Commit 29.05.2025

This commit is contained in:
Winz 2025-06-01 14:01:16 +02:00
parent 2f1080922f
commit 1e4d9ecef7
43 changed files with 9085 additions and 3 deletions

4
.gitignore vendored
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@ -27,6 +27,7 @@ var/
venv/
ENV/
env/
yolov8env/
.venv/
.env/
.ENV/
@ -109,3 +110,6 @@ dmypy.json
#Models
*.keras
*.h5
runs/
Test/

20
test_yolo.py Normal file
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@ -0,0 +1,20 @@
from ultralytics import YOLO
import os
# Ordner mit Bildern
image_dir = "Test"
model = YOLO("Test/best.pt")
# Schleife über alle Dateien im Ordner
for filename in os.listdir(image_dir):
if filename.lower().endswith((".jpg", ".jpeg", ".png")):
image_path = os.path.join(image_dir, filename)
results = model(image_path, save=True) # Speichert Bild mit BBox
# Alternativ: Zugriff auf erkannte Objekte
for r in results:
print(r.boxes.xyxy) # Koordinaten
print(r.boxes.conf) # Confidence
print(r.boxes.cls) # Klassen

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@ -6,6 +6,8 @@ import shutil
from pathlib import Path
import cv2
import numpy as np
import torch
import torchvision
def verify_images(dataset_path):
"""Überprüfe alle Bilder auf Lesbarkeit und korrekte Dimensionen."""
@ -79,7 +81,7 @@ def train_yolo():
epochs=50,
imgsz=640, # Bildgröße
batch=16, # Batch-Größe
device='cpu', # Verwende CPU (oder 'cuda' für GPU)
device=0, # Verwende CPU (oder 'cuda' für GPU)
patience=5, # Early Stopping
save=True, # Speichere die besten Gewichte
project='yolo_training', # Projektname

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@ -1,6 +1,6 @@
names:
0: NAO-Roboter
nc: 1
path: C:\Users\vincent.hanewinkel\Projekts\Hochschule\NAO_Roboter_Erkennung\yolo_dataset
path: C:\Users\Vinz\Desktop\Uni\NAO_Roboter_Erkennung\yolo_dataset
train: train/images
val: val/images

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@ -0,0 +1,105 @@
task: detect
mode: train
model: yolov8n.pt
data: yolo_dataset\dataset.yaml
epochs: 50
time: null
patience: 5
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: '0'
workers: 8
project: yolo_training
name: NAO_detector11
exist_ok: false
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.1
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: yolo_training\NAO_detector11

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@ -0,0 +1,105 @@
task: detect
mode: train
model: yolov8n.pt
data: yolo_dataset\dataset.yaml
epochs: 50
time: null
patience: 5
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: '0'
workers: 8
project: yolo_training
name: NAO_detector12
exist_ok: false
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.1
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: yolo_training\NAO_detector12

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@ -0,0 +1,105 @@
task: detect
mode: train
model: yolov8n.pt
data: yolo_dataset\dataset.yaml
epochs: 50
time: null
patience: 5
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: '0'
workers: 8
project: yolo_training
name: NAO_detector13
exist_ok: false
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.1
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: yolo_training\NAO_detector13

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@ -0,0 +1,105 @@
task: detect
mode: train
model: yolov8n.pt
data: yolo_dataset\dataset.yaml
epochs: 50
time: null
patience: 5
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: '0'
workers: 8
project: yolo_training
name: NAO_detector14
exist_ok: false
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.1
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: yolo_training\NAO_detector14

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@ -0,0 +1,105 @@
task: detect
mode: train
model: yolov8n.pt
data: yolo_dataset\dataset.yaml
epochs: 50
time: null
patience: 5
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: '0'
workers: 8
project: yolo_training
name: NAO_detector15
exist_ok: false
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.1
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: yolo_training\NAO_detector15

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@ -0,0 +1,105 @@
task: detect
mode: train
model: yolov8n.pt
data: yolo_dataset\dataset.yaml
epochs: 50
time: null
patience: 5
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: '0'
workers: 8
project: yolo_training
name: NAO_detector16
exist_ok: false
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.1
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: yolo_training\NAO_detector16

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@ -0,0 +1,105 @@
task: detect
mode: train
model: yolov8n.pt
data: yolo_dataset\dataset.yaml
epochs: 50
time: null
patience: 5
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: '0'
workers: 8
project: yolo_training
name: NAO_detector17
exist_ok: false
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.1
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: yolo_training\NAO_detector17

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@ -0,0 +1,105 @@
task: detect
mode: train
model: yolov8n.pt
data: yolo_dataset\dataset.yaml
epochs: 50
time: null
patience: 5
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: '0'
workers: 8
project: yolo_training
name: NAO_detector18
exist_ok: false
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.1
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: yolo_training\NAO_detector18

