96*64 Model

train_yolo.py

@@ -81,7 +81,7 @@ def train_yolo():
     results = model.train(
         data=dataset_yaml,
         epochs=50,
-        imgsz=320,  # Bildgröße
+        imgsz=(80, 60),  # Bildgröße
         batch=16,    # Batch-Größe
         device=0,  # Verwende CPU (oder 'cuda' für GPU)
         patience=5,   # Early Stopping
@@ -94,13 +94,13 @@ def train_yolo():
     print("\nExportiere Modell in verschiedene Formate...")
     
     # ONNX Format (gut für eingebettete Systeme)
-    model.export(format='onnx', imgsz=320)
+    model.export(format='onnx', imgsz=(80, 60))
     
     # OpenVINO Format (optimiert für Intel Hardware)
-    model.export(format='openvino', imgsz=320)
+    model.export(format='openvino', imgsz=(80, 60))
 
     # tflite Format  
-    model.export(format="tflite",imgsz=320,)
+    model.export(format="tflite",imgsz=(80, 60))
     
     print("\nTraining abgeschlossen. Die Modelle wurden im 'yolo_training/NAO_detector' Ordner gespeichert.")
 

yolo_training/NAO_detector2/args.yaml

@@ -0,0 +1,107 @@
+task: detect
+mode: train
+model: yolov8n.pt
+data: yolo_dataset/dataset.yaml
+epochs: 50
+time: null
+patience: 5
+batch: 16
+imgsz:
+- 80
+- 60
+save: true
+save_period: -1
+cache: false
+device: '0'
+workers: 8
+project: yolo_training
+name: NAO_detector2
+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_detector2

yolo_training/NAO_detector2/results.csv

@@ -0,0 +1,10 @@
+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
+1,24.9125,2.15409,2.10792,1.24391,0.70243,0.4878,0.62258,0.37583,1.54244,1.4288,1.21992,0.000661064,0.000661064,0.000661064
+2,44.9091,1.91187,1.19581,1.12279,0.49108,0.63415,0.60834,0.32513,1.60866,1.27692,1.43341,0.00130144,0.00130144,0.00130144
+3,64.026,1.83625,1.09237,1.10677,0.59025,0.65854,0.64126,0.31251,1.64287,1.30798,1.50193,0.00191542,0.00191542,0.00191542
+4,84.1255,1.77744,1.09722,1.09541,0.78965,0.5122,0.60462,0.39948,1.50564,1.37216,1.36987,0.0018812,0.0018812,0.0018812
+5,106.065,1.72451,1.00674,1.0756,0.69027,0.58537,0.65348,0.36967,1.56627,1.19791,1.38099,0.0018416,0.0018416,0.0018416
+6,128.173,1.6816,0.96545,1.06602,0.5608,0.73171,0.62227,0.31853,1.65704,1.24745,1.38968,0.001802,0.001802,0.001802
+7,149.813,1.66449,0.95214,1.05808,0.80001,0.7561,0.86342,0.53905,1.33301,0.97867,1.1847,0.0017624,0.0017624,0.0017624
+8,175.593,1.61801,0.92736,1.03716,0.7216,0.78049,0.77649,0.54305,1.18629,0.92563,1.14214,0.0017228,0.0017228,0.0017228
+9,200.309,1.54485,0.88521,1.02098,0.7252,0.77253,0.77037,0.46198,1.47832,1.13508,1.3266,0.0016832,0.0016832,0.0016832

yolo_training/NAO_detector3/args.yaml

@@ -0,0 +1,107 @@
+task: detect
+mode: train
+model: yolov8n.pt
+data: yolo_dataset/dataset.yaml
+epochs: 50
+time: null
+patience: 5
+batch: 16
+imgsz:
+- 80
+- 60
+save: true
+save_period: -1
+cache: false
+device: '0'
+workers: 8
+project: yolo_training
+name: NAO_detector3
+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_detector3

