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ultralytics 8.0.43 optimized Results class and fixes (#1069)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Alexander Duda <Alexander.Duda@me.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
This commit is contained in:
Glenn Jocher
2023-02-21 20:37:59 +01:00
committed by GitHub
parent f2a7a29e53
commit fe61018975
22 changed files with 180 additions and 102 deletions
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8
ultralytics/yolo/v8/detect/train.py
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@ -1,6 +1,7 @@
# Ultralytics YOLO 🚀, GPL-3.0 license
from copy import copy
import numpy as np
import torch
import torch.nn as nn
@ -12,7 +13,7 @@ from ultralytics.yolo.engine.trainer import BaseTrainer
from ultralytics.yolo.utils import DEFAULT_CFG, RANK, colorstr
from ultralytics.yolo.utils.loss import BboxLoss
from ultralytics.yolo.utils.ops import xywh2xyxy
from ultralytics.yolo.utils.plotting import plot_images, plot_results
from ultralytics.yolo.utils.plotting import plot_images, plot_labels, plot_results
from ultralytics.yolo.utils.tal import TaskAlignedAssigner, dist2bbox, make_anchors
from ultralytics.yolo.utils.torch_utils import de_parallel
@ -102,6 +103,11 @@ class DetectionTrainer(BaseTrainer):
def plot_metrics(self):
plot_results(file=self.csv) # save results.png
def plot_training_labels(self):
boxes = np.concatenate([lb['bboxes'] for lb in self.train_loader.dataset.labels], 0)
cls = np.concatenate([lb['cls'] for lb in self.train_loader.dataset.labels], 0)
plot_labels(boxes, cls.squeeze(), names=self.data['names'], save_dir=self.save_dir)
# Criterion class for computing training losses
class Loss: