diff --git a/.conda/meta.yaml b/.conda/meta.yaml
index 5eb28efa9c..f194539df1 100644
--- a/.conda/meta.yaml
+++ b/.conda/meta.yaml
@@ -24,7 +24,6 @@ requirements:
     - numpy >=1.16.0, <2.0.0
     - scipy >=1.4.0, <2.0.0
     - pillow >=9.2.0
-    - matplotlib >=3.1.0
     - h5py >=3.1.0, <4.0.0
     - opencv >=4.5.0, <5.0.0
     - pypdfium2-team::pypdfium2_helpers >=4.0.0, <5.0.0
@@ -33,10 +32,7 @@ requirements:
     - 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
     - anyascii >=0.3.2
     - tqdm >=4.30.0
 
diff --git a/.github/workflows/builds.yml b/.github/workflows/builds.yml
index 8f45a8ad2c..725579f373 100644
--- a/.github/workflows/builds.yml
+++ b/.github/workflows/builds.yml
@@ -41,12 +41,12 @@ jobs:
         name: Install package (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
       - if: matrix.framework == 'pytorch'
         name: Install package (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
       - name: Import package
         run: python -c "import doctr; print(doctr.__version__)"
 
diff --git a/.github/workflows/demo.yml b/.github/workflows/demo.yml
index d62c7d79e0..0fc7f203ff 100644
--- a/.github/workflows/demo.yml
+++ b/.github/workflows/demo.yml
@@ -42,13 +42,13 @@ jobs:
         name: Install dependencies (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
           pip install -r demo/tf-requirements.txt
       - if: matrix.framework == 'pytorch'
         name: Install dependencies (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
           pip install -r demo/pt-requirements.txt
 
       - if: matrix.framework == 'tensorflow'
diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
index 8efd563559..79965b560c 100644
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -27,7 +27,7 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf]
+          pip install -e .[tf,viz,html]
           pip install -e .[docs]
 
       - name: Build documentation
diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index ecfb6a0e3a..c7c5120ef9 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -28,7 +28,7 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
           pip install -e .[testing]
       - name: Run unittests
         run: |
@@ -61,7 +61,7 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
           pip install -e .[testing]
       - name: Run unittests
         run: |
@@ -94,7 +94,7 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
           pip install -e .[testing]
 
       - name: Run unittests
diff --git a/.github/workflows/public_docker_images.yml b/.github/workflows/public_docker_images.yml
index 61a974e8fa..bf1cb4ea38 100644
--- a/.github/workflows/public_docker_images.yml
+++ b/.github/workflows/public_docker_images.yml
@@ -23,7 +23,7 @@ jobs:
       matrix:
         # Must match version at https://www.python.org/ftp/python/
         python: ["3.9.18", "3.10.13", "3.11.8"]
-        framework: ["tf", "torch"]
+        framework: ["tf", "torch", "tf,viz,html", "torch,viz,html"]
         system: ["cpu", "gpu"]
 
     # Sets the permissions granted to the `GITHUB_TOKEN` for the actions in this job.
diff --git a/.github/workflows/pull_requests.yml b/.github/workflows/pull_requests.yml
index 87baef1616..045c4676f6 100644
--- a/.github/workflows/pull_requests.yml
+++ b/.github/workflows/pull_requests.yml
@@ -22,7 +22,7 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
           pip install -e .[docs]
 
       - name: Build documentation
diff --git a/.github/workflows/references.yml b/.github/workflows/references.yml
index e9f7bd54dc..b579c79e9c 100644
--- a/.github/workflows/references.yml
+++ b/.github/workflows/references.yml
@@ -42,14 +42,14 @@ jobs:
         name: Install dependencies (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
           pip install -r references/requirements.txt
           sudo apt-get update && sudo apt-get install fonts-freefont-ttf -y
       - if: matrix.framework == 'pytorch'
         name: Install dependencies (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
           pip install -r references/requirements.txt
           sudo apt-get update && sudo apt-get install fonts-freefont-ttf -y
       - if: matrix.framework == 'tensorflow'
@@ -94,13 +94,13 @@ jobs:
         name: Install dependencies (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
           pip install -r references/requirements.txt
       - if: matrix.framework == 'pytorch'
         name: Install dependencies (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
           pip install -r references/requirements.txt
       - name: Download and extract detection toy set
         run: |
@@ -160,13 +160,13 @@ jobs:
         name: Install dependencies (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
           pip install -r references/requirements.txt
       - if: matrix.framework == 'pytorch'
         name: Install dependencies (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
           pip install -r references/requirements.txt
       - name: Download and extract toy set
         run: |
@@ -211,12 +211,12 @@ jobs:
         name: Install dependencies (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
       - if: matrix.framework == 'pytorch'
         name: Install dependencies (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
       - if: matrix.framework == 'tensorflow'
         name: Evaluate text recognition (TF)
         run: python references/recognition/evaluate_tensorflow.py crnn_mobilenet_v3_small --dataset IIIT5K -b 32
@@ -255,12 +255,12 @@ jobs:
         name: Install dependencies (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
       - if: matrix.framework == 'pytorch'
         name: Install dependencies (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
       - if: matrix.framework == 'tensorflow'
         name: Benchmark latency (TF)
         run: python references/recognition/latency_tensorflow.py crnn_mobilenet_v3_small --it 5
@@ -303,13 +303,13 @@ jobs:
         name: Install dependencies (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
           pip install -r references/requirements.txt
       - if: matrix.framework == 'pytorch'
         name: Install dependencies (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
           pip install -r references/requirements.txt
       - name: Download and extract toy set
         run: |
@@ -354,13 +354,13 @@ jobs:
         name: Install dependencies (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
           pip install -r references/requirements.txt
       - if: matrix.framework == 'pytorch'
         name: Install dependencies (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
           pip install -r references/requirements.txt
       - if: matrix.framework == 'tensorflow'
         name: Evaluate text detection (TF)
@@ -400,12 +400,12 @@ jobs:
         name: Install dependencies (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
       - if: matrix.framework == 'pytorch'
         name: Install dependencies (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
       - if: matrix.framework == 'tensorflow'
         name: Benchmark latency (TF)
         run: python references/detection/latency_tensorflow.py db_mobilenet_v3_large --it 5 --size 512
@@ -444,12 +444,12 @@ jobs:
         name: Install dependencies (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
       - if: matrix.framework == 'pytorch'
         name: Install dependencies (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
       - if: matrix.framework == 'pytorch'
         name: Benchmark latency (PT)
         run: python references/obj_detection/latency_pytorch.py fasterrcnn_mobilenet_v3_large_fpn --it 5 --size 512
diff --git a/.github/workflows/scripts.yml b/.github/workflows/scripts.yml
index a91d4cf5e6..37b0ce3652 100644
--- a/.github/workflows/scripts.yml
+++ b/.github/workflows/scripts.yml
@@ -41,12 +41,12 @@ jobs:
         name: Install package (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
       - if: matrix.framework == 'pytorch'
         name: Install package (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
 
       - name: Run analysis script
         run: |
@@ -87,12 +87,12 @@ jobs:
         name: Install package (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
       - if: matrix.framework == 'pytorch'
         name: Install package (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
 
       - name: Run detection script
         run: |
@@ -133,12 +133,12 @@ jobs:
         name: Install package (TF)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[tf] --upgrade
+          pip install -e .[tf,viz,html] --upgrade
       - if: matrix.framework == 'pytorch'
         name: Install package (PT)
         run: |
           python -m pip install --upgrade pip
-          pip install -e .[torch] --upgrade
+          pip install -e .[torch,viz,html] --upgrade
       - name: Run evaluation script
         run: |
           python scripts/evaluate.py db_resnet50 crnn_vgg16_bn --samples 10
diff --git a/README.md b/README.md
index 82cc3c2480..d82ef8344b 100644
--- a/README.md
+++ b/README.md
@@ -37,7 +37,7 @@ from doctr.io import DocumentFile
 pdf_doc = DocumentFile.from_pdf("path/to/your/doc.pdf")
 # Image
 single_img_doc = DocumentFile.from_images("path/to/your/img.jpg")
-# Webpage
+# Webpage (requires `weasyprint` to be installed)
 webpage_doc = DocumentFile.from_url("https://www.yoursite.com")
 # Multiple page images
 multi_img_doc = DocumentFile.from_images(["path/to/page1.jpg", "path/to/page2.jpg"])
@@ -75,6 +75,7 @@ If both options are set to False, the predictor will always fit and return rotat
 To interpret your model's predictions, you can visualize them interactively as follows:
 
 ```python
+# Display the result (requires matplotlib & mplcursors to be installed)
 result.show()
 ```
 
@@ -136,16 +137,6 @@ The KIE predictor results per page are in a dictionary format with each key repr
 
 Python 3.9 (or higher) and [pip](https://pip.pypa.io/en/stable/) are required to install docTR.
 
