[Misc] rename char classifiation scripts and dependency pin

.conda/meta.yaml

@@ -32,13 +32,13 @@ requirements:
     - shapely >=1.6.0, <3.0.0
     - langdetect >=1.0.9, <2.0.0
     - rapidfuzz >=3.0.0, <4.0.0
+    - huggingface_hub >=0.20.0, <1.0.0
     - matplotlib >=3.1.0
     - weasyprint >=55.0
     - defusedxml >=0.7.0
     - mplcursors >=0.3
     - unidecode >=1.0.0
     - tqdm >=4.30.0
-    - huggingface_hub >=0.20.0
 
 about:
   home: {{ urls.get('repository') }}

.github/workflows/references.yml

@@ -54,10 +54,10 @@ jobs:
           sudo apt-get update && sudo apt-get install fonts-freefont-ttf -y
       - if: matrix.framework == 'tensorflow'
         name: Train for a short epoch (TF)
-        run: python references/classification/train_tensorflow.py vit_s -b 32 --val-samples 1 --train-samples 1 --epochs 1
+        run: python references/classification/train_tensorflow_character.py vit_s -b 32 --val-samples 1 --train-samples 1 --epochs 1
       - if: matrix.framework == 'pytorch'
         name: Train for a short epoch (PT)
-        run: python references/classification/train_pytorch.py vit_s -b 32 --val-samples 1 --train-samples 1 --epochs 1
+        run: python references/classification/train_pytorch_character.py vit_s -b 32 --val-samples 1 --train-samples 1 --epochs 1
 
   train-orientation-classification:
     runs-on: ${{ matrix.os }}

api/pyproject.toml

@@ -11,7 +11,7 @@ license = "Apache-2.0"
 
 [tool.poetry.dependencies]
 python = ">=3.8.2,<3.11"  # pypdfium2 needs a python version above 3.8.2
-tensorflow = ">=2.11.0,<3.0.0"
+tensorflow = ">=2.11.0,<2.16.0"  # cf. https://github.com/mindee/doctr/pull/1461
 python-doctr = {git = "https://github.com/mindee/doctr.git", extras = ['tf'], branch = "main" }
 # Fastapi: minimum version required to avoid pydantic error
 # cf. https://github.com/tiangolo/fastapi/issues/4168

doctr/models/detection/differentiable_binarization/pytorch.py

@@ -57,28 +57,24 @@ def __init__(
 
         conv_layer = DeformConv2d if deform_conv else nn.Conv2d
 
-        self.in_branches = nn.ModuleList(
-            [
-                nn.Sequential(
-                    conv_layer(chans, out_channels, 1, bias=False),
-                    nn.BatchNorm2d(out_channels),
-                    nn.ReLU(inplace=True),
-                )
-                for idx, chans in enumerate(in_channels)
-            ]
-        )
+        self.in_branches = nn.ModuleList([
+            nn.Sequential(
+                conv_layer(chans, out_channels, 1, bias=False),
+                nn.BatchNorm2d(out_channels),
+                nn.ReLU(inplace=True),
+            )
+            for idx, chans in enumerate(in_channels)
+        ])
         self.upsample = nn.Upsample(scale_factor=2, mode="bilinear", align_corners=True)
-        self.out_branches = nn.ModuleList(
-            [
-                nn.Sequential(
-                    conv_layer(out_channels, out_chans, 3, padding=1, bias=False),
-                    nn.BatchNorm2d(out_chans),
-                    nn.ReLU(inplace=True),
-                    nn.Upsample(scale_factor=2**idx, mode="bilinear", align_corners=True),
-                )
-                for idx, chans in enumerate(in_channels)
-            ]
-        )
+        self.out_branches = nn.ModuleList([
+            nn.Sequential(
+                conv_layer(out_channels, out_chans, 3, padding=1, bias=False),
+                nn.BatchNorm2d(out_chans),
+                nn.ReLU(inplace=True),
+                nn.Upsample(scale_factor=2**idx, mode="bilinear", align_corners=True),
+            )
+            for idx, chans in enumerate(in_channels)
+        ])
 
     def forward(self, x: List[torch.Tensor]) -> torch.Tensor:
         if len(x) != len(self.out_branches):

pyproject.toml

@@ -44,19 +44,21 @@ dependencies = [
     "shapely>=1.6.0,<3.0.0",
     "langdetect>=1.0.9,<2.0.0",
     "rapidfuzz>=3.0.0,<4.0.0",
+    "huggingface-hub>=0.20.0,<1.0.0",
     "matplotlib>=3.1.0",
     "weasyprint>=55.0",
     "Pillow>=9.2.0",
     "defusedxml>=0.7.0",
     "mplcursors>=0.3",
     "unidecode>=1.0.0",
     "tqdm>=4.30.0",
-    "huggingface-hub>=0.20.0",
 ]
 
 [project.optional-dependencies]
 tf = [
-    "tensorflow>=2.11.0,<3.0.0",  # cf. https://github.com/mindee/doctr/pull/1182
+    # cf. https://github.com/mindee/doctr/pull/1182
+    # cf. https://github.com/mindee/doctr/pull/1461
+    "tensorflow>=2.11.0,<2.16.0",
     "tf2onnx>=1.16.0,<2.0.0",  # cf. https://github.com/onnx/tensorflow-onnx/releases/tag/v1.16.0
 ]
 torch = [
@@ -89,7 +91,9 @@ docs = [
 ]
 dev = [
     # Tensorflow
-    "tensorflow>=2.11.0,<3.0.0",  # cf. https://github.com/mindee/doctr/pull/1182
+    # cf. https://github.com/mindee/doctr/pull/1182
+    # cf. https://github.com/mindee/doctr/pull/1461
+    "tensorflow>=2.11.0,<2.16.0",
     "tf2onnx>=1.16.0,<2.0.0",  # cf. https://github.com/onnx/tensorflow-onnx/releases/tag/v1.16.0
     # PyTorch
     "torch>=1.12.0,<3.0.0",

references/classification/README.md

@@ -16,13 +16,13 @@ pip install -r references/requirements.txt
 You can start your training in TensorFlow:
 
 ```shell
-python references/classification/train_tensorflow.py mobilenet_v3_large --epochs 5
+python references/classification/train_tensorflow_character.py mobilenet_v3_large --epochs 5
 ```
 
 or PyTorch:
 
 ```shell
-python references/classification/train_pytorch.py mobilenet_v3_large --epochs 5 --device 0
+python references/classification/train_pytorch_character.py mobilenet_v3_large --epochs 5 --device 0
 ```
 
 ## Usage orientation classification
@@ -61,7 +61,7 @@ Feel free to inspect the multiple script option to customize your training to yo
 Character classification:
 
 ```python
-python references/classification/train_tensorflow.py --help
+python references/classification/train_tensorflow_character.py --help
 ```
 
 Orientation classification: