Modify syn data creation to use separate projector calibration data

data/create_syn_data.py

@@ -90,7 +90,7 @@ def get_mesh(rng, min_z=0):
     return verts, faces, colors, normals
 
 
-def create_data(out_root, idx, n_samples, imsize, patterns, K, baseline, blend_im, noise, track_length=4):
+def create_data(out_root, idx, n_samples, imsize, patterns, K_cam, K_proj, baseline, blend_im, noise, track_length=4):
     tic = time.time()
     rng = np.random.RandomState()
 
@@ -139,17 +139,21 @@ def create_data(out_root, idx, n_samples, imsize, patterns, K, baseline, blend_i
         # render the scene at multiple scales
         scales = [1, 0.5, 0.25, 0.125]
         for scale in scales:
-            fx = K[0, 0] * scale
-            fy = K[1, 1] * scale
-            px = K[0, 2] * scale
-            py = K[1, 2] * scale
+            fx_cam = K_cam[0, 0] * scale
+            fy_cam = K_cam[1, 1] * scale
+            px_cam = K_cam[0, 2] * scale
+            py_cam = K_cam[1, 2] * scale
+            fx_proj = K_proj[0, 0] * scale
+            fy_proj = K_proj[1, 1] * scale
+            px_proj = K_proj[0, 2] * scale
+            py_proj = K_proj[1, 2] * scale
             im_height = imsize[0] * scale // 1
             im_width = imsize[1] * scale // 1
-            cams.append(renderer.PyCamera(fx, fy, px, py, Rcam, tcam, im_width, im_height))
-            projs.append(renderer.PyCamera(fx, fy, px, py, Rproj, tproj, im_width, im_height))
+            cams.append(renderer.PyCamera(fx_cam, fy_cam, px_cam, py_cam, Rcam, tcam, im_width, im_height))
+            projs.append(renderer.PyCamera(fx_proj, fy_proj, px_proj, py_proj, Rproj, tproj, im_width, im_height))
 
         for s, cam, proj, pattern in zip(itertools.count(), cams, projs, patterns):
-            fl = K[0, 0] / (2 ** s)
+            fl = K_cam[0, 0] / (2 ** s)
 
             shader = renderer.PyShader(0.5, 1.5, 0.0, 10)
             pyrenderer = renderer.PyRenderer(cam, shader, engine='gpu')
@@ -208,8 +212,9 @@ def load_camera_parameters():
     # weird casting cause the values are str(float) (eg. '123.'), but we want int
     imsize = [int(float(x)) for x in cam_mat['opencv_storage']['img_shape']['data'].split()]
     K_shape = int(cam_mat['opencv_storage']['cam_int']['rows']), int(cam_mat['opencv_storage']['cam_int']['cols'])
-    K = np.array(cam_mat['opencv_storage']['cam_int']['data'].split(), dtype=float).reshape(K_shape).T
-    return imsize, K
+    K_cam = np.array(cam_mat['opencv_storage']['cam_int']['data'].split(), dtype=float).reshape(K_shape).T
+    K_proj = np.array(cam_mat['opencv_storage']['proj_int']['data'].split(), dtype=float).reshape(K_shape).T
+    return imsize, K_cam, K_proj
 
 
 if __name__ == '__main__':
@@ -242,7 +247,7 @@ if __name__ == '__main__':
     objs = get_objs(shapenet_root, obj_classes)
 
     # camera parameters
-    imsize, K = load_camera_parameters()
+    imsize, K_cam, K_proj = load_camera_parameters()
     # remember what was set in the settings
     imsize = settings_imsize
 
@@ -278,5 +283,5 @@ if __name__ == '__main__':
     # start the job
     n_samples = 2 ** 10 + 2 ** 13
     for idx in range(start, n_samples):
-        args = (out_root, idx, n_samples, imsize, patterns, K, baseline, blend_im, noise, track_length)
+        args = (out_root, idx, n_samples, imsize, patterns, K_cam, K_proj, baseline, blend_im, noise, track_length)
         create_data(*args)