leeaf_trainyolo_model_trainer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2023-06-08T07:24:52.715160Z",
     "start_time": "2023-06-08T07:24:52.708871Z"
    }
   },
   "outputs": [],
   "source": [
    "# DATASET PARAMETERS\n",
    "API_KEY = \"__FILL_IN_YOUR_API_KEY__\"\n",
    "PROJECT_NAME = \"__FILL_IN_YOUR_PROJECT_NAME__\"\n",
    "\n",
    "# YOLO PARAMETERS\n",
    "IM_SIZE = 640\n",
    "N_EPOCHS = 50  # you can lower this if you have a large dataset\n",
    "BATCH_SIZE = 2  # you can increase this if you have a large dataset, > 50 images, you can increase this to 4, >100 images you can increase this to 8\n",
    "MODEL = 'yolov8n-seg.pt'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading project\n",
      "Loading samples...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 80/80 [00:00<00:00, 21236.98it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading samples... (this may take a while depending on your dataset size)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 80/80 [00:01<00:00, 50.03it/s]\n"
     ]
    }
   ],
   "source": [
    "from trainyolo.client import Client, Project\n",
    "\n",
    "# init client\n",
    "client = Client(API_KEY)\n",
    "\n",
    "# load project\n",
    "project = Project.get_by_name(client, PROJECT_NAME)\n",
    "project_location = project.pull(location='./data', format='yolov8')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-06-08T07:23:04.253663Z",
     "start_time": "2023-06-08T07:22:58.150249Z"
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  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "New https://pypi.org/project/ultralytics/8.0.114 available 😃 Update with 'pip install -U ultralytics'\r\n",
      "Ultralytics YOLOv8.0.112 🚀 Python-3.10.10 torch-2.0.1 CPU\r\n",
      "\u001B[34m\u001B[1myolo/engine/trainer: \u001B[0mtask=segment, mode=train, model=yolov8n-seg.pt, data=./data/LEEAF V1/dataset.yaml, epochs=50, patience=50, batch=2, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=None, exist_ok=False, pretrained=False, optimizer=SGD, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=0, resume=False, amp=True, fraction=1.0, profile=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, show=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, vid_stride=1, line_width=None, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, boxes=True, 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, mosaic=1.0, mixup=0.0, copy_paste=0.0, cfg=None, v5loader=False, tracker=botsort.yaml, save_dir=runs/segment/train2\r\n",
      "Overriding model.yaml nc=80 with nc=1\r\n",
      "\r\n",
      "                   from  n    params  module                                       arguments                     \r\n",
      "  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]                 \r\n",
      "  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]                \r\n",
      "  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]             \r\n",
      "  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]                \r\n",
      "  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]             \r\n",
      "  5                  -1  1     73984  ultralytics.nn.modules.conv.Conv             [64, 128, 3, 2]               \r\n",
      "  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]           \r\n",
      "  7                  -1  1    295424  ultralytics.nn.modules.conv.Conv             [128, 256, 3, 2]              \r\n",
      "  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]           \r\n",
      "  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]                 \r\n",
      " 10                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \r\n",
      " 11             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \r\n",
      " 12                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]                 \r\n",
      " 13                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \r\n",
      " 14             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \r\n",
      " 15                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]                  \r\n",
      " 16                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]                \r\n",
      " 17            [-1, 12]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \r\n",
      " 18                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]                 \r\n",
      " 19                  -1  1    147712  ultralytics.nn.modules.conv.Conv             [128, 128, 3, 2]              \r\n",
      " 20             [-1, 9]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \r\n",
      " 21                  -1  1    493056  ultralytics.nn.modules.block.C2f             [384, 256, 1]                 \r\n",
      " 22        [15, 18, 21]  1   1004275  ultralytics.nn.modules.head.Segment          [1, 32, 64, [64, 128, 256]]   \r\n",
      "YOLOv8n-seg summary: 261 layers, 3263811 parameters, 3263795 gradients\r\n",
      "\r\n",
      "Transferred 381/417 items from pretrained weights\r\n",
      "\u001B[34m\u001B[1mTensorBoard: \u001B[0mStart with 'tensorboard --logdir runs/segment/train2', view at http://localhost:6006/\r\n",
      "\u001B[34m\u001B[1moptimizer:\u001B[0m SGD(lr=0.01) with parameter groups 66 weight(decay=0.0), 77 weight(decay=0.0005), 76 bias\r\n",
      "\u001B[34m\u001B[1mtrain: \u001B[0mScanning /Users/amaxilatis/repositories/sparkworks/project-leeaf/image-pa\u001B[0m\r\n",
      "\u001B[34m\u001B[1mtrain: \u001B[0mNew cache created: /Users/amaxilatis/repositories/sparkworks/project-leeaf/image-parser/data/LEEAF V1/labels.cache\r\n",
      "\u001B[34m\u001B[1mval: \u001B[0mScanning /Users/amaxilatis/repositories/sparkworks/project-leeaf/image-pars\u001B[0m\r\n",
