Created using Colaboratory

tutorial.ipynb

@@ -917,93 +917,23 @@
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
-        "outputId": "70004839-0c90-4bc0-c0e5-9a92f3e65b01"
+        "outputId": "c4dfc591-b6f9-4a60-9149-ee7eff970c90"
       },
       "source": [
         "# Train YOLOv5s on COCO128 for 3 epochs\n",
         "!python train.py --img 640 --batch 16 --epochs 3 --data coco128.yaml --weights yolov5s.pt --cache"
       ],
-      "execution_count": 4,
+      "execution_count": 9,
       "outputs": [
         {
           "output_type": "stream",
           "text": [
             "\u001b[34m\u001b[1mgithub: \u001b[0mup to date with https://github.com/ultralytics/yolov5 ✅\n",
-            "YOLOv5 🚀 v5.0-157-gc6b51f4 torch 1.8.1+cu101 CUDA:0 (Tesla V100-SXM2-16GB, 16160.5MB)\n",
-            "\n",
-            "Namespace(adam=False, artifact_alias='latest', batch_size=16, bbox_interval=-1, bucket='', cache_images=True, cfg='', data='./data/coco128.yaml', device='', entity=None, epochs=1, evolve=False, exist_ok=False, global_rank=-1, hyp='data/hyp.scratch.yaml', image_weights=False, img_size=[640, 640], label_smoothing=0.0, linear_lr=False, local_rank=-1, multi_scale=False, name='exp', noautoanchor=False, nosave=False, notest=False, project='runs/train', quad=False, rect=False, resume=False, save_dir='runs/train/exp', save_period=-1, single_cls=False, sync_bn=False, total_batch_size=16, upload_dataset=False, weights='yolov5s.pt', workers=8, world_size=1)\n",
-            "\u001b[34m\u001b[1mtensorboard: \u001b[0mStart with 'tensorboard --logdir runs/train', view at http://localhost:6006/\n",
-            "2021-06-08 16:52:25.719745: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n",
-            "\u001b[34m\u001b[1mhyperparameters: \u001b[0mlr0=0.01, lrf=0.2, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=0.05, cls=0.5, cls_pw=1.0, obj=1.0, obj_pw=1.0, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, 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\n",
-            "\u001b[34m\u001b[1mwandb: \u001b[0mInstall Weights & Biases for YOLOv5 logging with 'pip install wandb' (recommended)\n",
-            "Downloading https://github.com/ultralytics/yolov5/releases/download/v5.0/yolov5s.pt to yolov5s.pt...\n",
-            "100% 14.1M/14.1M [00:00<00:00, 18.7MB/s]\n",
-            "\n",
-            "\n",
-            "                 from  n    params  module                                  arguments                     \n",
-            "  0                -1  1      3520  models.common.Focus                     [3, 32, 3]                    \n",
-            "  1                -1  1     18560  models.common.Conv                      [32, 64, 3, 2]                \n",
-            "  2                -1  1     18816  models.common.C3                        [64, 64, 1]                   \n",
-            "  3                -1  1     73984  models.common.Conv                      [64, 128, 3, 2]               \n",
-            "  4                -1  1    156928  models.common.C3                        [128, 128, 3]                 \n",
-            "  5                -1  1    295424  models.common.Conv                      [128, 256, 3, 2]              \n",
-            "  6                -1  1    625152  models.common.C3                        [256, 256, 3]                 \n",
-            "  7                -1  1   1180672  models.common.Conv                      [256, 512, 3, 2]              \n",
-            "  8                -1  1    656896  models.common.SPP                       [512, 512, [5, 9, 13]]        \n",
-            "  9                -1  1   1182720  models.common.C3                        [512, 512, 1, False]          \n",
-            " 10                -1  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n",
-            " 11                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n",
-            " 12           [-1, 6]  1         0  models.common.Concat                    [1]                           \n",
-            " 13                -1  1    361984  models.common.C3                        [512, 256, 1, False]          \n",
-            " 14                -1  1     33024  models.common.Conv                      [256, 128, 1, 1]              \n",
-            " 15                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n",
-            " 16           [-1, 4]  1         0  models.common.Concat                    [1]                           \n",
-            " 17                -1  1     90880  models.common.C3                        [256, 128, 1, False]          \n",
-            " 18                -1  1    147712  models.common.Conv                      [128, 128, 3, 2]              \n",
