test

app.py

@@ -2,28 +2,36 @@ from transformers import pipeline
 from PIL import Image
 import gradio as gr
 
-# Load the Hugging Face depth estimation pipeline
-pipe = pipeline(task="depth-estimation", model="LiheYoung/depth-anything-small-hf")
-
-def estimate_depth(image):
-    # Perform depth estimation on the input image
-    depth = pipe(image)["depth"]
-    return depth
+# Load the Hugging Face depth estimation pipelines
+pipe_base = pipeline(task="depth-estimation", model="LiheYoung/depth-anything-base-hf")
+pipe_small = pipeline(task="depth-estimation", model="LiheYoung/depth-anything-small-hf")
+pipe_intel = pipeline(task="depth-estimation", model="Intel/dpt-swinv2-tiny-256")
+
+def estimate_depths(image):
+    # Perform depth estimation with each pipeline
+    depth_base = pipe_base(image)["depth"]
+    depth_small = pipe_small(image)["depth"]
+    depth_intel = pipe_intel(image)["depth"]
+    
+    return depth_base, depth_small, depth_intel
 
 # Create a Gradio interface
 iface = gr.Interface(
-    fn=estimate_depth, 
+    fn=estimate_depths, 
     inputs=gr.Image(type="pil"), 
-    outputs=gr.Image(type="pil"),
-    title="Depth Estimation",
-    description="Upload an image to get its depth estimation map."
+    outputs=[
+        gr.outputs.Image(type="pil", label="LiheYoung/depth-anything-base-hf"),
+        gr.outputs.Image(type="pil", label="LiheYoung/depth-anything-small-hf"),
+        gr.outputs.Image(type="pil", label="Intel/dpt-swinv2-tiny-256")
+    ],
+    title="Multi-Model Depth Estimation",
+    description="Upload an image to get depth estimation maps from multiple models."
 )
 
 # Launch the Gradio app
 iface.launch()
 
 
-
 """ 
 from transformers import pipeline
 from PIL import Image