      "\u001B[34m\u001B[1mval: \u001B[0mNew cache created: /Users/amaxilatis/repositories/sparkworks/project-leeaf/image-parser/data/LEEAF V1/labels.cache\r\n",
      "Plotting labels to runs/segment/train2/labels.jpg... \r\n",
      "Image sizes 640 train, 640 val\r\n",
      "Using 0 dataloader workers\r\n",
      "Logging results to \u001B[1mruns/segment/train2\u001B[0m\r\n",
      "Starting training for 50 epochs...\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "       1/50         0G      1.297      1.939      3.172       1.39          8   ^C\r\n",
      "       1/50         0G      1.282      2.044      3.221      1.383         28   \r\n",
      "Traceback (most recent call last):\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/bin/yolo\", line 8, in <module>\r\n",
      "    sys.exit(entrypoint())\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/ultralytics/yolo/cfg/__init__.py\", line 398, in entrypoint\r\n",
      "    getattr(model, mode)(**overrides)  # default args from model\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/ultralytics/yolo/engine/model.py\", line 371, in train\r\n",
      "    self.trainer.train()\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/ultralytics/yolo/engine/trainer.py\", line 192, in train\r\n",
      "    self._do_train(world_size)\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/ultralytics/yolo/engine/trainer.py\", line 311, in _do_train\r\n",
      "    for i, batch in pbar:\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/tqdm/std.py\", line 1178, in __iter__\r\n",
      "    for obj in iterable:\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/ultralytics/yolo/data/build.py\", line 38, in __iter__\r\n",
      "    yield next(self.iterator)\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/torch/utils/data/dataloader.py\", line 633, in __next__\r\n",
      "    data = self._next_data()\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/torch/utils/data/dataloader.py\", line 677, in _next_data\r\n",
      "    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py\", line 51, in fetch\r\n",
      "    data = [self.dataset[idx] for idx in possibly_batched_index]\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/torch/utils/data/_utils/fetch.py\", line 51, in <listcomp>\r\n",
      "    data = [self.dataset[idx] for idx in possibly_batched_index]\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/ultralytics/yolo/data/base.py\", line 239, in __getitem__\r\n",
      "    return self.transforms(self.get_image_and_label(index))\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/ultralytics/yolo/data/augment.py\", line 56, in __call__\r\n",
      "    data = t(data)\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/ultralytics/yolo/data/augment.py\", line 56, in __call__\r\n",
      "    data = t(data)\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/ultralytics/yolo/data/augment.py\", line 443, in __call__\r\n",
      "    img, M, scale = self.affine_transform(img, border)\r\n",
      "  File \"/Users/amaxilatis/repositories/sparkworks/project-leeaf/venv/lib/python3.10/site-packages/ultralytics/yolo/data/augment.py\", line 345, in affine_transform\r\n",
      "    img = cv2.warpAffine(img, M[:2], dsize=self.size, borderValue=(114, 114, 114))\r\n",
      "KeyboardInterrupt\r\n"
     ]
    }
   ],
   "source": [
    "# Train yolo model\n",
    "!yolo task=segment mode=train model=$MODEL data=\"{project_location}/dataset.yaml\" epochs=$N_EPOCHS imgsz=$IM_SIZE batch=$BATCH_SIZE"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-06-08T07:23:26.746043Z",
     "start_time": "2023-06-08T07:23:11.638341Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n-seg.pt to yolov8n-seg.pt...\r\n",
      "100%|██████████████████████████████████████| 6.73M/6.73M [00:02<00:00, 3.37MB/s]\r\n",
      "Ultralytics YOLOv8.0.112 🚀 Python-3.10.10 torch-2.0.1 CPU\r\n",
      "\u001B[34m\u001B[1myolo/engine/trainer: \u001B[0mtask=segment, mode=train, model=yolov8n-seg.pt, data=./data/LEEAF V1/dataset.yaml, epochs=50, patience=50, batch=2, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=None, exist_ok=False, pretrained=False, optimizer=SGD, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=0, resume=False, amp=True, fraction=1.0, profile=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, show=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, vid_stride=1, line_width=None, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, boxes=True, 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, mosaic=1.0, mixup=0.0, copy_paste=0.0, cfg=None, v5loader=False, tracker=botsort.yaml, save_dir=runs/segment/train\r\n",
      "Overriding model.yaml nc=80 with nc=1\r\n",
      "\r\n",
      "                   from  n    params  module                                       arguments                     \r\n",
      "  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]                 \r\n",
      "  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]                \r\n",
      "  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]             \r\n",
      "  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]                \r\n",
      "  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]             \r\n",
      "  5                  -1  1     73984  ultralytics.nn.modules.conv.Conv             [64, 128, 3, 2]               \r\n",
      "  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]           \r\n",
      "  7                  -1  1    295424  ultralytics.nn.modules.conv.Conv             [128, 256, 3, 2]              \r\n",
      "  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]           \r\n",
      "  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]                 \r\n",
      " 10                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \r\n",
      " 11             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \r\n",
      " 12                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]                 \r\n",
      " 13                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \r\n",
      " 14             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \r\n",
      " 15                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]                  \r\n",
      " 16                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]                \r\n",
      " 17            [-1, 12]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \r\n",
      " 18                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]                 \r\n",
      " 19                  -1  1    147712  ultralytics.nn.modules.conv.Conv             [128, 128, 3, 2]              \r\n",
      " 20             [-1, 9]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \r\n",
      " 21                  -1  1    493056  ultralytics.nn.modules.block.C2f             [384, 256, 1]                 \r\n",
      " 22        [15, 18, 21]  1   1004275  ultralytics.nn.modules.head.Segment          [1, 32, 64, [64, 128, 256]]   \r\n",
      "YOLOv8n-seg summary: 261 layers, 3263811 parameters, 3263795 gradients\r\n",
      "\r\n",
      "Transferred 381/417 items from pretrained weights\r\n",
      "\u001B[34m\u001B[1mTensorBoard: \u001B[0mStart with 'tensorboard --logdir runs/segment/train', view at http://localhost:6006/\r\n",
      "\u001B[34m\u001B[1moptimizer:\u001B[0m SGD(lr=0.01) with parameter groups 66 weight(decay=0.0), 77 weight(decay=0.0005), 76 bias\r\n",
      "\u001B[34m\u001B[1mtrain: \u001B[0mScanning /Users/amaxilatis/repositories/sparkworks/project-leeaf/image-pa\u001B[0m\r\n",
      "\u001B[34m\u001B[1mtrain: \u001B[0mNew cache created: /Users/amaxilatis/repositories/sparkworks/project-leeaf/image-parser/data/LEEAF V1/labels.cache\r\n",
      "\u001B[34m\u001B[1mval: \u001B[0mScanning /Users/amaxilatis/repositories/sparkworks/project-leeaf/image-pars\u001B[0m\r\n",
      "\u001B[34m\u001B[1mval: \u001B[0mNew cache created: /Users/amaxilatis/repositories/sparkworks/project-leeaf/image-parser/data/LEEAF V1/labels.cache\r\n",
      "Plotting labels to runs/segment/train/labels.jpg... \r\n",
      "Image sizes 640 train, 640 val\r\n",
      "Using 0 dataloader workers\r\n",
      "Logging results to \u001B[1mruns/segment/train\u001B[0m\r\n",
      "Starting training for 50 epochs...\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "       1/50         0G      1.017      1.722      3.112      1.216        113   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.011      0.318     0.0819     0.0437     0.0108      0.312     0.0679     0.0389\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "       2/50         0G     0.9668      1.353      2.769      1.116          4   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176     0.0112      0.324      0.146     0.0926     0.0104      0.301       0.17     0.0929\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "       3/50         0G     0.9436      1.216       2.39      1.078         11   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.591     0.0738       0.17      0.122      0.719     0.0727       0.18       0.11\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "       4/50         0G      1.018      0.976      2.134      1.057         11   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.423      0.233      0.178      0.108      0.447      0.244      0.198      0.104\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "       5/50         0G      1.129     0.9565      1.922      1.069         15   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.485      0.244       0.22      0.128      0.531      0.267      0.236      0.139\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "       6/50         0G      1.104      1.007      1.744      1.063         13   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176       0.64      0.267      0.264       0.16      0.573      0.278      0.258      0.155\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "       7/50         0G      1.203      1.302      1.682      1.177         11   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.622      0.244      0.253      0.152      0.588      0.227      0.227      0.126\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "       8/50         0G      1.142      1.197      1.785      1.142          1   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.514      0.273      0.261       0.17      0.508      0.246      0.206      0.125\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "       9/50         0G      1.066       1.19      1.763      1.084         14   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176       0.56      0.256      0.241      0.164      0.489      0.227      0.164     0.0974\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      10/50         0G      1.023      1.113      1.567       1.12         10   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.612      0.251      0.253      0.164      0.613      0.252      0.238      0.149\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      11/50         0G       1.13      1.361      1.583      1.137         14   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.616       0.29      0.291      0.197      0.579      0.281      0.261      0.164\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      12/50         0G       1.14      1.222      1.505      1.115          4   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176       0.55      0.284      0.264       0.18      0.514       0.27      