Add camera parameters and depth range to output

Extend the Gradio interface to output depth min/max values, camera extrinsics (OpenCV w2c/COLMAP format), and camera intrinsics alongside the existing 8-bit and 16-bit depth maps. This provides complete depth and camera information for downstream 3D reconstruction tasks.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

app.py

@@ -16,10 +16,10 @@ model = model.to(device=device)
 @spaces.GPU
 def analyze_depth(image):
     """
-    分析圖片深度並輸出灰階深度圖
+    分析圖片深度並輸出灰階深度圖及相機參數
     """
     if image is None:
-        return None
+        return None, None, None, None, None
 
     # Run inference
     prediction = model.inference([image], process_res=1600)
@@ -29,8 +29,8 @@ def analyze_depth(image):
     depth_np = depth.cpu().numpy() if torch.is_tensor(depth) else depth
 
     # 正規化：depthMin → 最大值 (近/亮), depthMax → 0 (遠/暗)
-    depth_min = depth_np.min()
-    depth_max = depth_np.max()
+    depth_min = float(depth_np.min())
+    depth_max = float(depth_np.max())
     depth_normalized = (depth_max - depth_np) / (depth_max - depth_min)
 
     # 8bit 預覽圖 (0-255)
@@ -48,7 +48,32 @@ def analyze_depth(image):
     # 使用 imageio 儲存 16bit PNG
     imageio.imwrite(temp_path, depth_16bit)
 
-    return depth_8bit_img, temp_path
+    # 取得相機參數
+    extrinsics = prediction.extrinsics[0]  # [3, 4]
+    intrinsics = prediction.intrinsics[0]  # [3, 3]
+
+    # 轉換為 numpy array 並格式化為可讀的 JSON
+    extrinsics_np = extrinsics.cpu().numpy() if torch.is_tensor(extrinsics) else extrinsics
+    intrinsics_np = intrinsics.cpu().numpy() if torch.is_tensor(intrinsics) else intrinsics
+
+    # 準備輸出資料
+    depth_info = {
+        "depth_min": depth_min,
+        "depth_max": depth_max
+    }
+
+    extrinsics_info = {
+        "format": "OpenCV w2c / COLMAP",
+        "shape": "[3, 4]",
+        "matrix": extrinsics_np.tolist()
+    }
+
+    intrinsics_info = {
+        "shape": "[3, 3]",
+        "matrix": intrinsics_np.tolist()
+    }
+
+    return depth_8bit_img, temp_path, depth_info, extrinsics_info, intrinsics_info
 
 # 建立 Gradio 介面
 demo = gr.Interface(
@@ -56,10 +81,13 @@ demo = gr.Interface(
     inputs=gr.Image(type="pil", label="上傳圖片"),
     outputs=[
         gr.Image(type="pil", label="8bit 預覽圖"),
-        gr.File(label="16bit 深度圖 (PNG)")
+        gr.File(label="16bit 深度圖 (PNG)"),
+        gr.JSON(label="深度範圍 (Depth Min/Max)"),
+        gr.JSON(label="相機外參 (Extrinsics)"),
+        gr.JSON(label="相機內參 (Intrinsics)")
     ],
     title="Depth Anything V3 - 深度分析",
-    description="上傳圖片，輸出深度圖（白色=近，黑色=遠）。16bit PNG 保留更精準的深度值 (0-65535)。"
+    description="上傳圖片，輸出深度圖（白色=近，黑色=遠）及相機參數。16bit PNG 保留更精準的深度值 (0-65535)。"
 )
 
 demo.launch()