Update app.py

app.py

@@ -1,5 +1,4 @@
 from fastapi import FastAPI, UploadFile, File
-import uvicorn
 import cv2
 import numpy as np
 import torch
@@ -9,7 +8,6 @@ import io
 
 app = FastAPI()
 
-# Load AI model MiDaS
 midas = torch.hub.load("intel-isl/MiDaS", "MiDaS_small")
 midas.eval()
 transform = T.Compose([T.Resize((256, 256)), T.ToTensor(), T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])])
@@ -18,18 +16,17 @@ transform = T.Compose([T.Resize((256, 256)), T.ToTensor(), T.Normalize(mean=[0.4
 async def upload_image(file: UploadFile = File(...)):
     image_bytes = await file.read()
     image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
-    
-    # Convert to tensor & run AI model
+
     img_tensor = transform(image).unsqueeze(0)
     with torch.no_grad():
         depth_map = midas(img_tensor).squeeze().cpu().numpy()
 
-    # Normalize depth map
     depth_map = cv2.normalize(depth_map, None, 0, 255, cv2.NORM_MINMAX).astype(np.uint8)
-    depth_img = cv2.applyColorMap(depth_map, cv2.COLORMAP_JET)
-
+    depth_img = cv2.resize(depth_map, (128, 64))
+    
     _, buffer = cv2.imencode(".jpg", depth_img)
     return {"depth_map": buffer.tobytes()}
 
 if __name__ == "__main__":
+    import uvicorn
     uvicorn.run(app, host="0.0.0.0", port=7860)