changed floating point 16

owl_core.py

@@ -1,4 +1,5 @@
 import torch
+import torch.quantization
 from tqdm import tqdm
 import cv2
 import os
@@ -47,8 +48,6 @@ def owl_full_video(
         threshold: float,
         fps_processed: int = 1,
         scaling_factor: float = 0.5,
-        processor = Owlv2Processor.from_pretrained("google/owlv2-base-patch16-ensemble"),
-        model = Owlv2ForObjectDetection.from_pretrained("google/owlv2-base-patch16-ensemble").to('cuda'),
         device: str = 'cuda',
         batch_size: int = 6,
         ):
@@ -56,10 +55,14 @@ def owl_full_video(
         Saves results per frame to a df.
     """
 
+    processor = Owlv2Processor.from_pretrained("google/owlv2-base-patch16-ensemble")
+    model = Owlv2ForObjectDetection.from_pretrained("google/owlv2-base-patch16-ensemble").half().to('cuda')
+
+
     # create new dirs and paths for results
     filename = os.path.splitext(os.path.basename(vid_path))[0]
-    results_dir = f'../temp/{filename}_{datetime.now().strftime("%H%M%S")}'
-    # results_dir = f'temp/{filename}_{datetime.now().strftime("%H%M%S")}'
+    # results_dir = f'../temp/{filename}_{datetime.now().strftime("%H%M%S")}' # run this on server
+    results_dir = f'temp/{filename}_{datetime.now().strftime("%H%M%S")}' # run this on local
     frames_dir = os.path.join(results_dir, "frames")
 
     # if the frames directory does not exist, create it and get the frames from the video