val.py refactor (#4053)

* val.py refactor

* cleanup

* cleanup

* cleanup

* cleanup

* save after eval

* opt.imgsz bug fix

* wandb refactor

* dataloader to train_loader

* capitalize global variables

* runs/hub/exp to runs/detect/exp

* refactor wandb logging

* Refactor wandb operations (#4061)

Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>

detect.py

@@ -21,7 +21,7 @@ from utils.datasets import LoadStreams, LoadImages
 from utils.general import check_img_size, check_requirements, check_imshow, colorstr, non_max_suppression, \
     apply_classifier, scale_coords, xyxy2xywh, strip_optimizer, set_logging, increment_path, save_one_box
 from utils.plots import colors, plot_one_box
-from utils.torch_utils import select_device, load_classifier, time_synchronized
+from utils.torch_utils import select_device, load_classifier, time_sync
 
 
 @torch.no_grad()
@@ -100,14 +100,14 @@ def run(weights='yolov5s.pt',  # model.pt path(s)
             img = img.unsqueeze(0)
 
         # Inference
-        t1 = time_synchronized()
+        t1 = time_sync()
         pred = model(img,
                      augment=augment,
                      visualize=increment_path(save_dir / Path(path).stem, mkdir=True) if visualize else False)[0]
 
         # Apply NMS
         pred = non_max_suppression(pred, conf_thres, iou_thres, classes, agnostic_nms, max_det=max_det)
-        t2 = time_synchronized()
+        t2 = time_sync()
 
         # Apply Classifier
         if classify: