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gradio_app.py

@@ -1,15 +1,6 @@
 import gradio as gr
 import numpy as np
-
-try:
-    import spaces  # type: ignore
-
-    IN_SPACES = True
-except ImportError:
-    print("Not running on Zero")
-    IN_SPACES = False
 import torch
-
 from monopriors.relative_depth_models import (
     RelativeDepthPrediction,
     get_relative_predictor,
@@ -27,6 +18,15 @@ from typing import Literal, get_args
 import gc
 
 from jaxtyping import UInt8
+import mmcv
+
+try:
+    import spaces  # type: ignore
+
+    IN_SPACES = True
+except ImportError:
+    print("Not running on Zero")
+    IN_SPACES = False
 
 title = "# Depth Comparison"
 description1 = """Demo to help compare different depth models. Including both Scale | Shift Invariant and Metric Depth types."""
@@ -38,7 +38,7 @@ DEVICE: Literal["cuda"] | Literal["cpu"] = (
 MODELS_TO_SKIP: list[str] = []
 if gr.NO_RELOAD:
     MODEL_1 = get_relative_predictor("DepthAnythingV2Predictor")(device=DEVICE)
-    MODEL_2 = get_relative_predictor("Metric3DRelativePredictor")(device=DEVICE)
+    MODEL_2 = get_relative_predictor("UniDepthRelativePredictor")(device=DEVICE)
 
 
 def predict_depth(
@@ -95,6 +95,14 @@ def on_submit(rgb: UInt8[np.ndarray, "h w 3"]):
     models_list = [MODEL_1, MODEL_2]
     blueprint = create_depth_comparison_blueprint(models_list)
     rr.send_blueprint(blueprint)
+
+    # resize the image to have a max dim of 1024
+    max_dim = 1024
+    current_dim = max(rgb.shape[0], rgb.shape[1])
+    if current_dim > max_dim:
+        scale_factor = max_dim / current_dim
+        rgb = mmcv.imrescale(img=rgb, scale=scale_factor)
+
     try:
         for model in models_list:
             # get the name of the model