-            " 19          [-1, 14]  1         0  models.common.Concat                    [1]                           \n",
-            " 20                -1  1    296448  models.common.C3                        [256, 256, 1, False]          \n",
-            " 21                -1  1    590336  models.common.Conv                      [256, 256, 3, 2]              \n",
-            " 22          [-1, 10]  1         0  models.common.Concat                    [1]                           \n",
-            " 23                -1  1   1182720  models.common.C3                        [512, 512, 1, False]          \n",
-            " 24      [17, 20, 23]  1    229245  models.yolo.Detect                      [80, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]\n",
-            "Model Summary: 283 layers, 7276605 parameters, 7276605 gradients, 17.1 GFLOPs\n",
-            "\n",
-            "Transferred 362/362 items from yolov5s.pt\n",
-            "\n",
-            "WARNING: Dataset not found, nonexistent paths: ['/content/coco128/images/train2017']\n",
-            "Downloading https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128.zip ...\n",
-            "100% 21.1M/21.1M [00:00<00:00, 68.2MB/s]\n",
-            "Dataset autodownload success\n",
-            "\n",
-            "Scaled weight_decay = 0.0005\n",
-            "Optimizer groups: 62 .bias, 62 conv.weight, 59 other\n",
-            "\u001b[34m\u001b[1mtrain: \u001b[0mScanning '../coco128/labels/train2017' images and labels...128 found, 0 missing, 2 empty, 0 corrupted: 100% 128/128 [00:00<00:00, 2036.51it/s]\n",
-            "\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: ../coco128/labels/train2017.cache\n",
-            "\u001b[34m\u001b[1mtrain: \u001b[0mCaching images (0.1GB): 100% 128/128 [00:00<00:00, 189.76it/s]\n",
-            "\u001b[34m\u001b[1mval: \u001b[0mScanning '../coco128/labels/train2017.cache' images and labels... 128 found, 0 missing, 2 empty, 0 corrupted: 100% 128/128 [00:00<00:00, 687414.74it/s]\n",
-            "\u001b[34m\u001b[1mval: \u001b[0mCaching images (0.1GB): 100% 128/128 [00:01<00:00, 93.37it/s]\n",
-            "Plotting labels... \n",
-            "\n",
-            "\u001b[34m\u001b[1mautoanchor: \u001b[0mAnalyzing anchors... anchors/target = 4.26, Best Possible Recall (BPR) = 0.9946\n",
-            "Image sizes 640 train, 640 test\n",
-            "Using 2 dataloader workers\n",
-            "Logging results to runs/train/exp\n",
-            "Starting training for 1 epochs...\n",
-            "\n",
-            "     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n",
-            "       0/0     10.8G   0.04226   0.06068   0.02005     0.123       158       640: 100% 8/8 [00:05<00:00,  1.35it/s]\n",
-            "               Class     Images     Labels          P          R     [email protected] [email protected]:.95: 100% 4/4 [00:06<00:00,  1.53s/it]\n",
-            "                 all        128        929      0.633      0.641      0.668      0.439\n",
-            "1 epochs completed in 0.005 hours.\n",
-            "\n",
-            "Optimizer stripped from runs/train/exp/weights/last.pt, 14.8MB\n",
-            "Optimizer stripped from runs/train/exp/weights/best.pt, 14.8MB\n",
-            "\u001b[34m\u001b[1mgithub: \u001b[0mup to date with https://github.com/ultralytics/yolov5 ✅\n",
-            "YOLOv5 🚀 v5.0-157-gc6b51f4 torch 1.8.1+cu101 CUDA:0 (Tesla V100-SXM2-16GB, 16160.5MB)\n",
+            "YOLOv5 🚀 v5.0-158-g78cf488 torch 1.8.1+cu101 CUDA:0 (Tesla V100-SXM2-16GB, 16160.5MB)\n",
             "\n",
             "Namespace(adam=False, artifact_alias='latest', batch_size=16, bbox_interval=-1, bucket='', cache_images=True, cfg='', data='./data/coco128.yaml', device='', entity=None, epochs=3, evolve=False, exist_ok=False, global_rank=-1, hyp='data/hyp.scratch.yaml', image_weights=False, img_size=[640, 640], label_smoothing=0.0, linear_lr=False, local_rank=-1, multi_scale=False, name='exp', noautoanchor=False, nosave=False, notest=False, project='runs/train', quad=False, rect=False, resume=False, save_dir='runs/train/exp', save_period=-1, single_cls=False, sync_bn=False, total_batch_size=16, upload_dataset=False, weights='yolov5s.pt', workers=8, world_size=1)\n",
             "\u001b[34m\u001b[1mtensorboard: \u001b[0mStart with 'tensorboard --logdir runs/train', view at http://localhost:6006/\n",
-            "2021-06-08 16:53:03.275914: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n",
+            "2021-06-08 17:00:55.016221: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0\n",
             "\u001b[34m\u001b[1mhyperparameters: \u001b[0mlr0=0.01, lrf=0.2, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=0.05, cls=0.5, cls_pw=1.0, obj=1.0, obj_pw=1.0, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, 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\n",
