ultralytics 8.0.18 new python callbacks and minor fixes (#580)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Jeroen Rombouts <36196499+jarombouts@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

ultralytics/yolo/v8/classify/val.py

@@ -10,6 +10,7 @@ class ClassificationValidator(BaseValidator):
 
     def __init__(self, dataloader=None, save_dir=None, pbar=None, logger=None, args=None):
         super().__init__(dataloader, save_dir, pbar, logger, args)
+        self.args.task = 'classify'
         self.metrics = ClassifyMetrics()
 
     def get_desc(self):

ultralytics/yolo/v8/detect/val.py

@@ -20,6 +20,7 @@ class DetectionValidator(BaseValidator):
 
     def __init__(self, dataloader=None, save_dir=None, pbar=None, logger=None, args=None):
         super().__init__(dataloader, save_dir, pbar, logger, args)
+        self.args.task = 'detect'
         self.data_dict = yaml_load(check_file(self.args.data), append_filename=True) if self.args.data else None
         self.is_coco = False
         self.class_map = None

ultralytics/yolo/v8/segment/predict.py

@@ -87,7 +87,7 @@ class SegmentationPredictor(DetectionPredictor):
                 c = int(cls)  # integer class
                 label = None if self.args.hide_labels else (
                     self.model.names[c] if self.args.hide_conf else f'{self.model.names[c]} {conf:.2f}')
-                self.annotator.box_label(d.xyxy.squeeze(), label, color=colors(c, True))
+                self.annotator.box_label(d.xyxy.squeeze(), label, color=colors(c, True)) if self.args.boxes else None
             if self.args.save_crop:
                 imc = im0.copy()
                 save_one_box(d.xyxy,

ultralytics/yolo/v8/segment/val.py

@@ -19,7 +19,7 @@ class SegmentationValidator(DetectionValidator):
 
     def __init__(self, dataloader=None, save_dir=None, pbar=None, logger=None, args=None):
         super().__init__(dataloader, save_dir, pbar, logger, args)
-        self.args.task = "segment"
+        self.args.task = 'segment'
         self.metrics = SegmentMetrics(save_dir=self.save_dir)
 
     def preprocess(self, batch):