yolov8_training.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Ultralytics YOLOv8.0.196  Python-3.11.8 torch-2.3.0+cpu CPU (Intel Core(TM) i3-8130U 2.20GHz)\n",
      "Setup complete  (4 CPUs, 11.9 GB RAM, 34.8/931.4 GB disk)\n"
     ]
    }
   ],
   "source": [
    "# pip install ultralytics==8.0.196\n",
    "\n",
    "from IPython import display\n",
    "display.clear_output()\n",
    "\n",
    "import ultralytics\n",
    "ultralytics.checks()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n.pt to 'yolov8n.pt'...\n",
      "100%|██████████| 6.23M/6.23M [00:02<00:00, 2.98MB/s]\n"
     ]
    }
   ],
   "source": [
    "from ultralytics import YOLO\n",
    "\n",
    "# Load a model\n",
    "# model = YOLO('yolov8n.yaml')  # build a new model from scratch\n",
    "model = YOLO('yolov8n.pt')  # loading a pretrained model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "New https://pypi.org/project/ultralytics/8.2.11 available  Update with 'pip install -U ultralytics'\n",
      "Ultralytics YOLOv8.0.196  Python-3.11.8 torch-2.3.0+cpu CPU (Intel Core(TM) i3-8130U 2.20GHz)\n",
      "\u001b[34m\u001b[1mengine\\trainer: \u001b[0mtask=detect, mode=train, model=yolov8n.pt, data=AugmentedDatasetv8\\data.yaml, epochs=25, patience=50, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=None, 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, 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, stream_buffer=False, 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, tracker=botsort.yaml, save_dir=runs\\detect\\train3\n",
      "Downloading https://ultralytics.com/assets/Arial.ttf to 'C:\\Users\\afaqa\\AppData\\Roaming\\Ultralytics\\Arial.ttf'...\n",
      "100%|██████████| 755k/755k [00:00<00:00, 1.26MB/s]\n",
      "Overriding model.yaml nc=80 with nc=6\n",
      "\n",
      "                   from  n    params  module                                       arguments                     \n",
      "  0                  -1  1       464  ultralytics.nn.modules.conv.Conv             [3, 16, 3, 2]                 \n",
      "  1                  -1  1      4672  ultralytics.nn.modules.conv.Conv             [16, 32, 3, 2]                \n",
      "  2                  -1  1      7360  ultralytics.nn.modules.block.C2f             [32, 32, 1, True]             \n",
      "  3                  -1  1     18560  ultralytics.nn.modules.conv.Conv             [32, 64, 3, 2]                \n",
      "  4                  -1  2     49664  ultralytics.nn.modules.block.C2f             [64, 64, 2, True]             \n",
      "  5                  -1  1     73984  ultralytics.nn.modules.conv.Conv             [64, 128, 3, 2]               \n",
      "  6                  -1  2    197632  ultralytics.nn.modules.block.C2f             [128, 128, 2, True]           \n",
      "  7                  -1  1    295424  ultralytics.nn.modules.conv.Conv             [128, 256, 3, 2]              \n",
      "  8                  -1  1    460288  ultralytics.nn.modules.block.C2f             [256, 256, 1, True]           \n",
      "  9                  -1  1    164608  ultralytics.nn.modules.block.SPPF            [256, 256, 5]                 \n",
      " 10                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
      " 11             [-1, 6]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 12                  -1  1    148224  ultralytics.nn.modules.block.C2f             [384, 128, 1]                 \n",
      " 13                  -1  1         0  torch.nn.modules.upsampling.Upsample         [None, 2, 'nearest']          \n",
      " 14             [-1, 4]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 15                  -1  1     37248  ultralytics.nn.modules.block.C2f             [192, 64, 1]                  \n",
      " 16                  -1  1     36992  ultralytics.nn.modules.conv.Conv             [64, 64, 3, 2]                \n",
      " 17            [-1, 12]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 18                  -1  1    123648  ultralytics.nn.modules.block.C2f             [192, 128, 1]                 \n",
      " 19                  -1  1    147712  ultralytics.nn.modules.conv.Conv             [128, 128, 3, 2]              \n",
      " 20             [-1, 9]  1         0  ultralytics.nn.modules.conv.Concat           [1]                           \n",
      " 21                  -1  1    493056  ultralytics.nn.modules.block.C2f             [384, 256, 1]                 \n",
      " 22        [15, 18, 21]  1    752482  ultralytics.nn.modules.head.Detect           [6, [64, 128, 256]]           \n",
      "Model summary: 225 layers, 3012018 parameters, 3012002 gradients, 8.2 GFLOPs\n",
      "\n",
      "Transferred 319/355 items from pretrained weights\n",
      "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs\\detect\\train3', view at http://localhost:6006/\n",
      "Freezing layer 'model.22.dfl.conv.weight'\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mScanning D:\\FAST\\Semester 6\\Artificial Intelligence\\Project\\AugmentedDatasetv8\\train\\labels... 303 images, 0 backgrounds, 0 corrupt: 100%|██████████| 303/303 [00:02<00:00, 105.37it/s]\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: D:\\FAST\\Semester 6\\Artificial Intelligence\\Project\\AugmentedDatasetv8\\train\\labels.cache\n",
      "\u001b[34m\u001b[1mval: \u001b[0mScanning D:\\FAST\\Semester 6\\Artificial Intelligence\\Project\\AugmentedDatasetv8\\valid\\labels... 29 images, 0 backgrounds, 0 corrupt: 100%|██████████| 29/29 [00:00<00:00, 79.24it/s]\n",
      "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: D:\\FAST\\Semester 6\\Artificial Intelligence\\Project\\AugmentedDatasetv8\\valid\\labels.cache\n",
      "Plotting labels to runs\\detect\\train3\\labels.jpg... \n",
      "\u001b[34m\u001b[1moptimizer:\u001b[0m 'optimizer=auto' found, ignoring 'lr0=0.01' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... \n",
      "\u001b[34m\u001b[1moptimizer:\u001b[0m AdamW(lr=0.001, momentum=0.9) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)\n",
      "Image sizes 640 train, 640 val\n",
      "Using 0 dataloader workers\n",
      "Logging results to \u001b[1mruns\\detect\\train3\u001b[0m\n",
      "Starting training for 25 epochs...\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "       1/25         0G      1.123      3.267      1.519         49        640: 100%|██████████| 19/19 [06:25<00:00, 20.29s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:14<00:00, 14.23s/it]\n",
      "                   all         29         41      0.016          1      0.277       0.16\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "       2/25         0G      1.047      2.652       1.48         40        640: 100%|██████████| 19/19 [06:52<00:00, 21.71s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:24<00:00, 24.15s/it]\n",
      "                   all         29         41    0.00796      0.958      0.308        0.2\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "       3/25         0G      1.073      2.142      1.441         48        640: 100%|██████████| 19/19 [08:36<00:00, 27.17s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:12<00:00, 12.43s/it]\n",
      "                   all         29         41      0.763      0.167      0.442       0.27\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "       4/25         0G      1.052       1.85      1.414         46        640: 100%|██████████| 19/19 [05:28<00:00, 17.27s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:12<00:00, 12.20s/it]\n",
      "                   all         29         41       0.44      0.525      0.466      0.252\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "       5/25         0G      1.052      1.626      1.393         50        640: 100%|██████████| 19/19 [05:23<00:00, 17.01s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:13<00:00, 13.09s/it]\n",
      "                   all         29         41      0.735      0.393      0.667      0.308\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "       6/25         0G      1.062      1.639      1.403         38        640: 100%|██████████| 19/19 [04:40<00:00, 14.75s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:12<00:00, 12.18s/it]\n",
      "                   all         29         41      0.432      0.503      0.414      0.217\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "       7/25         0G      1.095      1.663      1.425         46        640: 100%|██████████| 19/19 [04:31<00:00, 14.31s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:11<00:00, 11.37s/it]\n",
      "                   all         29         41      0.587      0.478      0.442       0.24\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "       8/25         0G       1.01      1.444      1.403         46        640: 100%|██████████| 19/19 [05:19<00:00, 16.79s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:13<00:00, 13.76s/it]\n",
      "                   all         29         41      0.673      0.544      0.539      0.319\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "       9/25         0G       0.99      1.381      1.343         51        640: 100%|██████████| 19/19 [06:09<00:00, 19.44s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:16<00:00, 16.16s/it]\n",
      "                   all         29         41       0.55       0.68      0.601      0.365\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      10/25         0G      0.996      1.352      1.354         30        640: 100%|██████████| 19/19 [05:45<00:00, 18.16s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:12<00:00, 12.80s/it]\n",
      "                   all         29         41      0.692      0.685      0.741      0.515\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      11/25         0G      1.031      1.291      1.355         31        640: 100%|██████████| 19/19 [06:12<00:00, 19.58s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:12<00:00, 12.25s/it]\n",
      "                   all         29         41      0.583      0.787      0.768      0.531\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      12/25         0G     0.9933      1.212      1.348         46        640: 100%|██████████| 19/19 [04:24<00:00, 13.94s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:10<00:00, 10.51s/it]\n",
      "                   all         29         41      0.768      0.497      0.606      0.395\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      13/25         0G     0.9392       1.21      1.292         52        640: 100%|██████████| 19/19 [05:38<00:00, 17.82s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:12<00:00, 12.81s/it]\n",
      "                   all         29         41      0.787      0.627      0.755      0.459\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      14/25         0G     0.9458       1.18      1.308         49        640: 100%|██████████| 19/19 [05:12<00:00, 16.43s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:13<00:00, 13.73s/it]\n",
      "                   all         29         41      0.738      0.849      0.884      0.573\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      15/25         0G     0.9431      1.134      1.289         41        640: 100%|██████████| 19/19 [05:25<00:00, 17.11s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:11<00:00, 11.08s/it]\n",
      "                   all         29         41      0.805      0.587      0.695       0.46\n",
      "Closing dataloader mosaic\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      16/25         0G     0.8793      1.451      1.351         24        640: 100%|██████████| 19/19 [05:30<00:00, 17.37s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:13<00:00, 13.94s/it]\n",
      "                   all         29         41      0.677      0.737      0.767      0.492\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      17/25         0G     0.8118      1.322      1.322         20        640: 100%|██████████| 19/19 [05:05<00:00, 16.06s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:11<00:00, 11.66s/it]\n",
      "                   all         29         41      0.912      0.584      0.678      0.502\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      18/25         0G     0.7706      1.182      1.276         22        640: 100%|██████████| 19/19 [05:13<00:00, 16.48s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:13<00:00, 13.38s/it]\n",
      "                   all         29         41      0.895      0.628      0.735       0.53\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      19/25         0G     0.7405      1.113       1.27         21        640: 100%|██████████| 19/19 [05:28<00:00, 17.31s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:13<00:00, 13.07s/it]\n",
      "                   all         29         41      0.692      0.775      0.789      0.536\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      20/25         0G     0.7024      1.065      1.227         21        640: 100%|██████████| 19/19 [04:39<00:00, 14.69s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:11<00:00, 11.89s/it]\n",
      "                   all         29         41      0.836      0.591      0.692      0.504\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      21/25         0G     0.6789      1.009      1.209         19        640: 100%|██████████| 19/19 [04:27<00:00, 14.10s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:11<00:00, 11.32s/it]\n",
      "                   all         29         41      0.884      0.577      0.665      0.483\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      22/25         0G     0.6662     0.9937      1.178         17        640: 100%|██████████| 19/19 [04:18<00:00, 13.62s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:10<00:00, 10.80s/it]\n",
      "                   all         29         41      0.777      0.793      0.796      0.546\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      23/25         0G     0.6298     0.9337      1.129         22        640: 100%|██████████| 19/19 [04:26<00:00, 14.01s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:10<00:00, 10.73s/it]\n",
      "                   all         29         41      0.846      0.845      0.844      0.603\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      24/25         0G     0.6375     0.9596      1.158         19        640: 100%|██████████| 19/19 [04:34<00:00, 14.45s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:11<00:00, 11.62s/it]\n",
      "                   all         29         41      0.831      0.804       0.84        0.6\n",
      "\n",
      "      Epoch    GPU_mem   box_loss   cls_loss   dfl_loss  Instances       Size\n",
      "      25/25         0G     0.6174     0.9263      1.151         20        640: 100%|██████████| 19/19 [04:26<00:00, 14.04s/it]\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:11<00:00, 11.44s/it]\n",
      "                   all         29         41        0.8      0.845      0.826      0.594\n",
      "\n",
      "25 epochs completed in 2.336 hours.\n",
      "Optimizer stripped from runs\\detect\\train3\\weights\\last.pt, 6.3MB\n",
      "Optimizer stripped from runs\\detect\\train3\\weights\\best.pt, 6.2MB\n",
      "\n",
      "Validating runs\\detect\\train3\\weights\\best.pt...\n",
      "Ultralytics YOLOv8.0.196  Python-3.11.8 torch-2.3.0+cpu CPU (Intel Core(TM) i3-8130U 2.20GHz)\n",
      "Model summary (fused): 168 layers, 3006818 parameters, 0 gradients, 8.1 GFLOPs\n",
      "                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 1/1 [00:09<00:00,  9.74s/it]\n",
      "                   all         29         41      0.848      0.845      0.844      0.603\n",
      "                bottle         29         10          1      0.689      0.769      0.621\n",
      "              keychain         29          7      0.921          1      0.995      0.763\n",
      "              lunchbox         29          4      0.884       0.75      0.746      0.547\n",
      "            pencilcase         29          1      0.711          1      0.995      0.597\n",
      "              register         29          6      0.644      0.667      0.574      0.379\n",
      "             schoolbag         29         13      0.926      0.966      0.984      0.715\n",
      "Speed: 4.5ms preprocess, 305.4ms inference, 0.0ms loss, 12.6ms postprocess per image\n",
      "Results saved to \u001b[1mruns\\detect\\train3\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "# Training the model\n",
    "results = model.train(data='AugmentedDatasetv8\\data.yaml', epochs=100,batch=32)  # train the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "image 1/1 d:\\FAST\\Semester 6\\Artificial Intelligence\\Project\\test.jpeg: 640x640 1 bottle, 1 lunchbox, 1 register, 490.7ms\n",
      "Speed: 24.8ms preprocess, 490.7ms inference, 4.4ms postprocess per image at shape (1, 3, 640, 640)\n",
      "Results saved to \u001b[1mruns\\detect\\predict4\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "# Testing the model\n",
    "results = model('test.jpeg', save=True)  # predict on an image"
   ]
  }
 ],
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