Add new whls and add 3DGS tab

app.py

@@ -6,7 +6,7 @@ import gradio as gr
 import torch
 from mast3r.demo import get_args_parser
 from mast3r_demo import mast3r_demo_tab
-# from gs_demo import gs_demo_tab
+from gs_demo import gs_demo_tab
 
 if __name__ == '__main__':
     # parser = get_args_parser()
@@ -27,8 +27,8 @@ if __name__ == '__main__':
         with gr.Tabs():
             with gr.Tab("MASt3R Demo"):
                 mast3r_demo_tab()
-            # with gr.Tab("Gaussian Splatting Demo"):
-            #     gs_demo_tab(cache_path)
+            with gr.Tab("Gaussian Splatting Demo"):
+                gs_demo_tab(cache_path)
 
         demo.launch(show_error=True, share=None, server_name=None, server_port=None) 
         # demo.launch(show_error=True, share=None, server_name='0.0.0.0', server_port=5555) 

demo/mast3r_demo.py

@@ -139,40 +139,40 @@ def get_3D_model_from_scene(scene, scene_state, min_conf_thr=2, as_pointcloud=Fa
     return _convert_scene_output_to_glb(outfile, rgbimg, pts3d, msk, focals, cams2world, as_pointcloud=as_pointcloud,
                                         transparent_cams=transparent_cams, cam_size=cam_size, silent=SILENT)
 
-# def save_colmap_scene(scene, save_dir, min_conf_thr=2, clean_depth=False):
-#     if 'save_pointcloud_with_normals' not in globals():
-#         sys.path.append(os.path.join(os.path.dirname(__file__), '../wild-gaussian-splatting/gaussian-splatting'))
-#         sys.path.append(os.path.join(os.path.dirname(__file__), '../wild-gaussian-splatting/src'))
-#         from colmap_dataset_utils import (
-#             inv,
-#             init_filestructure,
-#             save_images_masks,
-#             save_cameras,
-#             save_imagestxt,
-#             save_pointcloud,
-#             save_pointcloud_with_normals
-#         )
-
-#     cam2world = scene.get_im_poses().detach().cpu().numpy()
-#     world2cam = inv(cam2world) #
-#     principal_points = scene.get_principal_points().detach().cpu().numpy()
-#     focals = scene.get_focals().detach().cpu().numpy()[..., None]
-#     imgs = np.array(scene.imgs)
-
-#     pts3d, _, confs = scene.get_dense_pts3d(clean_depth=clean_depth)
-#     pts3d = [i.detach().reshape(imgs[0].shape) for i in pts3d] #
-
-#     masks = to_numpy([c > min_conf_thr for c in to_numpy(confs)])
-
-#     # move
-#     mask_images = True
-
-#     save_path, images_path, masks_path, sparse_path = init_filestructure(save_dir)
-#     save_images_masks(imgs, masks, images_path, masks_path, mask_images)
-#     save_cameras(focals, principal_points, sparse_path, imgs_shape=imgs.shape)
-#     save_imagestxt(world2cam, sparse_path)
-#     save_pointcloud_with_normals(imgs, pts3d, masks, sparse_path)
-#     return save_path
+def save_colmap_scene(scene, save_dir, min_conf_thr=2, clean_depth=False):
+    if 'save_pointcloud_with_normals' not in globals():
+        sys.path.append(os.path.join(os.path.dirname(__file__), '../wild-gaussian-splatting/gaussian-splatting'))
+        sys.path.append(os.path.join(os.path.dirname(__file__), '../wild-gaussian-splatting/src'))
+        from colmap_dataset_utils import (
+            inv,
+            init_filestructure,
+            save_images_masks,
+            save_cameras,
+            save_imagestxt,
+            save_pointcloud,
+            save_pointcloud_with_normals
+        )
+
+    cam2world = scene.get_im_poses().detach().cpu().numpy()
+    world2cam = inv(cam2world) #
+    principal_points = scene.get_principal_points().detach().cpu().numpy()
+    focals = scene.get_focals().detach().cpu().numpy()[..., None]
+    imgs = np.array(scene.imgs)
+
+    pts3d, _, confs = scene.get_dense_pts3d(clean_depth=clean_depth)
+    pts3d = [i.detach().reshape(imgs[0].shape) for i in pts3d] #
+
+    masks = to_numpy([c > min_conf_thr for c in to_numpy(confs)])
+
+    # move
+    mask_images = True
+
+    save_path, images_path, masks_path, sparse_path = init_filestructure(save_dir)
+    save_images_masks(imgs, masks, images_path, masks_path, mask_images)
+    save_cameras(focals, principal_points, sparse_path, imgs_shape=imgs.shape)
+    save_imagestxt(world2cam, sparse_path)
+    save_pointcloud_with_normals(imgs, pts3d, masks, sparse_path)
+    return save_path
 
 @spaces.GPU(duration=10)
 def get_reconstructed_scene(image_size, current_scene_state,
@@ -223,10 +223,7 @@ def get_reconstructed_scene(image_size, current_scene_state,
     os.makedirs(base_colmapdata_dir, exist_ok=True)
     colmap_data_dir = get_next_dir(base_colmapdata_dir)
     # 
-    # save_colmap_scene(scene, colmap_data_dir, min_conf_thr, clean_depth)
-    if 'GaussianRasterizer' not in globals():
-        print("Importing diff_gaussian_rasterization")
-        from diff_gaussian_rasterization import GaussianRasterizer, GaussianRasterizationSettings
+    save_colmap_scene(scene, colmap_data_dir, min_conf_thr, clean_depth)
     
     if current_scene_state is not None and \
        current_scene_state.outfile_name is not None:
@@ -269,12 +266,6 @@ def set_scenegraph_options(inputfiles, win_cyclic, refid, scenegraph_type):
     return win_col, winsize, win_cyclic, refid
 
 
-# def get_reconstructed_scene_wrapper_func(*args, **kwargs):
-#     return get_reconstructed_scene(CACHE_PATH, MODEL, DEVICE, SILENT, *args, **kwargs)
-
-# def update_3D_model_from_scene(*args, **kwargs):
-#     return get_3D_model_from_scene(SILENT, *args, **kwargs)
-
 def mast3r_demo_tab():
     
     if not SILENT:

requirements.txt

@@ -15,8 +15,8 @@ tensorboard
 pyglet<2
 roma
 
-https://huggingface.co/spaces/ostapagon/mast3r-3dgs/resolve/main/wheels/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl?download=true
 https://huggingface.co/spaces/ostapagon/mast3r-3dgs/resolve/main/wheels/simple_knn-0.0.0-cp310-cp310-linux_x86_64.whl?download=true
+https://huggingface.co/spaces/ostapagon/mast3r-3dgs/resolve/main/wheels/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl?download=true
 
 camtools==0.1.4
 einops==0.7.0

wheels/simple_knn-0.0.0-cp310-cp310-linux_x86_64.whl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:59729fbacdab4fff910203ee283a8aca6452a389e11c648640d83e9ae42bb906
-size 2913535
+oid sha256:d5d186b907917fba676b89dbe35e644fa617cf73781b94da0740648c09829611
+size 3089436