add app files

.gitignore

@@ -0,0 +1,201 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[codz]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# UV
+#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#uv.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+#poetry.toml
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.envrc
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# Abstra
+# Abstra is an AI-powered process automation framework.
+# Ignore directories containing user credentials, local state, and settings.
+# Learn more at https://abstra.io/docs
+.abstra/
+
+# Visual Studio Code
+#  Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore 
+#  that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore
+#  and can be added to the global gitignore or merged into this file. However, if you prefer, 
+#  you could uncomment the following to ignore the entire vscode folder
+# .vscode/
+
+# Ruff stuff:
+.ruff_cache/
+
+# PyPI configuration file
+.pypirc
+
+# Cursor
+#  Cursor is an AI-powered code editor. `.cursorignore` specifies files/directories to
+#  exclude from AI features like autocomplete and code analysis. Recommended for sensitive data
+#  refer to https://docs.cursor.com/context/ignore-files
+.cursorignore
+.cursorindexingignore
+
+# Marimo
+marimo/_static/
+marimo/_lsp/
+__marimo__/

main.py

@@ -0,0 +1,17 @@
+import gradio as gr
+
+
+def greet(name: str, intensity: int) -> str:
+    return "Hello, " + name + "!" * int(intensity)
+
+
+demo = gr.Interface(
+    fn=greet,
+    inputs=[
+        "text",
+        "slider",
+    ],  # the inputs are a text box and a slider ("text" and "slider" are components in Gradio)
+    outputs=["text"],  # the output is a text box
+)
+
+demo.launch()

out/bar002_labeled.json

@@ -0,0 +1,162 @@
+[
+  {
+    "text":"n",
+    "bbox":[
+      54,
+      26,
+      73,
+      46
+    ],
+    "labels":"AXIS_TITLE"
+  },
+  {
+    "text":"40",
+    "bbox":[
+      54,
+      54,
+      94,
+      84
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"35",
+    "bbox":[
+      54,
+      111,
+      91,
+      141
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"30",
+    "bbox":[
+      53,
+      168,
+      92,
+      198
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"25",
+    "bbox":[
+      52,
+      223,
+      90,
+      253
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"20",
+    "bbox":[
+      51,
+      280,
+      90,
+      310
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"15",
+    "bbox":[
+      56,
+      338,
+      88,
+      367
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"10",
+    "bbox":[
+      53,
+      394,
+      88,
+      424
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"5",
+    "bbox":[
+      69,
+      449,
+      86,
+      478
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"0",
+    "bbox":[
+      68,
+      506,
+      88,
+      535
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"17",
+    "bbox":[
+      177,
+      535,
+      212,
+      564
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"18",
+    "bbox":[
+      366,
+      539,
+      401,
+      569
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"19",
+    "bbox":[
+      562,
+      542,
+      595,
+      571
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"20",
+    "bbox":[
+      753,
+      545,
+      793,
+      576
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"(a)",
+    "bbox":[
+      777,
+      195,
+      822,
+      230
+    ],
+    "labels":"OTHER"
+  },
+  {
+    "text":"Number of rays in A",
+    "bbox":[
+      314,
+      586,
+      652,
+      627
+    ],
+    "labels":"AXIS_TITLE"
+  }
+]

out/json_labeled.json

@@ -0,0 +1,162 @@
+[
+  {
+    "text":"n",
+    "bbox":[
+      54,
+      26,
+      73,
+      46
+    ],
+    "labels":"AXIS_TITLE"
+  },
+  {
+    "text":"40",
+    "bbox":[
+      54,
+      54,
+      94,
+      84
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"35",
+    "bbox":[
+      54,
+      111,
+      91,
+      141
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"30",
+    "bbox":[
+      53,
+      168,
+      92,
+      198
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"25",
+    "bbox":[
+      52,
+      223,
+      90,
+      253
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"20",
+    "bbox":[
+      51,
+      280,
+      90,
+      310
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"15",
+    "bbox":[
+      56,
+      338,
+      88,
+      367
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"10",
+    "bbox":[
+      53,
+      394,
+      88,
+      424
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"5",
+    "bbox":[
+      69,
+      449,
+      86,
+      478
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"0",
+    "bbox":[
+      68,
+      506,
+      88,
+      535
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"17",
+    "bbox":[
+      177,
+      535,
+      212,
+      564
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"18",
+    "bbox":[
+      366,
+      539,
+      401,
+      569
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"19",
+    "bbox":[
+      562,
+      542,
+      595,
+      571
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"20",
+    "bbox":[
+      753,
+      545,
+      793,
+      576
+    ],
+    "labels":"TICK_LABEL"
+  },
+  {
+    "text":"(a)",
+    "bbox":[
+      777,
+      195,
+      822,
+      230
+    ],
+    "labels":"OTHER"
+  },
+  {
+    "text":"Number of rays in A",
+    "bbox":[
+      314,
+      586,
+      652,
+      627
+    ],
+    "labels":"AXIS_TITLE"
+  }
+]

