diff --git a/tutorial.ipynb b/tutorial.ipynb index 4429c1044cfe..b6d672d10e52 100644 --- a/tutorial.ipynb +++ b/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 mAP@.5 mAP@.5:.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 mAP@.5 mAP@.5:.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 mAP@.5 mAP@.5:.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 mAP@.5 mAP@.5:.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 mAP@.5 mAP@.5:.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 mAP@.5 mAP@.5:.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 mAP@.5 mAP@.5:.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",