Update Loggers (#9760)

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
 <div align="center">
   <a href="https://bit.ly/yolov5-readme-comet">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-comet.png" width="10%" /></a>
-  <img src="https://github.com/ultralytics/assets/raw/master/social/logo-transparent.png" width="9%" height="0" alt="" />
+  <img src="https://github.com/ultralytics/assets/raw/master/social/logo-transparent.png" width="15%" height="0" alt="" />
   <a href="https://bit.ly/yolov5-deci-platform">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-deci.png" width="10%" /></a>
-  <img src="https://github.com/ultralytics/assets/raw/master/social/logo-transparent.png" width="9%" height="0" alt="" />
+  <img src="https://github.com/ultralytics/assets/raw/master/social/logo-transparent.png" width="15%" height="0" alt="" />
   <a href="https://cutt.ly/yolov5-readme-clearml">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-clearml.png" width="10%" /></a>
-  <img src="https://github.com/ultralytics/assets/raw/master/social/logo-transparent.png" width="9%" height="0" alt="" />
+  <img src="https://github.com/ultralytics/assets/raw/master/social/logo-transparent.png" width="15%" height="0" alt="" />
   <a href="https://roboflow.com/?ref=ultralytics">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-roboflow.png" width="10%" /></a>
-  <img src="https://github.com/ultralytics/assets/raw/master/social/logo-transparent.png" width="9%" height="0" alt="" />
-  <a href="https://wandb.ai/site?utm_campaign=repo_yolo_readme">
-    <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-wb.png" width="10%" /></a>
 </div>
 
-|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)|
 
 
 ## <div align="center">Why YOLOv5</div>

requirements.txt

@@ -16,8 +16,8 @@ tqdm>=4.64.0
 
 # Logging -------------------------------------
 tensorboard>=2.4.1
-# wandb
 # clearml
+# comet
 
 # Plotting ------------------------------------
 pandas>=1.1.4

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",
-        "<a href=\"https://wandb.ai/glenn-jocher/yolov5_tutorial\">\n",
-        "<img alt=\"Weights & Biases dashboard\" src=\"https://user-images.githubusercontent.com/26833433/182482859-288a9622-4661-48db-99de-650d1dead5c6.jpg\" width=\"1280\"/></a>"
-      ]
-    },
     {
       "cell_type": "markdown",
       "metadata": {

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
 

utils/loggers/__init__.py

@@ -84,10 +84,10 @@ class Loggers():
         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 @@ class Loggers():
             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
 

utils/loggers/wandb/wandb_utils.py

@@ -135,7 +135,7 @@ class WandbLogger():
         # 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