Update app.py

app.py

@@ -9,6 +9,17 @@ model = FastDepth(pretrained=True)
 model.eval()
 app = FastAPI()
 
+import os
+if not os.path.exists("fastdepth"):
+    os.system("git clone https://github.com/dwofk/fast-depth.git fastdepth")
+
+from fastdepth import FastDepth  # Import sau khi clone
+
+app = FastAPI()
+
+# 🟢 Load mô hình FastDepth
+model = FastDepth(pretrained=True)
+model.eval()
 
 def analyzepath(image):
     depth_map = model(image).squeeze().cpu().numpy()
@@ -16,12 +27,19 @@ def analyzepath(image):
 @app.post("/analyze_path/")
 async def analyze_path(file: UploadFile = File(...)):
     image_bytes = await file.read()
-    image = Image.open(io.BytesIO(image_bytes)).convert("L")  # Chuyển ảnh sang grayscale
-    mImage = cv2.flip(image, -1)
-    #depth_map = np.array(image)
-    depth_map = analyzepath(mImage)
-    
-    # Phân tích ảnh Depth Map
+    image = Image.open(io.BytesIO(image_bytes)).convert("L")
+    depth_map = np.array(image)
+
+    # 🟢 Lật ảnh (nếu cần)
+    flipped_depth_map = cv2.flip(depth_map, -1)
+    transform = torchvision.transforms.Compose([
+        torchvision.transforms.Resize((224, 224)),
+        torchvision.transforms.ToTensor(),
+    ])
+    img_tensor = transform(image).unsqueeze(0).to(device)
+    with torch.no_grad():
+        depth_map = model(img_tensor).squeeze().cpu().numpy()
+    # 🟢 Phân tích đường đi
     command = detect_path(flipped_depth_map)
 
     return {"command": command}