def generate_current_image(self, next_image, current_depth, transformation_from_current_to_next):
generated_current_image = kornia.warp_frame_depth(next_image,
current_depth,
transformation_from_current_to_next,
self.camera_matrix)
return generated_current_image
def _get_synthesized_image(self):
self._model.eval()
data_point = self._dataset_manager.get_validation_dataset(
with_normalize=True)[0]
with torch.no_grad():
left_current_depth = self._model.depth(
data_point["left_current_image"][None].to(self._device))
right_current_depth = self._model.depth(
data_point["right_current_image"][None].to(self._device))
data_point = self._dataset_manager.get_validation_dataset(
with_normalize=False)[0]
left_current_image = data_point["left_current_image"][None].to(
self._device)
right_current_image = data_point["right_current_image"][None].to(
self._device)
cameras_calibration = self._dataset_manager.get_cameras_calibration(
device=self._device)
with torch.no_grad():
generated_left_image = kornia.warp_frame_depth(
right_current_image, left_current_depth,
torch.inverse(
cameras_calibration.transform_from_left_to_right),
cameras_calibration.left_camera_matrix)
generated_right_image = kornia.warp_frame_depth(
left_current_image, right_current_depth,
cameras_calibration.transform_from_left_to_right,
cameras_calibration.left_camera_matrix)
figure = plt.figure(dpi=200, figsize=(9, 6))
plt.subplot(3, 2, 1)
image = left_current_image[0].cpu().permute(1, 2, 0).detach().numpy()
plt.imshow(np.clip(image, 0, 1))
self.set_title("Left current image")
plt.subplot(3, 2, 2)
image = right_current_image[0].cpu().permute(1, 2, 0).detach().numpy()
plt.imshow(np.clip(image, 0, 1))
self.set_title("Right current image")
plt.subplot(3, 2, 3)
depth_image = left_current_depth[0].detach().cpu().permute(
1, 2, 0).numpy()[:, :, 0]
plt.imshow(np.clip(1.0 / depth_image, 0, 100) / 100, cmap="inferno")
self.set_title("Left current depth")
plt.subplot(3, 2, 4)
depth_image = right_current_depth[0].detach().cpu().permute(
1, 2, 0).numpy()[:, :, 0]
plt.imshow(np.clip(1.0 / depth_image, 0, 100) / 100, cmap="inferno")
self.set_title("Right current depth")
plt.subplot(3, 2, 5)
image = generated_left_image[0].cpu().permute(1, 2, 0).detach().numpy()
plt.imshow(np.clip(image, 0, 1))
self.set_title("Generated left image")
plt.subplot(3, 2, 6)
image = generated_right_image[0].cpu().permute(1, 2,
0).detach().numpy()
plt.imshow(np.clip(image, 0, 1))
self.set_title("Generated right image")
return {"generated": figure}