Camera backside problem solved and visualizing resolution control added

tvcalib/utils/visualization_mpl_min.py

@@ -4,6 +4,7 @@
 import matplotlib.pyplot as plt
 from matplotlib.lines import Line2D
 from matplotlib.patches import Polygon, Rectangle
+import kornia
 
 
 def init_figure(img_width, img_height, img_delta_w=0.2, img_delta_h=0.1):
@@ -23,21 +24,43 @@ def init_figure(img_width, img_height, img_delta_w=0.2, img_delta_h=0.1):
     return fig, ax
 
 
-def draw_reprojection(ax, object3d, cam, dist_circles=0.25, kwargs={"alpha": 0.5, "linewidth": 5}):
+def draw_reprojection(ax, object3d, cam, ratio_width=1, ratio_height=1, dist_circles=0.25, kwargs={"alpha": 0.5, "linewidth": 5}):
+    # ndc is an abbreviation for Normalized Device Coordinates
+    # for more details, refer https://carmencincotti.com/2022-05-02/homogeneous-coordinates-clip-space-ndc/#ndc
+    ndc_point = torch.tensor([0., 0., 1.]).view(1, 3, 1)
+    point_3d = torch.bmm(cam.P_ndc.pinverse(), ndc_point)
+    principal_3d = kornia.geometry.conversions.convert_points_from_homogeneous(point_3d.transpose(1, 2))
 
+    # original projection
     lines3d = object3d.line_segments.transpose(0, 1).transpose(-1, -2)
-    for lidx, line_name in enumerate(object3d.line_segments_names):
+    points_px = torch.zeros((23, 2, 2))
+    for lidx in range(23):
         with torch.no_grad():
             line3d = lines3d[lidx]
-            points_px = cam.project_point2pixel(line3d, lens_distortion=False).cpu()[0, 0]
-            line2d = Line2D(
-                points_px[:, 0],
-                points_px[:, 1],
-                color=object3d.cmap_01[line_name],
-                **kwargs,
-            )
-            ax.add_line(line2d)
+            points_px[lidx, :, :] = cam.project_point2pixel(line3d, lens_distortion=False).cpu()[0, 0]
+
+    # Exception handling for camera back side problem
+    for lidx in range(23):
+        line3d = lines3d[lidx]
+        if (torch.dot(line3d[0] - cam.position.view(3), principal_3d.view(3) - cam.position.view(3)) < 0) and \
+                (torch.dot(line3d[1] - cam.position.view(3), principal_3d.view(3) - cam.position.view(3)) < 0):
+            continue
+        elif torch.dot(line3d[0] - cam.position.view(3), principal_3d.view(3) - cam.position.view(3)) < 0:
+            points_px[lidx][0] = points_px[lidx][1] + 10 * (points_px[lidx][1] - points_px[lidx][0])
+        elif torch.dot(line3d[1] - cam.position.view(3), principal_3d.view(3) - cam.position.view(3)) < 0:
+            points_px[lidx][1] = points_px[lidx][0] + 10 * (points_px[lidx][0] - points_px[lidx][1])
+
+    # draw lines
+    for lidx, line_name in enumerate(object3d.line_segments_names):
+        line2d = Line2D(
+            points_px[lidx, :, 0]*ratio_width,
+            points_px[lidx, :, 1]*ratio_height,
+            color=object3d.cmap_01[line_name],
+            **kwargs,
+        )
+        ax.add_line(line2d)
 
+    # draw circles
     points3d_circle = {
         k: torch.from_numpy(np.stack(v, axis=0)).float()
         for k, v in object3d._field_sncalib.sample_field_points(
@@ -48,6 +71,8 @@ def draw_reprojection(ax, object3d, cam, dist_circles=0.25, kwargs={"alpha": 0.5
     for circle_name, circle3d in points3d_circle.items():
         with torch.no_grad():
             points_px = cam.project_point2pixel(circle3d, lens_distortion=False).cpu()[0, 0]
+            points_px[:, 0] *= ratio_height
+            points_px[:, 1] *= ratio_width
             # print(circle_name, circle3d.shape, points_px.shape)
             circle2d = Polygon(
                 points_px[:, :2],