ultralytics 8.0.105 classification hyp fix and new onplot callbacks (#2684)

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: Ivan Shcheklein <shcheklein@gmail.com>

ultralytics/yolo/engine/trainer.py

@@ -85,6 +85,7 @@ class BaseTrainer:
         self.validator = None
         self.model = None
         self.metrics = None
+        self.plots = {}
         init_seeds(self.args.seed + 1 + RANK, deterministic=self.args.deterministic)
 
         # Dirs
@@ -537,6 +538,10 @@ class BaseTrainer:
         """Plot and display metrics visually."""
         pass
 
+    def on_plot(self, name, data=None):
+        """Registers plots (e.g. to be consumed in callbacks)"""
+        self.plots[name] = {'data': data, 'timestamp': time.time()}
+
     def final_eval(self):
         """Performs final evaluation and validation for object detection YOLO model."""
         for f in self.last, self.best:

ultralytics/yolo/engine/validator.py

@@ -19,6 +19,7 @@ Usage - formats:
                           yolov8n_paddle_model       # PaddlePaddle
 """
 import json
+import time
 from pathlib import Path
 
 import torch
@@ -84,6 +85,7 @@ class BaseValidator:
         if self.args.conf is None:
             self.args.conf = 0.001  # default conf=0.001
 
+        self.plots = {}
         self.callbacks = _callbacks or callbacks.get_default_callbacks()
 
     @smart_inference_mode()
@@ -252,6 +254,10 @@ class BaseValidator:
         """Returns the metric keys used in YOLO training/validation."""
         return []
 
+    def on_plot(self, name, data=None):
+        """Registers plots (e.g. to be consumed in callbacks)"""
+        self.plots[name] = {'data': data, 'timestamp': time.time()}
+
     # TODO: may need to put these following functions into callback
     def plot_val_samples(self, batch, ni):
         """Plots validation samples during training."""