Merge branch 'master' into remove-manual-accounting
Ultralytics Assistant
GitHub
commit
2a826bfcd6
|
|
@ -4,7 +4,7 @@
|
|||
<img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/banner-yolov8.png"></a>
|
||||
</p>
|
||||
|
||||
[中文](https://docs.ultralytics.com/zh/) | [한국어](https://docs.ultralytics.com/ko/) | [日本語](https://docs.ultralytics.com/ja/) | [Русский](https://docs.ultralytics.com/ru/) | [Deutsch](https://docs.ultralytics.com/de/) | [Français](https://docs.ultralytics.com/fr/) | [Español](https://docs.ultralytics.com/es/) | [Português](https://docs.ultralytics.com/pt/) | [Türkçe](https://docs.ultralytics.com/tr/) | [Tiếng Việt](https://docs.ultralytics.com/vi/) | [हिन्दी](https://docs.ultralytics.com/hi/) | [العربية](https://docs.ultralytics.com/ar/)
|
||||
[中文](https://docs.ultralytics.com/zh/) | [한국어](https://docs.ultralytics.com/ko/) | [日本語](https://docs.ultralytics.com/ja/) | [Русский](https://docs.ultralytics.com/ru/) | [Deutsch](https://docs.ultralytics.com/de/) | [Français](https://docs.ultralytics.com/fr/) | [Español](https://docs.ultralytics.com/es/) | [Português](https://docs.ultralytics.com/pt/) | [Türkçe](https://docs.ultralytics.com/tr/) | [Tiếng Việt](https://docs.ultralytics.com/vi/) | [العربية](https://docs.ultralytics.com/ar/)
|
||||
|
||||
<div>
|
||||
<a href="https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml"><img src="https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml/badge.svg" alt="YOLOv5 CI"></a>
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
<img width="100%" src="https://raw.githubusercontent.com/ultralytics/assets/main/yolov8/banner-yolov8.png"></a>
|
||||
</p>
|
||||
|
||||
[中文](https://docs.ultralytics.com/zh/) | [한국어](https://docs.ultralytics.com/ko/) | [日本語](https://docs.ultralytics.com/ja/) | [Русский](https://docs.ultralytics.com/ru/) | [Deutsch](https://docs.ultralytics.com/de/) | [Français](https://docs.ultralytics.com/fr/) | [Español](https://docs.ultralytics.com/es/) | [Português](https://docs.ultralytics.com/pt/) | [Türkçe](https://docs.ultralytics.com/tr/) | [Tiếng Việt](https://docs.ultralytics.com/vi/) | [हिन्दी](https://docs.ultralytics.com/hi/) | [العربية](https://docs.ultralytics.com/ar/)
|
||||
[中文](https://docs.ultralytics.com/zh/) | [한국어](https://docs.ultralytics.com/ko/) | [日本語](https://docs.ultralytics.com/ja/) | [Русский](https://docs.ultralytics.com/ru/) | [Deutsch](https://docs.ultralytics.com/de/) | [Français](https://docs.ultralytics.com/fr/) | [Español](https://docs.ultralytics.com/es/) | [Português](https://docs.ultralytics.com/pt/) | [Türkçe](https://docs.ultralytics.com/tr/) | [Tiếng Việt](https://docs.ultralytics.com/vi/) | [العربية](https://docs.ultralytics.com/ar/)
|
||||
|
||||
<div>
|
||||
<a href="https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml"><img src="https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml/badge.svg" alt="YOLOv5 CI"></a>
|
||||
|
|
|
|||
|
|
@ -46,15 +46,15 @@
|
|||
},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"YOLOv5 🚀 v7.0-3-g61ebf5e Python-3.7.15 torch-1.12.1+cu113 CUDA:0 (Tesla T4, 15110MiB)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Setup complete ✅ (2 CPUs, 12.7 GB RAM, 22.6/78.2 GB disk)\n"
|
||||
]
|
||||
|
|
@ -66,7 +66,9 @@
|
|||
"%pip install -qr requirements.txt # install\n",
|
||||
"\n",
|
||||
"import torch\n",
|
||||
"\n",
|
||||
"import utils\n",
|
||||
"\n",
|
||||
"display = utils.notebook_init() # checks"
|
||||
]
|
||||
},
|
||||
|
|
