Add grayscale depth map output

app.py

@@ -1,6 +1,8 @@
 import gradio as gr
 import spaces
 import torch
+import numpy as np
+from PIL import Image
 from depth_anything_3.api import DepthAnything3
 
 # Load model
@@ -11,34 +13,33 @@ model = model.to(device=device)
 @spaces.GPU
 def analyze_depth(image):
     """
-    分析圖片深度並回傳 intrinsics
+    分析圖片深度並輸出灰階深度圖
     """
     if image is None:
-        return "請上傳圖片"
+        return None
 
     # Run inference
     prediction = model.inference([image])
 
-    # 取得 intrinsics
-    intrinsics = prediction.intrinsics[0]  # [3, 3] 矩陣
+    # 取得深度圖 [H, W]
+    depth = prediction.depth[0]
+    depth_np = depth.cpu().numpy() if torch.is_tensor(depth) else depth
 
-    # 轉換為 numpy 並格式化輸出
-    intrinsics_np = intrinsics.cpu().numpy() if torch.is_tensor(intrinsics) else intrinsics
+    # 正規化：depthMin → 255 (近/亮), depthMax → 0 (遠/暗)
+    depth_min = depth_np.min()
+    depth_max = depth_np.max()
+    depth_normalized = (depth_max - depth_np) / (depth_max - depth_min)
+    depth_gray = (depth_normalized * 255).astype(np.uint8)
 
-    result = "Camera Intrinsics (3x3):\n"
-    result += f"[{intrinsics_np[0, 0]:.4f}, {intrinsics_np[0, 1]:.4f}, {intrinsics_np[0, 2]:.4f}]\n"
-    result += f"[{intrinsics_np[1, 0]:.4f}, {intrinsics_np[1, 1]:.4f}, {intrinsics_np[1, 2]:.4f}]\n"
-    result += f"[{intrinsics_np[2, 0]:.4f}, {intrinsics_np[2, 1]:.4f}, {intrinsics_np[2, 2]:.4f}]"
-
-    return result
+    return Image.fromarray(depth_gray, mode='L')
 
 # 建立 Gradio 介面
 demo = gr.Interface(
     fn=analyze_depth,
     inputs=gr.Image(type="pil", label="上傳圖片"),
-    outputs=gr.Textbox(label="Intrinsics 結果", lines=10),
-    title="Depth Anything V3 - Intrinsics 測試",
-    description="上傳一張圖片，系統將回傳相機內參 (intrinsics)"
+    outputs=gr.Image(type="pil", label="灰階深度圖"),
+    title="Depth Anything V3 - 深度分析",
+    description="上傳圖片，輸出灰階深度圖（白色=近，黑色=遠）"
 )
 
 demo.launch()