diff --git a/tutorial.ipynb b/tutorial.ipynb
index 828e434f..4e7049d8 100644
--- a/tutorial.ipynb
+++ b/tutorial.ipynb
@@ -368,7 +368,7 @@
"colab_type": "text"
},
"source": [
- "![\"Open](\"https://colab.research.google.com/assets/colab-badge.svg\")
"
+ ""
]
},
{
@@ -402,10 +402,10 @@
"colab": {
"base_uri": "https://localhost:8080/"
},
- "outputId": "2e5d0950-2978-4304-856f-3b39f0d6627c"
+ "outputId": "b15def02-a331-4580-9878-8d06900e296d"
},
"source": [
- "!git clone https://github.com/ultralytics/yolov3 -b update/yolov5_v6.0_release # clone\n",
+ "!git clone https://github.com/ultralytics/yolov3 # clone\n",
"%cd yolov3\n",
"%pip install -qr requirements.txt # install\n",
"\n",
@@ -413,13 +413,13 @@
"from yolov3 import utils\n",
"display = utils.notebook_init() # checks"
],
- "execution_count": 1,
+ "execution_count": 11,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
- "YOLOv3 🚀 v9.5.0-20-g9d10fe5 torch 1.10.0+cu111 CUDA:0 (A100-SXM4-40GB, 40536MiB)\n"
+ "YOLOv3 🚀 v9.6.0-0-g7eb23e3 torch 1.10.0+cu111 CUDA:0 (A100-SXM4-40GB, 40536MiB)\n"
]
},
{
@@ -459,26 +459,26 @@
"colab": {
"base_uri": "https://localhost:8080/"
},
- "outputId": "499c53a7-95f7-4fc1-dab8-7a660b813546"
+ "outputId": "5754dd6d-b5b0-41aa-ce81-7cc7a4c30553"
},
"source": [
"!python detect.py --weights yolov3.pt --img 640 --conf 0.25 --source data/images\n",
"display.Image(filename='runs/detect/exp/zidane.jpg', width=600)"
],
- "execution_count": 3,
+ "execution_count": 15,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1mdetect: \u001b[0mweights=['yolov3.pt'], source=data/images, 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/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False\n",
- "YOLOv3 🚀 v9.5.0-20-g9d10fe5 torch 1.10.0+cu111 CUDA:0 (A100-SXM4-40GB, 40536MiB)\n",
+ "YOLOv3 🚀 v9.6.0-0-g7eb23e3 torch 1.10.0+cu111 CUDA:0 (A100-SXM4-40GB, 40536MiB)\n",
"\n",
"Fusing layers... \n",
"Model Summary: 261 layers, 61922845 parameters, 0 gradients\n",
"image 1/2 /content/yolov3/data/images/bus.jpg: 640x480 4 persons, 1 bus, 1 tie, Done. (0.020s)\n",
"image 2/2 /content/yolov3/data/images/zidane.jpg: 384x640 2 persons, 3 ties, Done. (0.020s)\n",
- "Speed: 0.5ms pre-process, 19.8ms inference, 1.2ms NMS per image at shape (1, 3, 640, 640)\n",
+ "Speed: 0.6ms pre-process, 20.0ms inference, 1.2ms NMS per image at shape (1, 3, 640, 640)\n",
"Results saved to \u001b[1mruns/detect/exp\u001b[0m\n"
]
}
@@ -567,43 +567,42 @@
"colab": {
"base_uri": "https://localhost:8080/"
},
- "outputId": "0f4cfe4e-364e-4d79-e0af-8884d89eaacd"
+ "outputId": "fe3159ef-a2e4-49e3-ec0b-2ef434e9a28e"
},
"source": [
"# Run YOLOv3 on COCO val\n",
"!python val.py --weights yolov3.pt --data coco.yaml --img 640 --iou 0.65 --half"
],
- "execution_count": 5,
+ "execution_count": 13,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[34m\u001b[1mval: \u001b[0mdata=/content/yolov3/data/coco.yaml, weights=['yolov3.pt'], batch_size=32, imgsz=640, conf_thres=0.001, iou_thres=0.65, task=val, device=, single_cls=False, augment=False, verbose=False, save_txt=False, save_hybrid=False, save_conf=False, save_json=True, project=runs/val, name=exp, exist_ok=False, half=True, dnn=False\n",
- "YOLOv3 🚀 v9.5.0-20-g9d10fe5 torch 1.10.0+cu111 CUDA:0 (A100-SXM4-40GB, 40536MiB)\n",
+ "YOLOv3 🚀 v9.6.0-0-g7eb23e3 torch 1.10.0+cu111 CUDA:0 (A100-SXM4-40GB, 40536MiB)\n",
"\n",
"Fusing layers... \n",
"Model Summary: 261 layers, 61922845 parameters, 0 gradients\n",
- "\u001b[34m\u001b[1mval: \u001b[0mScanning '../datasets/coco/val2017' images and labels...4952 found, 48 missing, 0 empty, 0 corrupted: 100% 5000/5000 [00:00<00:00, 12689.82it/s]\n",
- "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: ../datasets/coco/val2017.cache\n",
- " Class Images Labels P R mAP@.5 mAP@.5:.95: 100% 157/157 [00:42<00:00, 3.70it/s]\n",
+ "\u001b[34m\u001b[1mval: \u001b[0mScanning '../datasets/coco/val2017.cache' images and labels... 4952 found, 48 missing, 0 empty, 0 corrupted: 100% 5000/5000 [00:00