feat: ✨ tqdm slack (#1837)

* feat: ✨ tqdm slack

* fix

* docs: ✏️ update README.md

references/classification/README.md

@@ -54,6 +54,16 @@ Each path must lead to a folder where the images are stored. For example:
     └── ...
 ```
 
+## Slack Logging with tqdm
+
+To enable Slack logging using `tqdm`, you need to set the following environment variables:
+
+- `TQDM_SLACK_TOKEN`: the Slack Bot Token
+- `TQDM_SLACK_CHANNEL`: you can retrieve it using `Right Click on Channel > Copy > Copy link`. You should get something like `https://xxxxxx.slack.com/archives/yyyyyyyy`. Keep only the `yyyyyyyy` part.
+
+You can follow this page on [how to create a Slack App](https://api.slack.com/quickstart).
+
+
 ## Advanced options
 
 Feel free to inspect the multiple script option to customize your training to your own needs!

references/classification/train_pytorch_character.py

@@ -27,7 +27,11 @@
     RandomPhotometricDistort,
     RandomRotation,
 )
-from tqdm.auto import tqdm
+
+if os.getenv("TQDM_SLACK_TOKEN") and os.getenv("TQDM_SLACK_CHANNEL"):
+    from tqdm.contrib.slack import tqdm
+else:
+    from tqdm.auto import tqdm
 
 from doctr import transforms as T
 from doctr.datasets import VOCABS, CharacterGenerator

references/classification/train_pytorch_orientation.py

@@ -26,7 +26,11 @@
     RandomPerspective,
     RandomPhotometricDistort,
 )
-from tqdm.auto import tqdm
+
+if os.getenv("TQDM_SLACK_TOKEN") and os.getenv("TQDM_SLACK_CHANNEL"):
+    from tqdm.contrib.slack import tqdm
+else:
+    from tqdm.auto import tqdm
 
 from doctr import transforms as T
 from doctr.datasets import OrientationDataset

references/classification/train_tensorflow_character.py

@@ -19,7 +19,11 @@
 import numpy as np
 import tensorflow as tf
 from tensorflow.keras import Model, mixed_precision, optimizers
-from tqdm.auto import tqdm
+
+if os.getenv("TQDM_SLACK_TOKEN") and os.getenv("TQDM_SLACK_CHANNEL"):
+    from tqdm.contrib.slack import tqdm
+else:
+    from tqdm.auto import tqdm
 
 from doctr.models import login_to_hub, push_to_hf_hub
 

references/classification/train_tensorflow_orientation.py

@@ -19,7 +19,11 @@
 import numpy as np
 import tensorflow as tf
 from tensorflow.keras import Model, mixed_precision, optimizers
-from tqdm.auto import tqdm
+
+if os.getenv("TQDM_SLACK_TOKEN") and os.getenv("TQDM_SLACK_CHANNEL"):
+    from tqdm.contrib.slack import tqdm
+else:
+    from tqdm.auto import tqdm
 
 from doctr.models import login_to_hub, push_to_hf_hub
 

references/detection/README.md

@@ -107,6 +107,15 @@ labels.json
 }
 ```
 
+## Slack Logging with tqdm
+
+To enable Slack logging using `tqdm`, you need to set the following environment variables:
+
+- `TQDM_SLACK_TOKEN`: the Slack Bot Token
+- `TQDM_SLACK_CHANNEL`: you can retrieve it using `Right Click on Channel > Copy > Copy link`. You should get something like `https://xxxxxx.slack.com/archives/yyyyyyyy`. Keep only the `yyyyyyyy` part.
+
+You can follow this page on [how to create a Slack App](https://api.slack.com/quickstart).
+
 ## Advanced options
 
 Feel free to inspect the multiple script option to customize your training to your own needs!

references/detection/evaluate_pytorch.py

@@ -17,7 +17,11 @@
 import torch
 from torch.utils.data import DataLoader, SequentialSampler
 from torchvision.transforms import Normalize
-from tqdm import tqdm
+
+if os.getenv("TQDM_SLACK_TOKEN") and os.getenv("TQDM_SLACK_CHANNEL"):
+    from tqdm.contrib.slack import tqdm
+else:
+    from tqdm.auto import tqdm
 
 from doctr import datasets
 from doctr import transforms as T

references/detection/evaluate_tensorflow.py

@@ -19,7 +19,11 @@
 
 import tensorflow as tf
 from tensorflow.keras import mixed_precision
-from tqdm import tqdm
+
+if os.getenv("TQDM_SLACK_TOKEN") and os.getenv("TQDM_SLACK_CHANNEL"):
+    from tqdm.contrib.slack import tqdm
+else:
+    from tqdm.auto import tqdm
 
