Fix float zeros format (#5491)

* Fix float zeros format

* 255 to integer

train.py

@@ -246,9 +246,9 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
 
     # Model parameters
     nl = de_parallel(model).model[-1].nl  # number of detection layers (to scale hyps)
-    hyp['box'] *= 3. / nl  # scale to layers
-    hyp['cls'] *= nc / 80. * 3. / nl  # scale to classes and layers
-    hyp['obj'] *= (imgsz / 640) ** 2 * 3. / nl  # scale to image size and layers
+    hyp['box'] *= 3 / nl  # scale to layers
+    hyp['cls'] *= nc / 80 * 3 / nl  # scale to classes and layers
+    hyp['obj'] *= (imgsz / 640) ** 2 * 3 / nl  # scale to image size and layers
     hyp['label_smoothing'] = opt.label_smoothing
     model.nc = nc  # attach number of classes to model
     model.hyp = hyp  # attach hyperparameters to model
@@ -293,7 +293,7 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
         optimizer.zero_grad()
         for i, (imgs, targets, paths, _) in pbar:  # batch -------------------------------------------------------------
             ni = i + nb * epoch  # number integrated batches (since train start)
-            imgs = imgs.to(device, non_blocking=True).float() / 255.0  # uint8 to float32, 0-255 to 0.0-1.0
+            imgs = imgs.to(device, non_blocking=True).float() / 255  # uint8 to float32, 0-255 to 0.0-1.0
 
             # Warmup
             if ni <= nw: