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Fix YOLO11 YouTube link (#16542)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn Jocher 2024-09-30 03:20:57 +02:00 • committed by GitHub
parent 6e43d1e1e5
commit ccee8533c1
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10 changed files with 95 additions and 95 deletions
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2
examples/heatmaps.ipynb
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@ -56,7 +56,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Ultralytics YOLOv8.2.17 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
"Ultralytics YOLOv8.2.17 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (T4, 15102MiB)\n",
"Setup complete ✅ (2 CPUs, 12.7 GB RAM, 29.8/78.2 GB disk)\n"
]
}

2
examples/hub.ipynb
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@ -54,7 +54,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (T4, 15102MiB)\n",
"Setup complete ✅ (2 CPUs, 12.7 GB RAM, 28.8/78.2 GB disk)\n"
]
}

2
examples/object_counting.ipynb
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@ -56,7 +56,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Ultralytics YOLOv8.2.18 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
"Ultralytics YOLOv8.2.18 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (T4, 15102MiB)\n",
"Setup complete ✅ (2 CPUs, 12.7 GB RAM, 29.8/78.2 GB disk)\n"
]
}

2
examples/object_tracking.ipynb
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@ -56,7 +56,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Ultralytics YOLOv8.2.17 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
"Ultralytics YOLOv8.2.17 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (T4, 15102MiB)\n",
"Setup complete ✅ (2 CPUs, 12.7 GB RAM, 29.8/78.2 GB disk)\n"
]
}

10
examples/tutorial.ipynb
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@ -78,7 +78,7 @@
"output_type": "stream",
"name": "stdout",
"text": [
"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (T4, 15102MiB)\n",
"Setup complete ✅ (2 CPUs, 12.7 GB RAM, 28.8/78.2 GB disk)\n"
]
}
@ -116,7 +116,7 @@
"text": [
"Downloading https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8n.pt to 'yolov8n.pt'...\n",
"100% 6.23M/6.23M [00:00<00:00, 83.2MB/s]\n",
"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (T4, 15102MiB)\n",
"YOLOv8n summary (fused): 168 layers, 3151904 parameters, 0 gradients, 8.7 GFLOPs\n",
"\n",
"Downloading https://ultralytics.com/images/zidane.jpg to 'zidane.jpg'...\n",
@ -182,7 +182,7 @@
"output_type": "stream",
"name": "stdout",
"text": [
"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (T4, 15102MiB)\n",
"YOLOv8n summary (fused): 168 layers, 3151904 parameters, 0 gradients, 8.7 GFLOPs\n",
"\n",
"Dataset 'coco8.yaml' images not found ⚠️, missing path '/content/datasets/coco8/images/val'\n",
@ -261,7 +261,7 @@
"output_type": "stream",
"name": "stdout",
"text": [
"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (T4, 15102MiB)\n",
"\u001b[34m\u001b[1mengine/trainer: \u001b[0mtask=detect, mode=train, model=yolov8n.pt, data=coco8.yaml, epochs=3, time=None, patience=100, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train, 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=None, multi_scale=False, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, embed=None, 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=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=None, workspace=4, 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, label_smoothing=0.0, 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, copy_paste=0.0, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml, save_dir=runs/detect/train\n",
"\n",
" from n params module arguments \n",
@ -330,7 +330,7 @@
"Optimizer stripped from runs/detect/train/weights/best.pt, 6.5MB\n",
"\n",
"Validating runs/detect/train/weights/best.pt...\n",
"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)\n",
"Ultralytics YOLOv8.2.3 🚀 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (T4, 15102MiB)\n",
"Model summary (fused): 168 layers, 3151904 parameters, 0 gradients, 8.7 GFLOPs\n",
" Class Images Instances Box(P R mAP50 mAP50-95): 100% 1/1 [00:00<00:00, 18.23it/s]\n",
" all 4 17 0.617 0.884 0.888 0.622\n",