0.224      0.141\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      13/50         0G      1.013       1.02      1.469      1.048          3   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.623      0.273      0.301       0.21      0.652      0.278      0.292      0.196\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      14/50         0G      1.098      1.023      1.463      1.089          2   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.633      0.295      0.318      0.215      0.646      0.301      0.316      0.197\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      15/50         0G      1.055     0.9903       1.42      1.093         22   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176       0.83      0.304      0.334      0.216       0.83      0.304       0.33       0.22\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      16/50         0G      1.074      1.157        1.4      1.077         62   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.746      0.352      0.407      0.271      0.724      0.341      0.382      0.233\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      17/50         0G      1.001      0.888      1.346      1.055         18   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.702      0.358      0.427      0.264      0.647       0.33      0.382      0.224\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      18/50         0G      1.039      1.088      1.363      1.072          5   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.673      0.398      0.442       0.27      0.628      0.345      0.398      0.249\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      19/50         0G      1.053      1.018      1.391      1.074          1   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.763      0.366      0.456      0.288      0.751      0.352      0.421      0.254\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      20/50         0G     0.9848     0.9118      1.432       1.07          2   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.603      0.414      0.451        0.3      0.828      0.347      0.437      0.266\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      21/50         0G      1.067     0.9566      1.472      1.081          6   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.552      0.455      0.476      0.308      0.858      0.343      0.448      0.251\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      22/50         0G     0.9558     0.8759      1.339      1.045          2   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.669      0.449      0.496      0.333      0.707      0.439      0.489      0.293\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      23/50         0G      1.076     0.9897      1.451      1.092          7   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.684      0.432       0.51      0.323      0.688      0.426      0.481      0.297\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      24/50         0G     0.9077     0.8135      1.209      1.036          6   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.674      0.423      0.496      0.327      0.756      0.405      0.508      0.311\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      25/50         0G     0.8765     0.7651      1.287      1.034          4   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.732      0.432      0.534      0.343      0.814      0.415      0.529      0.319\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      26/50         0G     0.9173     0.8416      1.245      1.048          1   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176       0.76      0.432       0.54      0.352      0.751      0.428      0.515      0.311\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      27/50         0G     0.8665     0.7904      1.141      1.016          4   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.857      0.403       0.54      0.351      0.843      0.398      0.516      0.303\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      28/50         0G     0.8813      0.806      1.207      1.035          1   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.777      0.466      0.568       0.36       0.75      0.443      0.516      0.301\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      29/50         0G      0.882     0.7504      1.274      1.016         15   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.653      0.546       0.59      0.361      0.639      0.506       0.54      0.303\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      30/50         0G     0.9556     0.7381      1.278      1.054         65   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.667       0.58      0.616      0.374      0.681      0.523      0.546      0.316\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      31/50         0G      1.048     0.8497       1.27      1.064         16   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.705      0.568       0.61      0.379      0.738      0.511      0.555      0.312\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      32/50         0G      0.801     0.6248      1.169     0.9961         25   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.712      0.568      0.608      0.365      0.705      0.506      0.526      0.307\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      33/50         0G      0.994     0.9238       1.16      1.034         90   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.648      0.576      0.597       0.37      0.652       0.54      0.539      0.316\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      34/50         0G      0.854     0.7782      1.144      1.013          1   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176       