Update app.py

app.py

@@ -8,8 +8,6 @@ import uuid
 import spaces
 
 # --- FIX: make gradio compatible by downgrading huggingface_hub -----------
-# original gradio (4.x) expects huggingface_hub to still have HfFolder
-# so we just ensure we're on a <1.0.0 version
 subprocess.run(
     shlex.split("pip install 'huggingface_hub<1.0.0'"),
     check=False,
@@ -17,6 +15,7 @@ subprocess.run(
 # --------------------------------------------------------------------------
 
 import gradio as gr  # import AFTER the pip install above
+from huggingface_hub import HfApi
 
 # install custom wheels for gaussian splatting
 subprocess.run(shlex.split("pip install wheel/diff_gaussian_rasterization-0.0.0-cp310-cp310-linux_x86_64.whl"))
@@ -33,12 +32,13 @@ from dust3r.image_pairs import make_pairs
 from dust3r.cloud_opt import global_aligner, GlobalAlignerMode
 from utils.dust3r_utils import compute_global_alignment, load_images, storePly, save_colmap_cameras, save_colmap_images
 
-from argparse import ArgumentParser, Namespace
+from argparse import ArgumentParser
 from arguments import ModelParams, PipelineParams, OptimizationParams
 from train_joint import training
 from render_by_interp import render_sets
 
 GRADIO_CACHE_FOLDER = './gradio_cache_folder'
+SPACE_REPO_ID = "longh37/InstantSplat"   # <== your Space id
 #############################################################################################################################################
 
 
@@ -106,7 +106,7 @@ def process(inputfiles, input_path=None):
 
     pairs = make_pairs(images, scene_graph='complete', prefilter=None, symmetrize=True)
     output = inference(pairs, model, opt.device, batch_size=opt.batch_size)
-    output_colmap_path = img_folder_path.replace("images", "sparse/0")
+    output_colmap_path=img_folder_path.replace("images", "sparse/0")
     os.makedirs(output_colmap_path, exist_ok=True)
 
     scene = global_aligner(output, device=opt.device, mode=GlobalAlignerMode.PointCloudOptimizer)
@@ -151,7 +151,7 @@ def process(inputfiles, input_path=None):
     parser.add_argument("--save_iterations", nargs="+", type=int, default=[])
     parser.add_argument("--checkpoint_iterations", nargs="+", type=int, default=[])
     parser.add_argument("--start_checkpoint", type=str, default = None)
-    parser.add_argument("--scene", type=str, default="demo")
+    parser.add_argument("--scene", type=int, default="demo")
     parser.add_argument("--n_views", type=int, default=3)
     parser.add_argument("--get_video", action="store_true")
     parser.add_argument("--optim_pose", type=bool, default=True)
@@ -188,7 +188,7 @@ def process(inputfiles, input_path=None):
     output_ply_path = opt.img_base_path + f'/output/point_cloud/iteration_{args.iteration}/point_cloud.ply'
     output_video_path = opt.img_base_path + f'/output/demo_{opt.n_views}_view.mp4'
 
-    # sanity checks so Gradio shows a clear error if something went wrong
+    # sanity checks
     if not os.path.exists(output_ply_path):
         print("PLY not found at:", output_ply_path)
         raise gr.Error(f"PLY file not found at {output_ply_path}")
@@ -197,8 +197,28 @@ def process(inputfiles, input_path=None):
         print("Video not found at:", output_video_path)
         raise gr.Error(f"Video file not found at {output_video_path}")
 
-    # return video, ply-for-download, ply-for-3d-viewer
-    return  output_video_path, output_ply_path, output_ply_path
+    # ------ (4) upload .ply to this Space repo & build URL ------
+    ply_url = None
+    rel_remote_path = f"outputs/{tmp_user_folder}_point_cloud.ply"
+    try:
+        api = HfApi()
+        api.upload_file(
+            repo_id=SPACE_REPO_ID,
+            repo_type="space",
+            path_or_fileobj=output_ply_path,
+            path_in_repo=rel_remote_path,
+        )
+        ply_url = f"https://huggingface.co/spaces/{SPACE_REPO_ID}/resolve/main/{rel_remote_path}"
+        print("Uploaded PLY to:", ply_url)
+    except Exception as e:
+        print("Failed to upload PLY to hub:", e)
+        ply_url = f"LOCAL:{output_ply_path}"
+
+    # return:
+    #  1) video path (for gr.Video)
+    #  2) ply URL (for API + textbox)
+    #  3) local ply path (for gr.Model3D viewer)
+    return output_video_path, ply_url, output_ply_path
     ##################################################################################################################################################
 
 
@@ -228,12 +248,10 @@ _DESCRIPTION = '''
 '''
 
 
-# block = gr.Blocks(title=_TITLE).queue()
 block = gr.Blocks().queue()
 with block:
     with gr.Row():
         with gr.Column(scale=1):
-            # gr.Markdown('# ' + _TITLE)
             gr.Markdown(_DESCRIPTION)
     
     with gr.Row(variant='panel'):
@@ -258,9 +276,9 @@ with block:
                         </div>
                         """
                     )    
-                output_file = gr.File(
-                    label="Download .ply",
-                    file_types=[".ply"],
+                output_file = gr.Textbox(
+                    label="PLY download URL",
+                    interactive=False,
                 )
             with gr.Column(scale=1):
                 output_video = gr.Video(label="video")
@@ -270,8 +288,6 @@ with block:
     gr.Examples(
         examples=[
             "sora-santorini-3-views",
-            # "TT-family-3-views",
-            # "dl3dv-ba55-3-views",
         ],
         inputs=[input_path],
         outputs=[output_video, output_file, output_model],
@@ -279,4 +295,5 @@ with block:
         cache_examples=True,
         label='Sparse-view Examples'
     )
+
 block.launch(server_name="0.0.0.0", share=False)