printing camera positions

gradio_app.py

@@ -95,7 +95,7 @@ def get_anchor_video(video_path, fps, num_frames, target_pose, mode,
         "--init_dx", str(init_dx),
         "--init_dy", str(init_dy),
         "--init_dz", str(init_dz),
-
+  
     ]   
 
     try:

inference/v2v_data/demo.py

@@ -154,6 +154,7 @@ class GetAnchorVideos:
                 opts.mask,
                 twice=False,
             )
+            
             warped_images.append(warped_frame2)
             masks.append(mask2)
         cond_video = (torch.cat(warped_images) + 1.0) / 2.0

inference/v2v_data/models/utils.py

@@ -181,18 +181,17 @@ def sphere2pose(c2ws_input, theta, phi, r, device, x=None, y=None):
 
 
 def generate_traj_specified(c2ws_anchor, theta, phi, d_r, d_x, d_y, frame, device, opts):
+    
     # Initialize a camera.
-
     camera_x = getattr(opts, "init_dx", 0.0)
     camera_y = getattr(opts, "init_dy", 0.0)
     camera_z = getattr(opts, "init_dz", 0.0)
-
     thetas = np.linspace(0, theta, frame)
     phis = np.linspace(0, phi, frame)
-
     rs = np.linspace(0, d_r, frame)+camera_z
     xs = np.linspace(0, d_x, frame)+camera_x
     ys = np.linspace(0, d_y, frame)+camera_y
+    print(f"thetas: {thetas}, phis: {phis}, rs: {rs}, xs: {xs}, ys: {ys}")
     # manipulate the above ones 
     c2ws_list = []
     for th, ph, r, x, y in zip(thetas, phis, rs, xs, ys):
@@ -205,6 +204,7 @@ def generate_traj_specified(c2ws_anchor, theta, phi, d_r, d_x, d_y, frame, devic
             np.float32(x),
             np.float32(y),
         )
+        print(f"c2w_new: {c2w_new}")
         c2ws_list.append(c2w_new)
     c2ws = torch.cat(c2ws_list, dim=0)
     return c2ws