@ -104,8 +106,8 @@
|
|||
},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[34m\u001b[1mclassify/predict: \u001b[0mweights=['yolov5s-cls.pt'], source=data/images, data=data/coco128.yaml, imgsz=[224, 224], device=, view_img=False, save_txt=False, nosave=False, augment=False, visualize=False, update=False, project=runs/predict-cls, name=exp, exist_ok=False, half=False, dnn=False, vid_stride=1\n",
|
||||
"YOLOv5 🚀 v7.0-3-g61ebf5e Python-3.7.15 torch-1.12.1+cu113 CUDA:0 (Tesla T4, 15110MiB)\n",
|
||||
|
|
@ -159,8 +161,8 @@
|
|||
},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"--2022-11-22 19:53:40-- https://image-net.org/data/ILSVRC/2012/ILSVRC2012_img_val.tar\n",
|
||||
"Resolving image-net.org (image-net.org)... 171.64.68.16\n",
|
||||
|
|
@ -193,8 +195,8 @@
|
|||
},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[34m\u001b[1mclassify/val: \u001b[0mdata=../datasets/imagenet, weights=['yolov5s-cls.pt'], batch_size=128, imgsz=224, device=, workers=8, verbose=True, project=runs/val-cls, name=exp, exist_ok=False, half=True, dnn=False\n",
|
||||
"YOLOv5 🚀 v7.0-3-g61ebf5e Python-3.7.15 torch-1.12.1+cu113 CUDA:0 (Tesla T4, 15110MiB)\n",
|
||||
|
|
@ -1255,15 +1257,19 @@
|
|||
"outputs": [],
|
||||
"source": [
|
||||
"# @title Select YOLOv5 🚀 logger {run: 'auto'}\n",
|
||||
"logger = 'Comet' #@param ['Comet', 'ClearML', 'TensorBoard']\n",
|
||||
"logger = \"Comet\" # @param ['Comet', 'ClearML', 'TensorBoard']\n",
|
||||
"\n",
|
||||
"if logger == 'Comet':\n",
|
||||
"if logger == \"Comet\":\n",
|
||||
" %pip install -q comet_ml\n",
|
||||
" import comet_ml; comet_ml.init()\n",
|
||||
"elif logger == 'ClearML':\n",
|
||||
" import comet_ml\n",
|
||||
"\n",
|
||||
" comet_ml.init()\n",
|
||||
"elif logger == \"ClearML\":\n",
|
||||
" %pip install -q clearml\n",
|
||||
" import clearml; clearml.browser_login()\n",
|
||||
"elif logger == 'TensorBoard':\n",
|
||||
" import clearml\n",
|
||||
"\n",
|
||||
" clearml.browser_login()\n",
|
||||
"elif logger == \"TensorBoard\":\n",
|
||||
" %load_ext tensorboard\n",
|
||||
" %tensorboard --logdir runs/train"
|
||||
]
|
||||
|
|
@ -1280,8 +1286,8 @@
|
|||
},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[34m\u001b[1mclassify/train: \u001b[0mmodel=yolov5s-cls.pt, data=imagenette160, epochs=5, batch_size=64, imgsz=224, nosave=False, cache=ram, device=, workers=8, project=runs/train-cls, name=exp, exist_ok=False, pretrained=True, optimizer=Adam, lr0=0.001, decay=5e-05, label_smoothing=0.1, cutoff=None, dropout=None, verbose=False, seed=0, local_rank=-1\n",
|
||||
"\u001b[34m\u001b[1mgithub: \u001b[0mup to date with https://github.com/ultralytics/yolov5 ✅\n",
|
||||
|
|
@ -1443,10 +1449,11 @@
|
|||
"outputs": [],
|
||||
"source": [
|
||||
"# YOLOv5 PyTorch HUB Inference (DetectionModels only)\n",
|
||||
"import torch\n",
|
||||
"\n",
|
||||
"model = torch.hub.load('ultralytics/yolov5', 'yolov5s', force_reload=True, trust_repo=True) # or yolov5n - yolov5x6 or custom\n",
|
||||
"im = 'https://ultralytics.com/images/zidane.jpg' # file, Path, PIL.Image, OpenCV, nparray, list\n",
|
||||
"model = torch.hub.load(\n",
|
||||
" \"ultralytics/yolov5\", \"yolov5s\", force_reload=True, trust_repo=True\n",
|
||||
") # or yolov5n - yolov5x6 or custom\n",
|
||||
"im = \"https://ultralytics.com/images/zidane.jpg\" # file, Path, PIL.Image, OpenCV, nparray, list\n",
|
||||
"results = model(im) # inference\n",
|
||||
"results.print() # or .show(), .save(), .crop(), .pandas(), etc."
