Update app.py

app.py

@@ -11,16 +11,16 @@ from net.dornet import Net
 from net.dornet_ddp import Net_ddp
 import subprocess
 
-def install_mmcv():
-    try:
-        subprocess.run([
-            "pip", "install", "mmcv-full==1.7.2",
-            "-f", "https://download.openmmlab.com/mmcv/dist/cu121/torch2.1.0/"
-        ], check=True)
-    except subprocess.CalledProcessError as e:
-        print("Failed to install mmcv-full:", e)
-
-install_mmcv()
+# def install_mmcv():
+#     try:
+#         subprocess.run([
+#             "pip", "install", "mmcv-full==1.7.2",
+#             "-f", "https://download.openmmlab.com/mmcv/dist/cu121/torch2.1.0/"
+#         ], check=True)
+#     except subprocess.CalledProcessError as e:
+#         print("Failed to install mmcv-full:", e)
+
+# install_mmcv()
 print("=" * 50)
 print(f"CUDA available: {torch.cuda.is_available()}")
 print(f"torch version: {torch.__version__}")
@@ -30,6 +30,7 @@ print("=" * 50)
 
 # init
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+device = "cpu"
 net = Net(tiny_model=False).to(device)
 model_ckpt_map = {
     "RGB-D-D": "./checkpoints/RGBDD.pth",
@@ -37,7 +38,7 @@ model_ckpt_map = {
 }
 
 # load model
-@spaces.GPU
+# @spaces.GPU
 def load_model(model_type: str):
     global net
     ckpt_path = model_ckpt_map[model_type]
@@ -56,7 +57,7 @@ load_model("RGB-D-D")
 
 
 # data process
-@spaces.GPU
+# @spaces.GPU
 def preprocess_inputs(rgb_image: Image.Image, lr_depth: Image.Image):
     image = np.array(rgb_image.convert("RGB")).astype(np.float32)
     h, w, _ = image.shape
@@ -78,7 +79,7 @@ def preprocess_inputs(rgb_image: Image.Image, lr_depth: Image.Image):
 
 
 # model inference
-@spaces.GPU
+# @spaces.GPU
 @torch.no_grad()
 def infer(rgb_image: Image.Image, lr_depth: Image.Image, model_type: str):
     load_model(model_type)  # reset weight