             "\u001b[34m\u001b[1mwandb: \u001b[0mInstall Weights & Biases for YOLOv5 logging with 'pip install wandb' (recommended)\n",
             "\n",
@@ -1038,10 +968,10 @@
             "Transferred 362/362 items from yolov5s.pt\n",
             "Scaled weight_decay = 0.0005\n",
             "Optimizer groups: 62 .bias, 62 conv.weight, 59 other\n",
-            "\u001b[34m\u001b[1mtrain: \u001b[0mScanning '../coco128/labels/train2017.cache' images and labels... 128 found, 0 missing, 2 empty, 0 corrupted: 100% 128/128 [00:00<00:00, 824686.50it/s]\n",
-            "\u001b[34m\u001b[1mtrain: \u001b[0mCaching images (0.1GB): 100% 128/128 [00:00<00:00, 201.90it/s]\n",
-            "\u001b[34m\u001b[1mval: \u001b[0mScanning '../coco128/labels/train2017.cache' images and labels... 128 found, 0 missing, 2 empty, 0 corrupted: 100% 128/128 [00:00<00:00, 23766.92it/s]\n",
-            "\u001b[34m\u001b[1mval: \u001b[0mCaching images (0.1GB): 100% 128/128 [00:01<00:00, 98.35it/s]\n",
+            "\u001b[34m\u001b[1mtrain: \u001b[0mScanning '../coco128/labels/train2017.cache' images and labels... 128 found, 0 missing, 2 empty, 0 corrupted: 100% 128/128 [00:00<00:00, 1503840.09it/s]\n",
+            "\u001b[34m\u001b[1mtrain: \u001b[0mCaching images (0.1GB): 100% 128/128 [00:00<00:00, 198.74it/s]\n",
+            "\u001b[34m\u001b[1mval: \u001b[0mScanning '../coco128/labels/train2017.cache' images and labels... 128 found, 0 missing, 2 empty, 0 corrupted: 100% 128/128 [00:00<00:00, 475107.00it/s]\n",
+            "\u001b[34m\u001b[1mval: \u001b[0mCaching images (0.1GB): 100% 128/128 [00:01<00:00, 98.63it/s]\n",
             "Plotting labels... \n",
             "\n",
             "\u001b[34m\u001b[1mautoanchor: \u001b[0mAnalyzing anchors... anchors/target = 4.26, Best Possible Recall (BPR) = 0.9946\n",
@@ -1051,19 +981,19 @@
             "Starting training for 3 epochs...\n",
             "\n",
             "     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n",
-            "       0/2     10.8G   0.04226   0.06067   0.02005     0.123       158       640: 100% 8/8 [00:05<00:00,  1.41it/s]\n",
-            "               Class     Images     Labels          P          R     [email protected] [email protected]:.95: 100% 4/4 [00:04<00:00,  1.21s/it]\n",
-            "                 all        128        929      0.633      0.641      0.668      0.439\n",
+            "       0/2     10.8G   0.04226   0.06067   0.02005     0.123       158       640: 100% 8/8 [00:05<00:00,  1.45it/s]\n",
+            "               Class     Images     Labels          P          R     [email protected] [email protected]:.95: 100% 4/4 [00:04<00:00,  1.17s/it]\n",
+            "                 all        128        929      0.633      0.641      0.668      0.438\n",
             "\n",
             "     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n",
-            "       1/2     8.29G   0.04571   0.06616   0.01952    0.1314       164       640: 100% 8/8 [00:01<00:00,  5.65it/s]\n",
-            "               Class     Images     Labels          P          R     [email protected] [email protected]:.95: 100% 4/4 [00:01<00:00,  3.21it/s]\n",
-            "                 all        128        929      0.613      0.659      0.669      0.438\n",
+            "       1/2     6.66G   0.04571   0.06615   0.01952    0.1314       164       640: 100% 8/8 [00:01<00:00,  5.10it/s]\n",
+            "               Class     Images     Labels          P          R     [email protected] [email protected]:.95: 100% 4/4 [00:01<00:00,  3.88it/s]\n",
+            "                 all        128        929      0.614      0.661       0.67      0.438\n",
             "\n",
             "     Epoch   gpu_mem       box       obj       cls     total    labels  img_size\n",
-            "       2/2     8.29G   0.04542    0.0718   0.01861    0.1358       191       640: 100% 8/8 [00:01<00:00,  4.89it/s]\n",
-            "               Class     Images     Labels          P          R     [email protected] [email protected]:.95: 100% 4/4 [00:02<00:00,  1.48it/s]\n",
-            "                 all        128        929      0.636      0.652       0.67       0.44\n",
+            "       2/2     6.66G   0.04542   0.07179   0.01861    0.1358       191       640: 100% 8/8 [00:01<00:00,  5.40it/s]\n",
+            "               Class     Images     Labels          P          R     [email protected] [email protected]:.95: 100% 4/4 [00:02<00:00,  1.43it/s]\n",
+            "                 all        128        929      0.636      0.652       0.67      0.439\n",
             "3 epochs completed in 0.007 hours.\n",
             "\n",
             "Optimizer stripped from runs/train/exp/weights/last.pt, 14.8MB\n",