-Since we use [weasyprint](https://weasyprint.org/), you will need extra dependencies if you are not running Linux.
-
-For MacOS users, you can install them as follows:
-
-```shell
-brew install cairo pango gdk-pixbuf libffi
-```
-
-For Windows users, those dependencies are included in GTK. You can find the latest installer over [here](https://github.com/tschoonj/GTK-for-Windows-Runtime-Environment-Installer/releases).
-
 ### Latest release
 
 You can then install the latest release of the package using [pypi](https://pypi.org/project/python-doctr/) as follows:
@@ -350,9 +341,15 @@ Your API should now be running locally on your port 8002. Access your automatica
 
 ```python
 import requests
+
+headers = {"accept": "application/json"}
+params = {"det_arch": "db_resnet50", "reco_arch": "crnn_vgg16_bn"}
+
 with open('/path/to/your/doc.jpg', 'rb') as f:
-    data = f.read()
-response = requests.post("http://localhost:8002/ocr", files={'file': data}).json()
+    files = [  # application/pdf, image/jpeg, image/png supported
+        ("files", ("doc.jpg", f.read(), "image/jpeg")),
+    ]
+print(requests.post("http://localhost:8080/ocr", headers=headers, params=params, files=files).json())
 ```
 
 ### Example notebooks
diff --git a/docs/README.md b/docs/README.md
index 972bda511d..bf92c7bc45 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -8,6 +8,6 @@ To install only the `docs` environment, you can do:
 ```bash
 # Make sure you are at the root of the repository before executing these commands
 python -m pip install --upgrade pip
-pip install -e .[tf]  # or .[torch]
+pip install -e .[tf,viz,html]  # or .[torch,viz,html]
 pip install -e .[docs]
 ```
diff --git a/docs/source/getting_started/installing.rst b/docs/source/getting_started/installing.rst
index d746ebc0b4..a00451514a 100644
--- a/docs/source/getting_started/installing.rst
+++ b/docs/source/getting_started/installing.rst
@@ -19,17 +19,6 @@ For MacBooks with M1 chip, you will need some additional packages or specific ve
 * `TensorFlow 2 Metal Plugin <https://developer.apple.com/metal/tensorflow-plugin/>`_
 * `PyTorch >= 1.12.0 <https://pytorch.org/get-started/locally/#start-locally>`_
 
-If you are running another OS than Linux, you will need a few extra dependencies.
-
-For MacOS users, you can install them using `Homebrew <https://brew.sh/>`_ as follows:
-
-.. code:: shell
-
-    brew install cairo pango gdk-pixbuf libffi
-
-For Windows users, those dependencies are included in GTK. You can find the latest installer over `here <https://github.com/tschoonj/GTK-for-Windows-Runtime-Environment-Installer/releases>`_.
-
-
 Via Python Package
 ==================
 
@@ -49,12 +38,18 @@ We strive towards reducing framework-specific dependencies to a minimum, but som
         .. code:: bash
 
             pip install "python-doctr[tf]"
+            # or with preinstalled packages for visualization & html support
+            pip install "python-doctr[tf,viz,html]"
 
     .. tab:: PyTorch
 
         .. code:: bash
 
             pip install "python-doctr[torch]"
+            # or with preinstalled packages for visualization & html support
+            pip install "python-doctr[torch,viz,html]"
+
+
 
 
 Via Conda (Only for Linux)
diff --git a/doctr/file_utils.py b/doctr/file_utils.py
index 93f12a55cb..68e9dfffac 100644
--- a/doctr/file_utils.py
+++ b/doctr/file_utils.py
@@ -5,21 +5,16 @@
 
 # Adapted from https://github.com/huggingface/transformers/blob/master/src/transformers/file_utils.py
 
+import importlib.metadata
 import importlib.util
 import logging
 import os
-import sys
+from typing import Optional
 
 CLASS_NAME: str = "words"
 
 
-if sys.version_info < (3, 8):  # pragma: no cover
-    import importlib_metadata
-else:
-    import importlib.metadata as importlib_metadata
-
-
-__all__ = ["is_tf_available", "is_torch_available", "CLASS_NAME"]
+__all__ = ["is_tf_available", "is_torch_available", "requires_package", "CLASS_NAME"]
 
