DDP, Comet, URLError fixes, improved error handling (#658)

Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Tungway1990 <68179274+Tungway1990@users.noreply.github.com>

ultralytics/yolo/v8/classify/predict.py

@@ -69,7 +69,7 @@ def predict(cfg=DEFAULT_CFG, use_python=False):
     source = cfg.source if cfg.source is not None else ROOT / "assets" if (ROOT / "assets").exists() \
         else "https://ultralytics.com/images/bus.jpg"
 
-    args = dict(model=model, source=source, verbose=True)
+    args = dict(model=model, source=source)
     if use_python:
         from ultralytics import YOLO
         YOLO(model)(**args)

ultralytics/yolo/v8/classify/train.py

@@ -141,7 +141,7 @@ def train(cfg=DEFAULT_CFG, use_python=False):
     data = cfg.data or "mnist160"  # or yolo.ClassificationDataset("mnist")
     device = cfg.device if cfg.device is not None else ''
 
-    args = dict(model=model, data=data, device=device, verbose=True)
+    args = dict(model=model, data=data, device=device)
     if use_python:
         from ultralytics import YOLO
         YOLO(model).train(**args)

ultralytics/yolo/v8/classify/val.py

@@ -50,7 +50,7 @@ def val(cfg=DEFAULT_CFG, use_python=False):
     model = cfg.model or "yolov8n-cls.pt"  # or "resnet18"
     data = cfg.data or "mnist160"
 
-    args = dict(model=model, data=data, verbose=True)
+    args = dict(model=model, data=data)
     if use_python:
         from ultralytics import YOLO
         YOLO(model).val(**args)

ultralytics/yolo/v8/detect/predict.py

@@ -87,7 +87,7 @@ def predict(cfg=DEFAULT_CFG, use_python=False):
     source = cfg.source if cfg.source is not None else ROOT / "assets" if (ROOT / "assets").exists() \
         else "https://ultralytics.com/images/bus.jpg"
 
-    args = dict(model=model, source=source, verbose=True)
+    args = dict(model=model, source=source)
     if use_python:
         from ultralytics import YOLO
         YOLO(model)(**args)

ultralytics/yolo/v8/detect/train.py

@@ -199,7 +199,7 @@ def train(cfg=DEFAULT_CFG, use_python=False):
     data = cfg.data or "coco128.yaml"  # or yolo.ClassificationDataset("mnist")
     device = cfg.device if cfg.device is not None else ''
 
-    args = dict(model=model, data=data, device=device, verbose=True)
+    args = dict(model=model, data=data, device=device)
     if use_python:
         from ultralytics import YOLO
         YOLO(model).train(**args)

ultralytics/yolo/v8/detect/val.py

@@ -129,7 +129,7 @@ class DetectionValidator(BaseValidator):
                 f'WARNING ⚠️ no labels found in {self.args.task} set, can not compute metrics without labels')
 
         # Print results per class
-        if (self.args.verbose or not self.training) and self.nc > 1 and len(self.stats):
+        if self.args.verbose and not self.training and self.nc > 1 and len(self.stats):
             for i, c in enumerate(self.metrics.ap_class_index):
                 self.logger.info(pf % (self.names[c], self.seen, self.nt_per_class[c], *self.metrics.class_result(i)))
 
@@ -237,7 +237,7 @@ def val(cfg=DEFAULT_CFG, use_python=False):
     model = cfg.model or "yolov8n.pt"
     data = cfg.data or "coco128.yaml"
 
-    args = dict(model=model, data=data, verbose=True)
+    args = dict(model=model, data=data)
     if use_python:
         from ultralytics import YOLO
         YOLO(model).val(**args)

ultralytics/yolo/v8/segment/predict.py

@@ -105,7 +105,7 @@ def predict(cfg=DEFAULT_CFG, use_python=False):
     source = cfg.source if cfg.source is not None else ROOT / "assets" if (ROOT / "assets").exists() \
         else "https://ultralytics.com/images/bus.jpg"
 
-    args = dict(model=model, source=source, verbose=True)
+    args = dict(model=model, source=source)
     if use_python:
         from ultralytics import YOLO
         YOLO(model)(**args)

ultralytics/yolo/v8/segment/train.py

@@ -145,7 +145,7 @@ def train(cfg=DEFAULT_CFG, use_python=False):
     data = cfg.data or "coco128-seg.yaml"  # or yolo.ClassificationDataset("mnist")
     device = cfg.device if cfg.device is not None else ''
 
-    args = dict(model=model, data=data, device=device, verbose=True)
+    args = dict(model=model, data=data, device=device)
     if use_python:
         from ultralytics import YOLO
         YOLO(model).train(**args)

ultralytics/yolo/v8/segment/val.py

@@ -247,7 +247,7 @@ def val(cfg=DEFAULT_CFG, use_python=False):
     model = cfg.model or "yolov8n-seg.pt"
     data = cfg.data or "coco128-seg.yaml"
 
-    args = dict(model=model, data=data, verbose=True)
+    args = dict(model=model, data=data)
     if use_python:
         from ultralytics import YOLO
         YOLO(model).val(**args)