Delete diffusionsfm/inference/predict.py

diffusionsfm/inference/predict.py

@@ -1,93 +0,0 @@
-from diffusionsfm.inference.ddim import inference_ddim
-from diffusionsfm.utils.rays import (
-    Rays,
-    rays_to_cameras,
-    rays_to_cameras_homography,
-)
-
-
-def predict_cameras(
-    model,
-    images,
-    device,
-    crop_parameters=None,
-    num_patches_x=16,
-    num_patches_y=16,
-    additional_timesteps=(),
-    calculate_intrinsics=False,
-    max_num_images=None,
-    mode=None,
-    return_rays=False,
-    use_homogeneous=False,
-    seed=0,
-):
-    """
-    Args:
-        images (torch.Tensor): (N, C, H, W)
-        crop_parameters (torch.Tensor): (N, 4) or None
-    """
-    if calculate_intrinsics:
-        ray_to_cam = rays_to_cameras_homography
-    else:
-        ray_to_cam = rays_to_cameras
-
-    get_spatial_rays = Rays.from_spatial
-
-    rays_final, rays_intermediate, pred_intermediate, _ = inference_ddim(
-        model,
-        images.unsqueeze(0),
-        device,
-        visualize=True,
-        crop_parameters=crop_parameters.unsqueeze(0),
-        num_patches_x=num_patches_x,
-        num_patches_y=num_patches_y,
-        pbar=False,
-        eta=[1, 0],
-        num_inference_steps=100,
-    )
-
-    spatial_rays = get_spatial_rays(
-        rays_final[0],
-        mode=mode,
-        num_patches_x=num_patches_x,
-        num_patches_y=num_patches_y,
-        use_homogeneous=use_homogeneous,
-    )
-
-    pred_cam = ray_to_cam(
-        spatial_rays,
-        crop_parameters,
-        num_patches_x=num_patches_x,
-        num_patches_y=num_patches_y,
-        depth_resolution=model.depth_resolution,
-        average_centers=True,
-        directions_from_averaged_center=True,
-    )
-
-    additional_predictions = []
-    for t in additional_timesteps:
-        ray = pred_intermediate[t]
-
-        ray = get_spatial_rays(
-            ray[0],
-            mode=mode,
-            num_patches_x=num_patches_x,
-            num_patches_y=num_patches_y,
-            use_homogeneous=use_homogeneous,
-        )
-
-        cam = ray_to_cam(
-            ray,
-            crop_parameters,
-            num_patches_x=num_patches_x,
-            num_patches_y=num_patches_y,
-            average_centers=True,
-            directions_from_averaged_center=True,
-        )
-        if return_rays:
-            cam = (cam, ray)
-        additional_predictions.append(cam)
-
-    if return_rays:
-        return (pred_cam, spatial_rays), additional_predictions
-    return pred_cam, additional_predictions, spatial_rays