spaces

README.md

@@ -6,7 +6,7 @@ colorTo: gray
 sdk: gradio
 sdk_version: 4.44.1
 app_file: app.py
-pinned: false
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+

app.py

@@ -5,23 +5,29 @@ import subprocess
 
 import torch
 import cv2
+import os
 from pathlib import Path
 import gradio as gr
 from gradio_rerun import Rerun
+import spaces
 
 # Run the script to get pretrained models
-subprocess.run(["bash", "get_pretrained_models.sh"])
+if not os.path.exists("checkpoints/depth_pro.pt"):
+    print("downloading pretrained model")
+    subprocess.run(["bash", "get_pretrained_models.sh"])
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
 # Load model and preprocessing transform
+print("loading model...")
 model, transform = depth_pro.create_model_and_transforms()
 model = model.to(device)
 model.eval()
 
 
 @rr.thread_local_stream("rerun_example_ml_depth_pro")
-def run_ml_depth_pro(model, transform, frames):
+@spaces.GPU(duration=20)
+def run_ml_depth_pro(frame):
     stream = rr.binary_stream()
 
     assert model is not None, "Model is None"
@@ -31,41 +37,43 @@ def run_ml_depth_pro(model, transform, frames):
     blueprint = rrb.Blueprint(
         rrb.Spatial3DView(origin="/"),
         rrb.Horizontal(
-            rrb.Spatial2DView(origin="/world/camera/depth", title="Depth"),
-            rrb.Spatial2DView(origin="/world/camera/image", title="Image"),
+            rrb.Spatial2DView(
+                origin="/world/camera/depth",
+            ),
+            rrb.Spatial2DView(origin="/world/camera/image"),
         ),
         collapse_panels=True,
     )
 
     rr.send_blueprint(blueprint)
 
-    for i, frame in enumerate(frames):
-        rr.set_time_sequence("frame", i)
-        rr.log("world/camera/image", rr.Image(frame))
-
-        image = transform(frame)
-        prediction = model.infer(image)
-        depth = prediction["depth"].squeeze().detach().cpu().numpy()
-
-        rr.log(
-            "world/camera",
-            rr.Pinhole(
-                width=frame.shape[1],
-                height=frame.shape[0],
-                focal_length=prediction["focallength_px"].item(),
-                principal_point=(frame.shape[1] / 2, frame.shape[0] / 2),
-                image_plane_distance=depth.max(),
-            ),
-        )
+    # for i, frame in enumerate(frames):
+    rr.set_time_sequence("frame", 0)
+    rr.log("world/camera/image", rr.Image(frame))
+
+    image = transform(frame)
+    prediction = model.infer(image)
+    depth = prediction["depth"].squeeze().detach().cpu().numpy()
+
+    rr.log(
+        "world/camera",
+        rr.Pinhole(
+            width=frame.shape[1],
+            height=frame.shape[0],
+            focal_length=prediction["focallength_px"].item(),
+            principal_point=(frame.shape[1] / 2, frame.shape[0] / 2),
+            image_plane_distance=depth.max(),
+        ),
+    )
 
-        rr.log(
-            "world/camera/depth",
-            # need 0.19 stable for this
-            # rr.DepthImage(depth, meter=1, depth_range=(depth.min(), depth.max())),
-            rr.DepthImage(depth, meter=1),
-        )
+    rr.log(
+        "world/camera/depth",
+        # need 0.19 stable for this
+        # rr.DepthImage(depth, meter=1, depth_range=(depth.min(), depth.max())),
+        rr.DepthImage(depth, meter=1),
+    )
 
-        yield stream.read()
+    yield stream.read()
 
 
 video_path = Path("hd-cat.mp4")
@@ -97,9 +105,7 @@ with gr.Blocks() as demo:
                     "selection": "hidden",
                 },
             )
-        stream_ml_depth_pro.click(
-            run_ml_depth_pro, inputs=[model, transform, frames], outputs=[viewer]
-        )
+        stream_ml_depth_pro.click(run_ml_depth_pro, inputs=[img], outputs=[viewer])
 
 
 if __name__ == "__main__":

pyproject.toml

@@ -11,6 +11,7 @@ dependencies = [
     "gradio-rerun>=0.0.6",
     "opencv-python>=4.10.0.84",
     "rerun-sdk==0.18.2",
+    "spaces>=0.30.3",
 ]
 
 [tool.uv]

requirements.txt

@@ -57,7 +57,7 @@ pillow==10.4.0
 pillow-heif==0.18.0
 platformdirs==4.3.6
 prompt-toolkit==3.0.48
-psutil==6.0.0
+psutil==5.9.8
 ptyprocess==0.7.0
 pure-eval==0.2.3
 pyarrow==17.0.0
@@ -80,6 +80,7 @@ semantic-version==2.10.0
 shellingham==1.5.4
 six==1.16.0
 sniffio==1.3.1
+spaces==0.30.3
 stack-data==0.6.3
 starlette==0.38.6
 sympy==1.13.3

uv.lock

@@ -1341,19 +1341,18 @@ wheels = [
 
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+version = "5.9.8"
 source = { registry = "https://pypi.org/simple" }
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 ]
 
 [[package]]
@@ -1715,6 +1714,7 @@ dependencies = [
     { name = "gradio-rerun" },
     { name = "opencv-python" },
     { name = "rerun-sdk" },
+    { name = "spaces" },
 ]
 
 [package.dev-dependencies]
@@ -1734,6 +1734,7 @@ requires-dist = [
     { name = "gradio-rerun", specifier = ">=0.0.6" },
     { name = "opencv-python", specifier = ">=4.10.0.84" },
     { name = "rerun-sdk", specifier = "==0.18.2" },
+    { name = "spaces", specifier = ">=0.30.3" },
 ]
 
 [package.metadata.requires-dev]
@@ -1900,6 +1901,24 @@ wheels = [
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 ]
 
+[[package]]
+name = "spaces"
+version = "0.30.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "gradio" },
+    { name = "httpx" },
+    { name = "packaging" },
+    { name = "psutil" },
+    { name = "pydantic" },
+    { name = "requests" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/cd/17/24e3ba4c812eeafb6647e1a3742d6065a2463d3bda25955f08000965cf50/spaces-0.30.3.tar.gz", hash = "sha256:f25cc0db4831e97df0f8dc5edeaddc11c35d75a51493fdb6eb5a2e8c98d4e923", size = 21139 }
+wheels = [
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+]
+
 [[package]]
 name = "stack-data"
 version = "0.6.3"