 ENV_VARS_TRUE_VALUES = {"1", "ON", "YES", "TRUE"}
 ENV_VARS_TRUE_AND_AUTO_VALUES = ENV_VARS_TRUE_VALUES.union({"AUTO"})
@@ -32,9 +27,9 @@
     _torch_available = importlib.util.find_spec("torch") is not None
     if _torch_available:
         try:
-            _torch_version = importlib_metadata.version("torch")
+            _torch_version = importlib.metadata.version("torch")
             logging.info(f"PyTorch version {_torch_version} available.")
-        except importlib_metadata.PackageNotFoundError:  # pragma: no cover
+        except importlib.metadata.PackageNotFoundError:  # pragma: no cover
             _torch_available = False
 else:  # pragma: no cover
     logging.info("Disabling PyTorch because USE_TF is set")
@@ -59,9 +54,9 @@
         # For the metadata, we have to look for both tensorflow and tensorflow-cpu
         for pkg in candidates:
             try:
-                _tf_version = importlib_metadata.version(pkg)
+                _tf_version = importlib.metadata.version(pkg)
                 break
-            except importlib_metadata.PackageNotFoundError:
+            except importlib.metadata.PackageNotFoundError:
                 pass
         _tf_available = _tf_version is not None
     if _tf_available:
@@ -82,6 +77,25 @@
     )
 
 
+def requires_package(name: str, extra_message: Optional[str] = None) -> None:  # pragma: no cover
+    """
+    package requirement helper
+
+    Args:
+    ----
+        name: name of the package
+        extra_message: additional message to display if the package is not found
+    """
+    try:
+        _pkg_version = importlib.metadata.version(name)
+        logging.info(f"{name} version {_pkg_version} available.")
+    except importlib.metadata.PackageNotFoundError:
+        raise ImportError(
+            f"\n\n{extra_message if extra_message is not None else ''} "
+            f"\nPlease install it with the following command: pip install {name}\n"
+        )
+
+
 def is_torch_available():
     """Whether PyTorch is installed."""
     return _torch_available
diff --git a/doctr/io/elements.py b/doctr/io/elements.py
index 4862b17b6b..b6d2cb9b5b 100644
--- a/doctr/io/elements.py
+++ b/doctr/io/elements.py
@@ -12,14 +12,19 @@
 from xml.etree.ElementTree import Element as ETElement
 from xml.etree.ElementTree import SubElement
 
-import matplotlib.pyplot as plt
 import numpy as np
 
 import doctr
+from doctr.file_utils import requires_package
 from doctr.utils.common_types import BoundingBox
 from doctr.utils.geometry import resolve_enclosing_bbox, resolve_enclosing_rbbox
+from doctr.utils.reconstitution import synthesize_kie_page, synthesize_page
 from doctr.utils.repr import NestedObject
-from doctr.utils.visualization import synthesize_kie_page, synthesize_page, visualize_kie_page, visualize_page
+
+try:  # optional dependency for visualization
+    from doctr.utils.visualization import visualize_kie_page, visualize_page
+except ModuleNotFoundError:
+    pass
 
 __all__ = ["Element", "Word", "Artefact", "Line", "Prediction", "Block", "Page", "KIEPage", "Document"]
 
@@ -282,6 +287,10 @@ def show(self, interactive: bool = True, preserve_aspect_ratio: bool = False, **
             preserve_aspect_ratio: pass True if you passed True to the predictor
             **kwargs: additional keyword arguments passed to the matplotlib.pyplot.show method
         """
+        requires_package("matplotlib", "`.show()` requires matplotlib & mplcursors installed")
+        requires_package("mplcursors", "`.show()` requires matplotlib & mplcursors installed")
+        import matplotlib.pyplot as plt
+
         visualize_page(self.export(), self.page, interactive=interactive, preserve_aspect_ratio=preserve_aspect_ratio)
         plt.show(**kwargs)
 
