Comet Logging and Visualization Integration (#9232)

* add comet to logger interface

* add comet logger

* add support for updated parameters

* clean up offline logger creation

* update callback args for comet logger

* add comet optimizer

* add optimizer config

* add comet README

* update tutorial notebook with Comet section

* add option to log class level metrics

* add support for class level metrics and confusion matrix

* handle errors when adding files to artifacts

* fix typo

* clean resume workflow

* updates for HPO

* update comet README

* fix typo in comet README

* update code snippets in comet README

* update comet links in tutorial

* updated links

* change optimizer batch size param and update comet README image

* update comet section in tutorial

* use prexisting cmd line flags to configure logger

* update artifact upload/download flow

* remove come remove comet logger specific cmd line args

* move downloading weights into comet logger code

* remove extra argparse

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* change checkpoint logging flow to follow offline logger

* update resume flow

* add comet logger to remote dataset property

* update cmd line args in hpo

* set types for integer/float env variables

* update README

* fix typo in README

* default to always logging model predictions

* Update tutorial.ipynb

* Update train.py

* Add Comet to Integrations table

* Update README.md

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

tutorial.ipynb

@@ -413,7 +413,7 @@
         "import utils\n",
         "display = utils.notebook_init()  # checks"
       ],
-      "execution_count": 1,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -465,7 +465,7 @@
         "!python detect.py --weights yolov5s.pt --img 640 --conf 0.25 --source data/images\n",
         "# display.Image(filename='runs/detect/exp/zidane.jpg', width=600)"
       ],
-      "execution_count": 2,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -535,7 +535,7 @@
         "torch.hub.download_url_to_file('https://ultralytics.com/assets/coco2017val.zip', 'tmp.zip')  # download (780M - 5000 images)\n",
         "!unzip -q tmp.zip -d ../datasets && rm tmp.zip  # unzip"
       ],
-      "execution_count": 3,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "display_data",
@@ -566,7 +566,7 @@
         "# Validate YOLOv5s on COCO val\n",
         "!python val.py --weights yolov5s.pt --data coco.yaml --img 640 --half"
       ],
-      "execution_count": 4,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -653,11 +653,14 @@
       "cell_type": "code",
       "source": [
         "#@title Select YOLOv5 🚀 logger {run: 'auto'}\n",
-        "logger = 'TensorBoard' #@param ['TensorBoard', 'ClearML', 'W&B']\n",
+        "logger = 'TensorBoard' #@param ['TensorBoard', 'Comet', 'ClearML', 'W&B']\n",
         "\n",
         "if logger == 'TensorBoard':\n",
         "  %load_ext tensorboard\n",
         "  %tensorboard --logdir runs/train\n",
+        "elif logger == 'Comet':\n",
+        "  %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",
@@ -683,7 +686,7 @@
         "# 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": 5,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "stream",
@@ -857,6 +860,28 @@
         "# 4. Visualize"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "## Comet Logging and Visualization 🌟 NEW\n",
+        "[Comet](https://www.comet.com/site/?ref=yolov5&utm_source=yolov5&utm_medium=affilliate&utm_campaign=yolov5_comet_integration) is now fully integrated with YOLOv5. Track and visualize model metrics in real time, save your hyperparameters, datasets, and model checkpoints, and visualize your model predictions with [Comet Custom Panels](https://www.comet.com/docs/v2/guides/comet-dashboard/code-panels/about-panels/?ref=yolov5&utm_source=yolov5&utm_medium=affilliate&utm_campaign=yolov5_comet_integration)! Comet makes sure you never lose track of your work and makes it easy to share results and collaborate across teams of all sizes! \n",
+        "\n",
+        "Getting started is easy:\n",
+        "```shell\n",
+        "pip install comet_ml  # 1. install\n",
+        "export COMET_API_KEY=<Your API Key>  # 2. paste API key\n",
+        "python train.py --img 640 --epochs 3 --data coco128.yaml --weights yolov5s.pt  # 3. train\n",
+        "```\n",
+        "\n",
+        "To learn more about all of the supported Comet features for this integration, check out the [Comet Tutorial](https://github.com/ultralytics/yolov5/tree/master/utils/loggers/comet). If you'd like to learn more about Comet, head over to our [documentation](https://www.comet.com/docs/v2/?ref=yolov5&utm_source=yolov5&utm_medium=affilliate&utm_campaign=yolov5_comet_integration). Get started by trying out the Comet Colab Notebook:\n",
+        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1RG0WOQyxlDlo5Km8GogJpIEJlg_5lyYO?usp=sharing)\n",
+        "\n",
+        "<img width=\"1920\" alt=\"yolo-ui\" src=\"https://user-images.githubusercontent.com/7529846/187608607-ff89c3d5-1b8b-4743-a974-9275301b0524.png\">"
+      ],
+      "metadata": {
+        "id": "nWOsI5wJR1o3"
+      }
+    },
     {
       "cell_type": "markdown",
       "source": [
@@ -1096,4 +1121,4 @@
       "outputs": []
     }
   ]
-}
+}