 gpu_devices = tf.config.list_physical_devices("GPU")
 if any(gpu_devices):

references/detection/train_pytorch.py

@@ -19,7 +19,11 @@
 from torch.optim.lr_scheduler import CosineAnnealingLR, MultiplicativeLR, OneCycleLR, PolynomialLR
 from torch.utils.data import DataLoader, RandomSampler, SequentialSampler
 from torchvision.transforms.v2 import Compose, Normalize, RandomGrayscale, RandomPhotometricDistort
-from tqdm.auto import tqdm
+
+if os.getenv("TQDM_SLACK_TOKEN") and os.getenv("TQDM_SLACK_CHANNEL"):
+    from tqdm.contrib.slack import tqdm
+else:
+    from tqdm.auto import tqdm
 
 from doctr import transforms as T
 from doctr.datasets import DetectionDataset

references/detection/train_pytorch_ddp.py

@@ -25,7 +25,11 @@
 from torch.utils.data import DataLoader, SequentialSampler
 from torch.utils.data.distributed import DistributedSampler
 from torchvision.transforms.v2 import Compose, Normalize, RandomGrayscale, RandomPhotometricDistort
-from tqdm.auto import tqdm
+
+if os.getenv("TQDM_SLACK_TOKEN") and os.getenv("TQDM_SLACK_CHANNEL"):
+    from tqdm.contrib.slack import tqdm
+else:
+    from tqdm.auto import tqdm
 
 from doctr import transforms as T
 from doctr.datasets import DetectionDataset

references/detection/train_tensorflow.py

@@ -20,7 +20,11 @@
 import numpy as np
 import tensorflow as tf
 from tensorflow.keras import Model, mixed_precision, optimizers
-from tqdm.auto import tqdm
+
+if os.getenv("TQDM_SLACK_TOKEN") and os.getenv("TQDM_SLACK_CHANNEL"):
+    from tqdm.contrib.slack import tqdm
+else:
+    from tqdm.auto import tqdm
 
 from doctr.models import login_to_hub, push_to_hf_hub
 

references/recognition/README.md

@@ -77,6 +77,16 @@ The order of entries in the json does not matter.
 
 When typing your labels, be aware that the VOCAB doesn't handle spaces. Also make sure your `labels.json` file is using UTF-8 encoding.
 
+## Slack Logging with tqdm
+
+To enable Slack logging using `tqdm`, you need to set the following environment variables:
+
+- `TQDM_SLACK_TOKEN`: the Slack Bot Token
+- `TQDM_SLACK_CHANNEL`: you can retrieve it using `Right Click on Channel > Copy > Copy link`. You should get something like `https://xxxxxx.slack.com/archives/yyyyyyyy`. Keep only the `yyyyyyyy` part.
+
+You can follow this page on [how to create a Slack App](https://api.slack.com/quickstart).
+
+
 ## Advanced options
 
 Feel free to inspect the multiple script option to customize your training to your own needs!

references/recognition/train_pytorch.py

@@ -25,7 +25,11 @@
     RandomPerspective,
     RandomPhotometricDistort,
 )
-from tqdm.auto import tqdm
+
+if os.getenv("TQDM_SLACK_TOKEN") and os.getenv("TQDM_SLACK_CHANNEL"):
+    from tqdm.contrib.slack import tqdm
+else:
+    from tqdm.auto import tqdm
 
 from doctr import transforms as T
 from doctr.datasets import VOCABS, RecognitionDataset, WordGenerator

references/recognition/train_pytorch_ddp.py

@@ -29,7 +29,11 @@
     RandomPerspective,
     RandomPhotometricDistort,
 )
-from tqdm.auto import tqdm
+
+if os.getenv("TQDM_SLACK_TOKEN") and os.getenv("TQDM_SLACK_CHANNEL"):
+    from tqdm.contrib.slack import tqdm
+else:
+    from tqdm.auto import tqdm
 
 from doctr import transforms as T
 from doctr.datasets import VOCABS, RecognitionDataset, WordGenerator

references/recognition/train_tensorflow.py

@@ -20,7 +20,11 @@
 import numpy as np
 import tensorflow as tf
 from tensorflow.keras import Model, mixed_precision, optimizers
-from tqdm.auto import tqdm
+
+if os.getenv("TQDM_SLACK_TOKEN") and os.getenv("TQDM_SLACK_CHANNEL"):
+    from tqdm.contrib.slack import tqdm
+else:
+    from tqdm.auto import tqdm
 
 from doctr.models import login_to_hub, push_to_hf_hub
 

references/requirements.txt

@@ -1,5 +1,6 @@
 -e .
 tqdm
+slack-sdk
 wandb>=0.10.31
 clearml>=1.11.1
 matplotlib>=3.1.0