@@ -457,6 +466,10 @@ def show(self, interactive: bool = True, preserve_aspect_ratio: bool = False, **
             preserve_aspect_ratio: pass True if you passed True to the predictor
             **kwargs: keyword arguments passed to the matplotlib.pyplot.show method
         """
+        requires_package("matplotlib", "`.show()` requires matplotlib & mplcursors installed")
+        requires_package("mplcursors", "`.show()` requires matplotlib & mplcursors installed")
+        import matplotlib.pyplot as plt
+
         visualize_kie_page(
             self.export(), self.page, interactive=interactive, preserve_aspect_ratio=preserve_aspect_ratio
         )
diff --git a/doctr/io/html.py b/doctr/io/html.py
index dd2d00c102..f8a8da237d 100644
--- a/doctr/io/html.py
+++ b/doctr/io/html.py
@@ -5,8 +5,6 @@
 
 from typing import Any
 
-from weasyprint import HTML
-
 __all__ = ["read_html"]
 
 
@@ -25,4 +23,6 @@ def read_html(url: str, **kwargs: Any) -> bytes:
     -------
         decoded PDF file as a bytes stream
     """
+    from weasyprint import HTML
+
     return HTML(url, **kwargs).write_pdf()
diff --git a/doctr/io/reader.py b/doctr/io/reader.py
index 37af393e46..76f7317cb1 100644
--- a/doctr/io/reader.py
+++ b/doctr/io/reader.py
@@ -8,6 +8,7 @@
 
 import numpy as np
 
+from doctr.file_utils import requires_package
 from doctr.utils.common_types import AbstractFile
 
 from .html import read_html
@@ -54,6 +55,11 @@ def from_url(cls, url: str, **kwargs) -> List[np.ndarray]:
         -------
             the list of pages decoded as numpy ndarray of shape H x W x 3
         """
+        requires_package(
+            "weasyprint",
+            "`.from_url` requires weasyprint installed.\n"
+            + "Installation instructions: https://doc.courtbouillon.org/weasyprint/stable/first_steps.html#installation",
+        )
         pdf_stream = read_html(url)
         return cls.from_pdf(pdf_stream, **kwargs)
 
