in vid_id]
+    C_vid_id = [C_vid.index(c) for c in natural_sort(C_vid)]
+    C_id = [vid_id[c] for c in C_vid_id]
+    C = [C[c] for c in C_id]
+    ret = [ret[c] for c in C_id]
+    S = [S[c] for c in C_id]
+    D = [D[c] for c in C_id]
+    K = [K[c] for c in C_id]
+    R = [R[c] for c in C_id]
+    T = [T[c] for c in C_id]
    
     return C, S, D, K, R, T