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@ -0,0 +1,105 @@
task: detect
mode: train
model: yolov8n.pt
data: yolo_dataset\dataset.yaml
epochs: 50
time: null
patience: 5
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: '0'
workers: 8
project: yolo_training
name: NAO_detector19
exist_ok: false
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.1
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: yolo_training\NAO_detector19

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@ -0,0 +1,105 @@
task: detect
mode: train
model: yolov8n.pt
data: yolo_dataset\dataset.yaml
epochs: 50
time: null
patience: 5
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: '0'
workers: 8
project: yolo_training
name: NAO_detector20
exist_ok: false
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.1
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
cutmix: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: yolo_training\NAO_detector20

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@ -0,0 +1,9 @@
epoch,time,train/box_loss,train/cls_loss,train/dfl_loss,metrics/precision(B),metrics/recall(B),metrics/mAP50(B),metrics/mAP50-95(B),val/box_loss,val/cls_loss,val/dfl_loss,lr/pg0,lr/pg1,lr/pg2
1,7.52047,1.11723,2.50827,1.23344,0.64416,0.6625,0.61984,0.42558,0.9807,2.84796,1.01126,0.00026,0.00026,0.00026
2,13.5902,1.01682,1.57683,1.09305,1,0.12005,0.76681,0.44889,1.05037,2.75628,1.06677,0.000529308,0.000529308,0.000529308
3,19.5255,1.02244,1.39512,1.15623,0.8902,0.6,0.82099,0.51933,1.15541,2.53382,1.13425,0.000787528,0.000787528,0.000787528
4,25.4312,1.03477,1.36568,1.15,0.69453,0.45479,0.54394,0.33059,1.18176,2.86775,1.29124,0.00103466,0.00103466,0.00103466
5,31.4153,1.05084,1.29919,1.1604,0.74022,0.6125,0.67861,0.46042,1.10177,2.15402,1.20983,0.0012707,0.0012707,0.0012707
6,37.2791,1.06106,1.2984,1.16066,0.76601,0.45015,0.53968,0.32264,1.32466,2.36514,1.48035,0.00149566,0.00149566,0.00149566
7,43.1021,1.09893,1.24551,1.19656,0.82645,0.65481,0.73781,0.49082,1.1212,2.01043,1.27297,0.00170953,0.00170953,0.00170953
8,48.9792,1.03723,1.1235,1.16268,0.71323,0.6625,0.74511,0.45166,1.1994,1.97413,1.27788,0.0017228,0.0017228,0.0017228
1 epoch time train/box_loss train/cls_loss train/dfl_loss metrics/precision(B) metrics/recall(B) metrics/mAP50(B) metrics/mAP50-95(B) val/box_loss val/cls_loss val/dfl_loss lr/pg0 lr/pg1 lr/pg2
2 1 7.52047 1.11723 2.50827 1.23344 0.64416 0.6625 0.61984 0.42558 0.9807 2.84796 1.01126 0.00026 0.00026 0.00026
3 2 13.5902 1.01682 1.57683 1.09305 1 0.12005 0.76681 0.44889 1.05037 2.75628 1.06677 0.000529308 0.000529308 0.000529308
4 3 19.5255 1.02244 1.39512 1.15623 0.8902 0.6 0.82099 0.51933 1.15541 2.53382 1.13425 0.000787528 0.000787528 0.000787528
5 4 25.4312 1.03477 1.36568 1.15 0.69453 0.45479 0.54394 0.33059 1.18176 2.86775 1.29124 0.00103466 0.00103466 0.00103466
6 5 31.4153 1.05084 1.29919 1.1604 0.74022 0.6125 0.67861 0.46042 1.10177 2.15402 1.20983 0.0012707 0.0012707 0.0012707
7 6 37.2791 1.06106 1.2984 1.16066 0.76601 0.45015 0.53968 0.32264 1.32466 2.36514 1.48035 0.00149566 0.00149566 0.00149566
8 7 43.1021 1.09893 1.24551 1.19656 0.82645 0.65481 0.73781 0.49082 1.1212 2.01043 1.27297 0.00170953 0.00170953 0.00170953
9 8 48.9792 1.03723 1.1235 1.16268 0.71323 0.6625 0.74511 0.45166 1.1994 1.97413 1.27788 0.0017228 0.0017228 0.0017228

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description: Ultralytics best model trained on yolo_dataset\dataset.yaml
author: Ultralytics
date: '2025-05-30T16:19:53.376545'
version: 8.3.146
license: AGPL-3.0 License (https://ultralytics.com/license)
docs: https://docs.ultralytics.com
stride: 32
task: detect
batch: 1
imgsz:
- 640
- 640
names:
0: NAO-Roboter
args:
batch: 1
fraction: 1.0
half: false
int8: false
dynamic: false
nms: false
channels: 3

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