diff --git a/doctr/utils/reconstitution.py b/doctr/utils/reconstitution.py
new file mode 100644
index 0000000000..82ae20cdd0
--- /dev/null
+++ b/doctr/utils/reconstitution.py
@@ -0,0 +1,126 @@
+# Copyright (C) 2021-2024, Mindee.
+
+# This program is licensed under the Apache License 2.0.
+# See LICENSE or go to <https://opensource.org/licenses/Apache-2.0> for full license details.
+from typing import Any, Dict, Optional
+
+import numpy as np
+from anyascii import anyascii
+from PIL import Image, ImageDraw
+
+from .fonts import get_font
+
+__all__ = ["synthesize_page", "synthesize_kie_page"]
+
+
+def synthesize_page(
+    page: Dict[str, Any],
+    draw_proba: bool = False,
+    font_family: Optional[str] = None,
+) -> np.ndarray:
+    """Draw a the content of the element page (OCR response) on a blank page.
+
+    Args:
+    ----
+        page: exported Page object to represent
+        draw_proba: if True, draw words in colors to represent confidence. Blue: p=1, red: p=0
+        font_size: size of the font, default font = 13
+        font_family: family of the font
+
+    Returns:
+    -------
+        the synthesized page
+    """
+    # Draw template
+    h, w = page["dimensions"]
+    response = 255 * np.ones((h, w, 3), dtype=np.int32)
+
+    # Draw each word
+    for block in page["blocks"]:
+        for line in block["lines"]:
+            for word in line["words"]:
+                # Get absolute word geometry
+                (xmin, ymin), (xmax, ymax) = word["geometry"]
+                xmin, xmax = int(round(w * xmin)), int(round(w * xmax))
+                ymin, ymax = int(round(h * ymin)), int(round(h * ymax))
+
+                # White drawing context adapted to font size, 0.75 factor to convert pts --> pix
+                font = get_font(font_family, int(0.75 * (ymax - ymin)))
+                img = Image.new("RGB", (xmax - xmin, ymax - ymin), color=(255, 255, 255))
+                d = ImageDraw.Draw(img)
+                # Draw in black the value of the word
+                try:
+                    d.text((0, 0), word["value"], font=font, fill=(0, 0, 0))
+                except UnicodeEncodeError:
+                    # When character cannot be encoded, use its anyascii version
+                    d.text((0, 0), anyascii(word["value"]), font=font, fill=(0, 0, 0))
+
+                # Colorize if draw_proba
+                if draw_proba:
+                    p = int(255 * word["confidence"])
+                    mask = np.where(np.array(img) == 0, 1, 0)
+                    proba: np.ndarray = np.array([255 - p, 0, p])
+                    color = mask * proba[np.newaxis, np.newaxis, :]
+                    white_mask = 255 * (1 - mask)
+                    img = color + white_mask
+
+                # Write to response page
+                response[ymin:ymax, xmin:xmax, :] = np.array(img)
+
+    return response
+
+
+def synthesize_kie_page(
+    page: Dict[str, Any],
+    draw_proba: bool = False,
+    font_family: Optional[str] = None,
+) -> np.ndarray:
+    """Draw a the content of the element page (OCR response) on a blank page.
+
+    Args:
+    ----
+        page: exported Page object to represent
+        draw_proba: if True, draw words in colors to represent confidence. Blue: p=1, red: p=0
+        font_size: size of the font, default font = 13
+        font_family: family of the font
+
+    Returns:
+    -------
+        the synthesized page
+    """
+    # Draw template
+    h, w = page["dimensions"]
+    response = 255 * np.ones((h, w, 3), dtype=np.int32)
+
+    # Draw each word
+    for predictions in page["predictions"].values():
+        for prediction in predictions:
+            # Get aboslute word geometry
+            (xmin, ymin), (xmax, ymax) = prediction["geometry"]
+            xmin, xmax = int(round(w * xmin)), int(round(w * xmax))
+            ymin, ymax = int(round(h * ymin)), int(round(h * ymax))
+
+            # White drawing context adapted to font size, 0.75 factor to convert pts --> pix
+            font = get_font(font_family, int(0.75 * (ymax - ymin)))
+            img = Image.new("RGB", (xmax - xmin, ymax - ymin), color=(255, 255, 255))
+            d = ImageDraw.Draw(img)
+            # Draw in black the value of the word
+            try:
+                d.text((0, 0), prediction["value"], font=font, fill=(0, 0, 0))
+            except UnicodeEncodeError:
+                # When character cannot be encoded, use its anyascii version
+                d.text((0, 0), anyascii(prediction["value"]), font=font, fill=(0, 0, 0))
+
+            # Colorize if draw_proba
+            if draw_proba:
+                p = int(255 * prediction["confidence"])
+                mask = np.where(np.array(img) == 0, 1, 0)
+                proba: np.ndarray = np.array([255 - p, 0, p])
+                color = mask * proba[np.newaxis, np.newaxis, :]
+                white_mask = 255 * (1 - mask)
+                img = color + white_mask
+
+            # Write to response page
+            response[ymin:ymax, xmin:xmax, :] = np.array(img)
+
+    return response
diff --git a/doctr/utils/visualization.py b/doctr/utils/visualization.py
index 66d9d9a943..4e97f751fe 100644
--- a/doctr/utils/visualization.py
+++ b/doctr/utils/visualization.py
@@ -9,16 +9,12 @@
 import cv2
 import matplotlib.patches as patches
 import matplotlib.pyplot as plt
-import mplcursors
 import numpy as np
-from anyascii import anyascii
 from matplotlib.figure import Figure
-from PIL import Image, ImageDraw
 
 from .common_types import BoundingBox, Polygon4P
-from .fonts import get_font
 
-__all__ = ["visualize_page", "synthesize_page", "visualize_kie_page", "synthesize_kie_page", "draw_boxes"]
+__all__ = ["visualize_page", "visualize_kie_page", "draw_boxes"]
 
 
 def rect_patch(
@@ -281,6 +277,8 @@ def visualize_page(
                     artists.append(rect)
 
     if interactive:
+        import mplcursors
+
         # Create mlp Cursor to hover patches in artists
         mplcursors.Cursor(artists, hover=2).connect("add", lambda sel: sel.annotation.set_text(sel.artist.get_label()))
     fig.tight_layout(pad=0.0)
@@ -288,63 +286,6 @@ def visualize_page(
     return fig
 