yolo_training/NAO_detector3/results.csv

@@ -0,0 +1,13 @@
+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
+1,29.4662,2.15409,2.10792,1.24391,0.70243,0.4878,0.62258,0.37583,1.54244,1.4288,1.21992,0.000661064,0.000661064,0.000661064
+2,51.925,1.91187,1.19581,1.12279,0.49108,0.63415,0.60834,0.32513,1.60866,1.27692,1.43341,0.00130144,0.00130144,0.00130144
+3,72.4804,1.83625,1.09237,1.10677,0.59025,0.65854,0.64126,0.31251,1.64287,1.30798,1.50193,0.00191542,0.00191542,0.00191542
+4,98.9677,1.77744,1.09722,1.09541,0.78965,0.5122,0.60462,0.39948,1.50564,1.37216,1.36987,0.0018812,0.0018812,0.0018812
+5,118.106,1.72451,1.00674,1.0756,0.69027,0.58537,0.65348,0.36967,1.56627,1.19791,1.38099,0.0018416,0.0018416,0.0018416
+6,136.699,1.6816,0.96545,1.06602,0.5608,0.73171,0.62227,0.31853,1.65704,1.24745,1.38968,0.001802,0.001802,0.001802
+7,155.502,1.66449,0.95214,1.05808,0.80001,0.7561,0.86342,0.53905,1.33301,0.97867,1.1847,0.0017624,0.0017624,0.0017624
+8,174.612,1.61801,0.92736,1.03716,0.7216,0.78049,0.77649,0.54305,1.18629,0.92563,1.14214,0.0017228,0.0017228,0.0017228
+9,193.332,1.54485,0.88521,1.02098,0.7252,0.77253,0.77037,0.46198,1.47832,1.13508,1.3266,0.0016832,0.0016832,0.0016832
+10,213.278,1.52407,0.88361,1.02719,0.68497,0.7561,0.82585,0.47667,1.48575,0.98921,1.26247,0.0016436,0.0016436,0.0016436
+11,234.356,1.49379,0.85295,1.01718,0.79063,0.58537,0.74858,0.47275,1.34454,1.0461,1.17443,0.001604,0.001604,0.001604
+12,254.546,1.49671,0.86267,1.01529,0.9186,0.82577,0.89399,0.51789,1.40833,0.89727,1.26746,0.0015644,0.0015644,0.0015644

yolo_training/NAO_detector3/weights/best_openvino_model/metadata.yaml

@@ -0,0 +1,22 @@
+description: Ultralytics best model trained on yolo_dataset/dataset.yaml
+author: Ultralytics
+date: '2025-08-11T23:12:24.345477'
+version: 8.3.154
+license: AGPL-3.0 License (https://ultralytics.com/license)
+docs: https://docs.ultralytics.com
+stride: 32
+task: detect
+batch: 1
+imgsz:
+- 96
+- 64
+names:
+  0: NAO-Roboter
+args:
+  batch: 1
+  fraction: 1.0
+  half: false
+  int8: false
+  dynamic: false
+  nms: false
+channels: 3

yolo_training/NAO_detector3/weights/best_saved_model/fingerprint.pb

@@ -0,0 +1 @@
+ёцм╕╫н╟²К
ъуА⌠сЧ·╒fИ╖╣М┌▒ц▀J ├┬└Иоъ∙▀┐
(⌠ИЯ∙╡жЫьН
2
:11516240603058020176

yolo_training/NAO_detector3/weights/best_saved_model/metadata.yaml

@@ -0,0 +1,21 @@
+description: Ultralytics best model trained on yolo_dataset/dataset.yaml
+author: Ultralytics
+date: '2025-08-11T23:12:31.669237'
+version: 8.3.154
+license: AGPL-3.0 License (https://ultralytics.com/license)
+docs: https://docs.ultralytics.com
+stride: 32
+task: detect
+batch: 1
+imgsz:
+- 96
+- 64
+names:
+  0: NAO-Roboter
+args:
+  batch: 1
+  fraction: 1.0
+  half: false
+  int8: false
+  nms: false
+channels: 3