test

app.py

@@ -1,7 +1,6 @@
 from transformers import pipeline
 from PIL import Image
 import gradio as gr
-import numpy as np
 
 # Load the Hugging Face depth estimation pipelines
 pipe_base = pipeline(task="depth-estimation", model="LiheYoung/depth-anything-base-hf")
@@ -16,19 +15,8 @@ def estimate_depths(image):
     depth_intel = pipe_intel(image)["depth"]
     depth_beit = pipe_beit(image)["depth"]
     
-    # Normalize depths for visualization
-    depth_base = normalize_depth(depth_base)
-    depth_small = normalize_depth(depth_small)
-    depth_intel = normalize_depth(depth_intel)
-    depth_beit = normalize_depth(depth_beit)
-    
     return depth_base, depth_small, depth_intel, depth_beit
 
-def normalize_depth(depth_map):
-    # Normalize depth map values to range [0, 255] for visualization
-    normalized_depth = ((depth_map - depth_map.min()) / (depth_map.max() - depth_map.min())) * 255
-    return normalized_depth.astype(np.uint8)
-
 # Create a Gradio interface using Blocks
 with gr.Blocks() as iface:
     gr.Markdown("# Multi-Model Depth Estimation\nUpload an image to get depth estimation maps from multiple models.")
@@ -38,11 +26,11 @@ with gr.Blocks() as iface:
     
     with gr.Row():
         with gr.Column():
-            output_base = gr.Image(type="numpy", label="LiheYoung/depth-anything-base-hf", interactive=False)
-            output_small = gr.Image(type="numpy", label="LiheYoung/depth-anything-small-hf", interactive=False)
+            output_base = gr.Image(type="pil", label="LiheYoung/depth-anything-base-hf", interactive=False)
+            output_small = gr.Image(type="pil", label="LiheYoung/depth-anything-small-hf", interactive=False)
         with gr.Column():
-            output_intel = gr.Image(type="numpy", label="Intel/dpt-swinv2-tiny-256", interactive=False)
-            output_beit = gr.Image(type="numpy", label="Intel/dpt-beit-base-384", interactive=False)
+            output_intel = gr.Image(type="pil", label="Intel/dpt-swinv2-tiny-256", interactive=False)
+            output_beit = gr.Image(type="pil", label="Intel/dpt-beit-base-384", interactive=False)
 
     input_image.change(fn=estimate_depths, inputs=input_image, outputs=[output_base, output_small, output_intel, output_beit])