 
-def synthesize_page(
-    page: Dict[str, Any],
-    draw_proba: bool = False,
-    font_family: Optional[str] = None,
-) -> np.ndarray:
-    """Draw a the content of the element page (OCR response) on a blank page.
-
-    Args:
-    ----
-        page: exported Page object to represent
-        draw_proba: if True, draw words in colors to represent confidence. Blue: p=1, red: p=0
-        font_size: size of the font, default font = 13
-        font_family: family of the font
-
-    Returns:
-    -------
-        the synthesized page
-    """
-    # Draw template
-    h, w = page["dimensions"]
-    response = 255 * np.ones((h, w, 3), dtype=np.int32)
-
-    # Draw each word
-    for block in page["blocks"]:
-        for line in block["lines"]:
-            for word in line["words"]:
-                # Get aboslute word geometry
-                (xmin, ymin), (xmax, ymax) = word["geometry"]
-                xmin, xmax = int(round(w * xmin)), int(round(w * xmax))
-                ymin, ymax = int(round(h * ymin)), int(round(h * ymax))
-
-                # White drawing context adapted to font size, 0.75 factor to convert pts --> pix
-                font = get_font(font_family, int(0.75 * (ymax - ymin)))
-                img = Image.new("RGB", (xmax - xmin, ymax - ymin), color=(255, 255, 255))
-                d = ImageDraw.Draw(img)
-                # Draw in black the value of the word
-                try:
-                    d.text((0, 0), word["value"], font=font, fill=(0, 0, 0))
-                except UnicodeEncodeError:
-                    # When character cannot be encoded, use its anyascii version
-                    d.text((0, 0), anyascii(word["value"]), font=font, fill=(0, 0, 0))
-
-                # Colorize if draw_proba
-                if draw_proba:
-                    p = int(255 * word["confidence"])
-                    mask = np.where(np.array(img) == 0, 1, 0)
-                    proba: np.ndarray = np.array([255 - p, 0, p])
-                    color = mask * proba[np.newaxis, np.newaxis, :]
-                    white_mask = 255 * (1 - mask)
-                    img = color + white_mask
-
-                # Write to response page
-                response[ymin:ymax, xmin:xmax, :] = np.array(img)
-
-    return response
-
-
 def visualize_kie_page(
     page: Dict[str, Any],
     image: np.ndarray,
@@ -413,6 +354,8 @@ def visualize_kie_page(
                     artists.append(rect)
 
     if interactive:
+        import mplcursors
+
         # Create mlp Cursor to hover patches in artists
         mplcursors.Cursor(artists, hover=2).connect("add", lambda sel: sel.annotation.set_text(sel.artist.get_label()))
     fig.tight_layout(pad=0.0)
@@ -420,62 +363,6 @@ def visualize_kie_page(
     return fig
 
 
-def synthesize_kie_page(
-    page: Dict[str, Any],
-    draw_proba: bool = False,
-    font_family: Optional[str] = None,
-) -> np.ndarray:
-    """Draw a the content of the element page (OCR response) on a blank page.
-
-    Args:
-    ----
-        page: exported Page object to represent
-        draw_proba: if True, draw words in colors to represent confidence. Blue: p=1, red: p=0
-        font_size: size of the font, default font = 13
-        font_family: family of the font
-
-    Returns:
-    -------
-        the synthesized page
-    """
-    # Draw template
-    h, w = page["dimensions"]
-    response = 255 * np.ones((h, w, 3), dtype=np.int32)
-
-    # Draw each word
-    for predictions in page["predictions"].values():
-        for prediction in predictions:
-            # Get aboslute word geometry
-            (xmin, ymin), (xmax, ymax) = prediction["geometry"]
-            xmin, xmax = int(round(w * xmin)), int(round(w * xmax))
-            ymin, ymax = int(round(h * ymin)), int(round(h * ymax))
-
-            # White drawing context adapted to font size, 0.75 factor to convert pts --> pix
-            font = get_font(font_family, int(0.75 * (ymax - ymin)))
-            img = Image.new("RGB", (xmax - xmin, ymax - ymin), color=(255, 255, 255))
-            d = ImageDraw.Draw(img)
-            # Draw in black the value of the word
-            try:
-                d.text((0, 0), prediction["value"], font=font, fill=(0, 0, 0))
-            except UnicodeEncodeError:
-                # When character cannot be encoded, use its anyascii version
-                d.text((0, 0), anyascii(prediction["value"]), font=font, fill=(0, 0, 0))
-
-            # Colorize if draw_proba
-            if draw_proba:
-                p = int(255 * prediction["confidence"])
-                mask = np.where(np.array(img) == 0, 1, 0)
-                proba: np.ndarray = np.array([255 - p, 0, p])
-                color = mask * proba[np.newaxis, np.newaxis, :]
-                white_mask = 255 * (1 - mask)
-                img = color + white_mask
-
-            # Write to response page
-            response[ymin:ymax, xmin:xmax, :] = np.array(img)
-
-    return response
-
-
 def draw_boxes(boxes: np.ndarray, image: np.ndarray, color: Optional[Tuple[int, int, int]] = None, **kwargs) -> None:
     """Draw an array of relative straight boxes on an image
 
