cpu

networks/base_model.py

@@ -16,7 +16,8 @@ class BaseModel(nn.Module):
             self.device= torch.device('cuda:{}'.format(opt.gpu_ids[0]))
         else:
             print("gpu is not available! ")
-            exit()
+            # exit()
+            self.device = torch.device('cpu')
         # self.device = torch.device('cuda')
 
     def save_networks(self, save_filename):

options/base_options.py

@@ -28,7 +28,7 @@ class BaseOptions():
         
         parser.add_argument('--loadSize', type=int, default=256, help='scale images to this size')
         parser.add_argument('--cropSize', type=int, default=224, help='then crop to this size')
-        parser.add_argument('--gpu_ids', type=str, default='0', help='gpu ids: e.g. 0  0,1,2, 0,2. use -1 for CPU')
+        parser.add_argument('--gpu_ids', type=str, default='-1', help='gpu ids: e.g. 0  0,1,2, 0,2. use -1 for CPU')
 
         parser.add_argument('--checkpoints_dir', type=str, default='./checkpoints', help='models are saved here')
         parser.add_argument('--name', type=str, default='experiment', help='name of the experiment. It decides where to store samples and models')

requirements.txt

@@ -13,4 +13,5 @@ termcolor==2.4.0
 torch==2.1.0
 torchinfo==1.8.0
 torchvision==0.16.0
-tqdm==4.66.1
+tqdm==4.66.1
+PyAV==12.0.5

run.py

@@ -28,8 +28,6 @@ def detect_video(video_path):
     print(f"working...")
 
     model = Validator(val_opt)
-    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-    model.to(device), model.model.to(device)
     model.load_state_dict(val_opt.ckpt)
     print("ckpt loaded!")