|
||||
]
|
||||
|
|
|
|||
|
|
@ -46,15 +46,15 @@
|
|||
},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"YOLOv5 🚀 v7.0-2-gc9d47ae Python-3.7.15 torch-1.12.1+cu113 CUDA:0 (Tesla T4, 15110MiB)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Setup complete ✅ (2 CPUs, 12.7 GB RAM, 22.6/78.2 GB disk)\n"
|
||||
]
|
||||
|
|
@ -66,7 +66,9 @@
|
|||
"%pip install -qr requirements.txt comet_ml # install\n",
|
||||
"\n",
|
||||
"import torch\n",
|
||||
"\n",
|
||||
"import utils\n",
|
||||
"\n",
|
||||
"display = utils.notebook_init() # checks"
|
||||
]
|
||||
},
|
||||
|
|
@ -104,8 +106,8 @@
|
|||
},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[34m\u001b[1msegment/predict: \u001b[0mweights=['yolov5s-seg.pt'], source=data/images, data=data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/predict-seg, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1, retina_masks=False\n",
|
||||
"YOLOv5 🚀 v7.0-2-gc9d47ae Python-3.7.15 torch-1.12.1+cu113 CUDA:0 (Tesla T4, 15110MiB)\n",
|
||||
|
|
@ -159,8 +161,8 @@
|
|||
},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Downloading https://github.com/ultralytics/assets/releases/download/v0.0.0/coco2017labels-segments.zip ...\n",
|
||||
"Downloading http://images.cocodataset.org/zips/val2017.zip ...\n",
|
||||
|
|
@ -186,8 +188,8 @@
|
|||
},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[34m\u001b[1msegment/val: \u001b[0mdata=/content/yolov5/data/coco.yaml, weights=['yolov5s-seg.pt'], batch_size=32, imgsz=640, conf_thres=0.001, iou_thres=0.6, max_det=300, task=val, device=, workers=8, single_cls=False, augment=False, verbose=False, save_txt=False, save_hybrid=False, save_conf=False, save_json=False, project=runs/val-seg, name=exp, exist_ok=False, half=True, dnn=False\n",
|
||||
"YOLOv5 🚀 v7.0-2-gc9d47ae Python-3.7.15 torch-1.12.1+cu113 CUDA:0 (Tesla T4, 15110MiB)\n",
|
||||
|
|
@ -250,15 +252,19 @@
|
|||
"outputs": [],
|
||||
"source": [
|
||||
"# @title Select YOLOv5 🚀 logger {run: 'auto'}\n",
|
||||
"logger = 'Comet' #@param ['Comet', 'ClearML', 'TensorBoard']\n",
|
||||
"logger = \"Comet\" # @param ['Comet', 'ClearML', 'TensorBoard']\n",
|
||||
"\n",
|
||||
"if logger == 'Comet':\n",
|
||||
"if logger == \"Comet\":\n",
|
||||
" %pip install -q comet_ml\n",
|
||||
" import comet_ml; comet_ml.init()\n",
|
||||
"elif logger == 'ClearML':\n",
|
||||
" import comet_ml\n",
|
||||
"\n",
|
||||
" comet_ml.init()\n",
|
||||
"elif logger == \"ClearML\":\n",
|
||||
" %pip install -q clearml\n",
|
||||
" import clearml; clearml.browser_login()\n",
|
||||
"elif logger == 'TensorBoard':\n",
|
||||
" import clearml\n",
|
||||
"\n",
|
||||
" clearml.browser_login()\n",
|
||||
"elif logger == \"TensorBoard\":\n",
|
||||
" %load_ext tensorboard\n",
|
||||
" %tensorboard --logdir runs/train"
|
||||
]
|
||||
|
|
@ -275,8 +281,8 @@
|
|||
},
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[34m\u001b[1msegment/train: \u001b[0mweights=yolov5s-seg.pt, cfg=, data=coco128-seg.yaml, hyp=data/hyps/hyp.scratch-low.yaml, epochs=3, batch_size=16, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=ram, image_weights=False, device=, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=runs/train-seg, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=-1, mask_ratio=4, no_overlap=False\n",
|
||||
"\u001b[34m\u001b[1mgithub: \u001b[0mup to date with https://github.com/ultralytics/yolov5 ✅\n",
|
||||
|
|
@ -556,10 +562,11 @@
|
|||
"outputs": [],
|
||||
"source": [
|
||||
"# YOLOv5 PyTorch HUB Inference (DetectionModels only)\n",
|
||||
"import torch\n",
|
||||
"\n",
|
||||
"model = torch.hub.load('ultralytics/yolov5', 'yolov5s-seg', force_reload=True, trust_repo=True) # or yolov5n - yolov5x6 or custom\n",
|
||||
"im = 'https://ultralytics.com/images/zidane.jpg' # file, Path, PIL.Image, OpenCV, nparray, list\n",
|
||||
"model = torch.hub.load(\n",
|
||||
" \"ultralytics/yolov5\", \"yolov5s-seg\", force_reload=True, trust_repo=True\n",
|
||||
") # or yolov5n - yolov5x6 or custom\n",
|
||||
"im = \"https://ultralytics.com/images/zidane.jpg\" # file, Path, PIL.Image, OpenCV, nparray, list\n",
|
||||
"results = model(im) # inference\n",
|
||||
"results.print() # or .show(), .save(), .crop(), .pandas(), etc."
|
||||
]
|
||||
|
|
|
|||
Loading…
Reference in New Issue