diff --git a/pyproject.toml b/pyproject.toml
index 60d9a7cfeb..06c3655699 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -32,7 +32,6 @@ classifiers=[
 ]
 dynamic = ["version"]
 dependencies = [
-    "importlib_metadata",
     # For proper typing, mypy needs numpy>=1.20.0 (cf. https://github.com/numpy/numpy/pull/16515)
     # Additional typing support is brought by numpy>=1.22.4, but core build sticks to >=1.16.0
     "numpy>=1.16.0,<2.0.0",
@@ -45,11 +44,8 @@ dependencies = [
     "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",
     "anyascii>=0.3.2",
     "tqdm>=4.30.0",
 ]
@@ -66,6 +62,13 @@ torch = [
     "torchvision>=0.13.0",
     "onnx>=1.12.0,<3.0.0",
 ]
+html = [
+    "weasyprint>=55.0",
+]
+viz = [
+    "matplotlib>=3.1.0",
+    "mplcursors>=0.3",
+]
 testing = [
     "pytest>=5.3.2",
     "coverage[toml]>=4.5.4",
@@ -99,6 +102,10 @@ dev = [
     "torch>=1.12.0,<3.0.0",
     "torchvision>=0.13.0",
     "onnx>=1.12.0,<3.0.0",
+    # Extras
+    "weasyprint>=55.0",
+    "matplotlib>=3.1.0",
+    "mplcursors>=0.3",
     # Testing
     "pytest>=5.3.2",
     "coverage[toml]>=4.5.4",
diff --git a/references/requirements.txt b/references/requirements.txt
index bb72bdd47b..679df79518 100644
--- a/references/requirements.txt
+++ b/references/requirements.txt
@@ -3,3 +3,4 @@ tqdm
 wandb>=0.10.31
 psutil>=5.9.0
 clearml>=1.11.1
+matplotlib>=3.1.0
diff --git a/tests/common/test_core.py b/tests/common/test_core.py
index cd2758b0df..2fb8d1b9b0 100644
--- a/tests/common/test_core.py
+++ b/tests/common/test_core.py
@@ -1,6 +1,7 @@
 import pytest
 
 import doctr
+from doctr.file_utils import requires_package
 
 
 def test_version():
@@ -15,3 +16,9 @@ def test_is_tf_available():
 @pytest.mark.skipif(doctr.is_torch_available() and doctr.is_tf_available(), reason="torch and tf are available")
 def test_is_torch_available():
     assert not doctr.is_torch_available()
+
+
+def test_requires_package():
+    requires_package("numpy")  # availbable
+    with pytest.raises(ImportError):  # not available
+        requires_package("non_existent_package")
diff --git a/tests/common/test_utils_reconstitution.py b/tests/common/test_utils_reconstitution.py
new file mode 100644
index 0000000000..3b70e67070
--- /dev/null
+++ b/tests/common/test_utils_reconstitution.py
@@ -0,0 +1,12 @@
+import numpy as np
+from test_io_elements import _mock_pages
+
+from doctr.utils import reconstitution
+
+
+def test_synthesize_page():
+    pages = _mock_pages()
+    reconstitution.synthesize_page(pages[0].export(), draw_proba=False)
+    render = reconstitution.synthesize_page(pages[0].export(), draw_proba=True)
+    assert isinstance(render, np.ndarray)
+    assert render.shape == (*pages[0].dimensions, 3)
diff --git a/tests/common/test_utils_visualization.py b/tests/common/test_utils_visualization.py
index b1e9998698..ae232ebb85 100644
--- a/tests/common/test_utils_visualization.py
+++ b/tests/common/test_utils_visualization.py
@@ -21,14 +21,6 @@ def test_visualize_page():
         visualization.create_obj_patch((1, 2, 3, 4, 5), (100, 100))
 
 
-def test_synthesize_page():
-    pages = _mock_pages()
-    visualization.synthesize_page(pages[0].export(), draw_proba=False)
-    render = visualization.synthesize_page(pages[0].export(), draw_proba=True)
-    assert isinstance(render, np.ndarray)
-    assert render.shape == (*pages[0].dimensions, 3)
-
-
 def test_draw_boxes():
     image = np.ones((256, 256, 3), dtype=np.float32)
     boxes = [