0.68      0.557      0.606      0.379      0.627      0.517      0.523      0.315\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      35/50         0G       1.04     0.9663      1.291      1.048          1   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.696      0.551      0.615      0.378       0.62      0.494      0.518      0.309\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      36/50         0G     0.8128     0.5961       1.09      1.011          1   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.756        0.5      0.601      0.379      0.776      0.432      0.528      0.316\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      37/50         0G      0.858     0.6964      1.102      1.002          3   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.755      0.517      0.602      0.384      0.674      0.466      0.526       0.32\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      38/50         0G     0.8565     0.7285      1.115      1.004         10   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.756      0.511      0.589      0.378      0.667      0.478      0.534      0.317\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      39/50         0G     0.8148     0.8037      1.146      1.017         25   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.794      0.511      0.598       0.39      0.725      0.464      0.536      0.317\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      40/50         0G     0.8258     0.7309      1.077     0.9867          4   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.719      0.523      0.596      0.387      0.663      0.477      0.527      0.304\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      41/50         0G     0.8248     0.7792      1.082       1.02          4   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.707       0.54      0.592      0.386       0.65      0.475      0.526      0.304\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      42/50         0G     0.9149     0.8424      1.123       1.02         13   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.748      0.534      0.619       0.39      0.671      0.472      0.524      0.313\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      43/50         0G     0.8254     0.6628       1.06     0.9862          6   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.778      0.518       0.62      0.386      0.721      0.449      0.527      0.317\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      44/50         0G     0.7709     0.7114      1.059     0.9906         13   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.785      0.539      0.618      0.391      0.709      0.485       0.54      0.326\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      45/50         0G     0.8337      0.768      1.068     0.9854         17   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.758      0.551      0.625      0.395      0.718      0.507      0.551      0.333\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      46/50         0G     0.8209     0.8287     0.9739      0.989          2   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.704      0.568      0.615      0.396      0.681      0.528      0.556      0.336\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      47/50         0G     0.7749     0.7506      1.009     0.9828         35   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.707      0.557      0.608      0.381      0.683      0.502      0.539      0.318\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      48/50         0G     0.7551     0.7268      1.082     0.9719          1   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.733      0.551       0.61      0.386        0.7      0.516      0.555      0.331\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      49/50         0G     0.7404     0.6284      1.054     0.9876         16   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176       0.73       0.54      0.609      0.392      0.746      0.518       0.56      0.336\r\n",
      "\r\n",
      "      Epoch    GPU_mem   box_loss   seg_loss   cls_loss   dfl_loss  Instances       Size\r\n",
      "      50/50         0G     0.7298     0.6394     0.9992     0.9605          4   \r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176      0.763      0.511      0.607      0.395      0.749        0.5      0.552      0.339\r\n",
      "\r\n",
      "50 epochs completed in 0.389 hours.\r\n",
      "Optimizer stripped from runs/segment/train/weights/last.pt, 6.8MB\r\n",
      "Optimizer stripped from runs/segment/train/weights/best.pt, 6.8MB\r\n",
      "\r\n",
      "Validating runs/segment/train/weights/best.pt...\r\n",
      "Ultralytics YOLOv8.0.112 🚀 Python-3.10.10 torch-2.0.1 CPU\r\n",
      "YOLOv8n-seg summary (fused): 195 layers, 3258259 parameters, 0 gradients\r\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  m\r\n",
      "                   all         17        176       0.76      0.511      0.608      0.395      0.749        0.5      0.552       0.34\r\n",
      "Speed: 0.6ms preprocess, 63.4ms inference, 0.0ms loss, 5.8ms postprocess per image\r\n",
      "Results saved to \u001B[1mruns/segment/train\u001B[0m\r\n"
     ]
    }
   ],
   "source": [
    "# upload model\n",
    "from trainyolo.utils.yolov8 import upload_yolov8_run\n",
    "\n",
    "upload_yolov8_run(project, mode='segment', iou=0.45)\n"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-06-01T11:45:58.920922Z",
     "start_time": "2023-06-01T11:22:16.346788Z"
    }
   }
  }
 ],
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    "name": "ipython",
    "version": 2
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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