diff --git a/README.md b/README.md index 8c19e52c45d7..8f45ccd229b5 100644 --- a/README.md +++ b/README.md @@ -155,7 +155,6 @@ python train.py --data coco.yaml --cfg yolov5n.yaml --weights '' --batch-size 12 - [Hyperparameter Evolution](https://github.com/ultralytics/yolov5/issues/607) - [Transfer Learning with Frozen Layers](https://github.com/ultralytics/yolov5/issues/1314) - [Architecture Summary](https://github.com/ultralytics/yolov5/issues/6998) 🌟 NEW -- [Weights & Biases Logging](https://github.com/ultralytics/yolov5/issues/1289) - [Roboflow for Datasets, Labeling, and Active Learning](https://github.com/ultralytics/yolov5/issues/4975)  🌟 NEW - [ClearML Logging](https://github.com/ultralytics/yolov5/tree/master/utils/loggers/clearml) 🌟 NEW - [Deci Platform](https://github.com/ultralytics/yolov5/wiki/Deci-Platform) 🌟 NEW @@ -171,23 +170,20 @@ python train.py --data coco.yaml --cfg yolov5n.yaml --weights '' --batch-size 12
- + - + - + - - -
-|Comet ⭐ NEW|Deci ⭐ NEW|ClearML ⭐ NEW|Roboflow|Weights & Biases -|:-:|:-:|:-:|:-:|:-:| -|Visualize model metrics and predictions and upload models and datasets in realtime with [Comet](https://bit.ly/yolov5-readme-comet)|Automatically compile and quantize YOLOv5 for better inference performance in one click at [Deci](https://bit.ly/yolov5-deci-platform)|Automatically track, visualize and even remotely train YOLOv5 using [ClearML](https://cutt.ly/yolov5-readme-clearml) (open-source!)|Label and export your custom datasets directly to YOLOv5 for training with [Roboflow](https://roboflow.com/?ref=ultralytics) |Automatically track and visualize all your YOLOv5 training runs in the cloud with [Weights & Biases](https://wandb.ai/site?utm_campaign=repo_yolo_readme) +|Comet ⭐ NEW|Deci ⭐ NEW|ClearML ⭐ NEW|Roboflow| +|:-:|:-:|:-:|:-:| +|Visualize model metrics and predictions and upload models and datasets in realtime with [Comet](https://bit.ly/yolov5-readme-comet)|Automatically compile and quantize YOLOv5 for better inference performance in one click at [Deci](https://bit.ly/yolov5-deci-platform)|Automatically track, visualize and even remotely train YOLOv5 using [ClearML](https://cutt.ly/yolov5-readme-clearml) (open-source!)|Label and export your custom datasets directly to YOLOv5 for training with [Roboflow](https://roboflow.com/?ref=ultralytics)| ##
Why YOLOv5
diff --git a/requirements.txt b/requirements.txt index 0436f415c642..52f7b9ea57d2 100644 --- a/requirements.txt +++ b/requirements.txt @@ -16,8 +16,8 @@ tqdm>=4.64.0 # Logging ------------------------------------- tensorboard>=2.4.1 -# wandb # clearml +# comet # Plotting ------------------------------------ pandas>=1.1.4 diff --git a/tutorial.ipynb b/tutorial.ipynb index 5d867fb36c93..63abebc5b37f 100644 --- a/tutorial.ipynb +++ b/tutorial.ipynb @@ -655,7 +655,7 @@ "cell_type": "code", "source": [ "#@title Select YOLOv5 🚀 logger {run: 'auto'}\n", - "logger = 'TensorBoard' #@param ['TensorBoard', 'Comet', 'ClearML', 'W&B']\n", + "logger = 'TensorBoard' #@param ['TensorBoard', 'Comet', 'ClearML']\n", "\n", "if logger == 'TensorBoard':\n", " %load_ext tensorboard\n", @@ -664,10 +664,7 @@ " %pip install -q comet_ml\n", " import comet_ml; comet_ml.init()\n", "elif logger == 'ClearML':\n", - " %pip install -q clearml && clearml-init\n", - "elif logger == 'W&B':\n", - " %pip install -q wandb\n", - " import wandb; wandb.login()" + " %pip install -q clearml && clearml-init" ], "metadata": { "id": "i3oKtE4g-aNn" @@ -699,7 +696,7 @@ "YOLOv5 🚀 v6.2-56-g30e674b Python-3.7.13 torch-1.12.1+cu113 CUDA:0 (Tesla V100-SXM2-16GB, 16160MiB)\n", "\n", "\u001b[34m\u001b[1mhyperparameters: \u001b[0mlr0=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=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, copy_paste=0.0\n", - "\u001b[34m\u001b[1mWeights & Biases: \u001b[0mrun 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases\n", + "\u001b[34m\u001b[1mComet: \u001b[0mrun 'pip install comet' to automatically track and visualize YOLOv5 🚀 runs with Comet\n", "\u001b[34m\u001b[1mClearML: \u001b[0mrun 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML\n", "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs/train', view at http://localhost:6006/\n", "\n", @@ -905,22 +902,6 @@ "id": "Lay2WsTjNJzP" } }, - { - "cell_type": "markdown", - "metadata": { - "id": "DLI1JmHU7B0l" - }, - "source": [ - "## Weights & Biases Logging\n", - "\n", - "[Weights & Biases](https://wandb.ai/site?utm_campaign=repo_yolo_notebook) (W&B) is integrated with YOLOv5 for real-time visualization and cloud logging of training runs. This allows for better run comparison and introspection, as well improved visibility and collaboration for teams. To enable W&B `pip install wandb`, and then train normally (you will be guided through setup on first use). \n", - "\n", - "During training you will see live updates at [https://wandb.ai/home](https://wandb.ai/home?utm_campaign=repo_yolo_notebook), and you can create and share detailed [Reports](https://wandb.ai/glenn-jocher/yolov5_tutorial/reports/YOLOv5-COCO128-Tutorial-Results--VmlldzozMDI5OTY) of your results. For more information see the [YOLOv5 Weights & Biases Tutorial](https://github.com/ultralytics/yolov5/issues/1289). \n", - "\n", - "\n", - "\"Weights" - ] - }, { "cell_type": "markdown", "metadata": { diff --git a/utils/docker/Dockerfile b/utils/docker/Dockerfile index 9b93fad7b203..be5c2fb71517 100644 --- a/utils/docker/Dockerfile +++ b/utils/docker/Dockerfile @@ -16,7 +16,7 @@ RUN apt update && apt install --no-install-recommends -y zip htop screen libgl1- COPY requirements.txt . RUN python -m pip install --upgrade pip wheel RUN pip uninstall -y Pillow torchtext torch torchvision -RUN pip install --no-cache -r requirements.txt albumentations wandb gsutil notebook Pillow>=9.1.0 \ +RUN pip install --no-cache -r requirements.txt albumentations comet clearml gsutil notebook Pillow>=9.1.0 \ 'opencv-python<4.6.0.66' \ --extra-index-url https://download.pytorch.org/whl/cu113 diff --git a/utils/loggers/__init__.py b/utils/loggers/__init__.py index 941d09e19e2d..bc8dd7621579 100644 --- a/utils/loggers/__init__.py +++ b/utils/loggers/__init__.py @@ -84,10 +84,10 @@ def __init__(self, save_dir=None, weights=None, opt=None, hyp=None, logger=None, self.csv = True # always log to csv # Messages - if not wandb: - prefix = colorstr('Weights & Biases: ') - s = f"{prefix}run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases" - self.logger.info(s) + # if not wandb: + # prefix = colorstr('Weights & Biases: ') + # s = f"{prefix}run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases" + # self.logger.info(s) if not clearml: prefix = colorstr('ClearML: ') s = f"{prefix}run 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML" @@ -110,9 +110,9 @@ def __init__(self, save_dir=None, weights=None, opt=None, hyp=None, logger=None, self.opt.hyp = self.hyp # add hyperparameters self.wandb = WandbLogger(self.opt, run_id) # temp warn. because nested artifacts not supported after 0.12.10 - if pkg.parse_version(wandb.__version__) >= pkg.parse_version('0.12.11'): - s = "YOLOv5 temporarily requires wandb version 0.12.10 or below. Some features may not work as expected." - self.logger.warning(s) + # if pkg.parse_version(wandb.__version__) >= pkg.parse_version('0.12.11'): + # s = "YOLOv5 temporarily requires wandb version 0.12.10 or below. Some features may not work as expected." + # self.logger.warning(s) else: self.wandb = None diff --git a/utils/loggers/wandb/wandb_utils.py b/utils/loggers/wandb/wandb_utils.py index d2dd0fa7c6cd..238f4edbf2a0 100644 --- a/utils/loggers/wandb/wandb_utils.py +++ b/utils/loggers/wandb/wandb_utils.py @@ -135,7 +135,7 @@ def __init__(self, opt, run_id=None, job_type='Training'): # Temporary-fix if opt.upload_dataset: opt.upload_dataset = False - LOGGER.info("Uploading Dataset functionality is not being supported temporarily due to a bug.") + # LOGGER.info("Uploading Dataset functionality is not being supported temporarily due to a bug.") # Pre-training routine -- self.job_type = job_type