requirements.txt

@@ -0,0 +1,179 @@
+accelerate==1.7.0
+aiofiles==24.1.0
+aiohappyeyeballs==2.6.1
+aiohttp==3.12.12
+aiosignal==1.3.2
+annotated-types==0.7.0
+anyio==4.9.0
+argon2-cffi==25.1.0
+argon2-cffi-bindings==21.2.0
+arrow==1.3.0
+asttokens==3.0.0
+async-lru==2.0.5
+attrs==25.3.0
+babel==2.17.0
+beautifulsoup4==4.13.4
+black==25.1.0
+bleach==6.2.0
+certifi==2025.4.26
+cffi==1.17.1
+charset-normalizer==3.4.2
+click==8.2.1
+comm==0.2.2
+datasets==3.6.0
+debugpy==1.8.14
+decorator==5.2.1
+defusedxml==0.7.1
+dill==0.3.8
+evaluate==0.4.3
+executing==2.2.0
+fastapi==0.115.12
+fastjsonschema==2.21.1
+ffmpy==0.6.0
+filelock==3.18.0
+fqdn==1.5.1
+frozenlist==1.7.0
+fsspec==2025.3.0
+gradio==5.34.0
+gradio_client==1.10.3
+groovy==0.1.2
+h11==0.16.0
+hf-xet==1.1.3
+httpcore==1.0.9
+httpx==0.28.1
+huggingface-hub==0.33.0
+idna==3.10
+ipykernel==6.29.5
+ipython==9.3.0
+ipython_pygments_lexers==1.1.1
+ipywidgets==8.1.7
+isoduration==20.11.0
+isort==6.0.1
+jedi==0.19.2
+Jinja2==3.1.6
+json5==0.12.0
+jsonpointer==3.0.0
+jsonschema==4.24.0
+jsonschema-specifications==2025.4.1
+jupyter==1.1.1
+jupyter-console==6.6.3
+jupyter-events==0.12.0
+jupyter-lsp==2.2.5
+jupyter_client==8.6.3
+jupyter_core==5.8.1
+jupyter_server==2.16.0
+jupyter_server_terminals==0.5.3
+jupyterlab==4.4.3
+jupyterlab_code_formatter==3.0.2
+jupyterlab_pygments==0.3.0
+jupyterlab_server==2.27.3
+jupyterlab_widgets==3.0.15
+markdown-it-py==3.0.0
+MarkupSafe==3.0.2
+matplotlib-inline==0.1.7
+mdurl==0.1.2
+mistune==3.1.3
+mpmath==1.3.0
+multidict==6.4.4
+multiprocess==0.70.16
+mypy_extensions==1.1.0
+nbclient==0.10.2
+nbconvert==7.16.6
+nbformat==5.10.4
+nest-asyncio==1.6.0
+networkx==3.5
+notebook==7.4.3
+notebook_shim==0.2.4
+numpy==2.3.0
+nvidia-cublas-cu12==12.6.4.1
+nvidia-cuda-cupti-cu12==12.6.80
+nvidia-cuda-nvrtc-cu12==12.6.77
+nvidia-cuda-runtime-cu12==12.6.77
+nvidia-cudnn-cu12==9.5.1.17
+nvidia-cufft-cu12==11.3.0.4
+nvidia-cufile-cu12==1.11.1.6
+nvidia-curand-cu12==10.3.7.77
+nvidia-cusolver-cu12==11.7.1.2
+nvidia-cusparse-cu12==12.5.4.2
+nvidia-cusparselt-cu12==0.6.3
+nvidia-nccl-cu12==2.26.2
+nvidia-nvjitlink-cu12==12.6.85
+nvidia-nvtx-cu12==12.6.77
+opencv-python==4.11.0.86
+orjson==3.10.18
+overrides==7.7.0
+packaging==25.0
+pandas==2.3.0
+pandocfilters==1.5.1
+parso==0.8.4
+pathspec==0.12.1
+pexpect==4.9.0
+pillow==11.2.1
+platformdirs==4.3.8
+prometheus_client==0.22.1
+prompt_toolkit==3.0.51
+propcache==0.3.2
+psutil==7.0.0
+ptyprocess==0.7.0
+pure_eval==0.2.3
+pyarrow==20.0.0
+pycparser==2.22
+pydantic==2.11.7
+pydantic_core==2.33.2
+pydub==0.25.1
+Pygments==2.19.1
+pytesseract==0.3.13
+python-dateutil==2.9.0.post0
+python-json-logger==3.3.0
+python-multipart==0.0.20
+pytz==2025.2
+PyYAML==6.0.2
+pyzmq==27.0.0
+referencing==0.36.2
+regex==2024.11.6
+requests==2.32.4
+rfc3339-validator==0.1.4
+rfc3986-validator==0.1.1
+rich==14.0.0
+rpds-py==0.25.1
+ruff==0.11.13
+safehttpx==0.1.6
+safetensors==0.5.3
+semantic-version==2.10.0
+Send2Trash==1.8.3
+setuptools==80.9.0
+shellingham==1.5.4
+six==1.17.0
+sniffio==1.3.1
+soupsieve==2.7
+stack-data==0.6.3
+starlette==0.46.2
+sympy==1.14.0
+terminado==0.18.1
+timm==1.0.15
+tinycss2==1.4.0
+tokenizers==0.21.1
+tomlkit==0.13.3
+torch==2.7.1
+torchvision==0.22.1
+tornado==6.5.1
+tqdm==4.67.1
+traitlets==5.14.3
+transformers==4.52.4
+triton==3.3.1
+typer==0.16.0
+types-python-dateutil==2.9.0.20250516
+typing-inspection==0.4.1
+typing_extensions==4.14.0
+tzdata==2025.2
+uri-template==1.3.0
+urllib3==2.4.0
+uvicorn==0.34.3
+wcwidth==0.2.13
+webcolors==24.11.1
+webencodings==0.5.1
+websocket-client==1.8.0
+websockets==15.0.1
+widgetsnbextension==4.0.14
+xxhash==3.5.0
+yarl==1.20.1

src/app.py

@@ -0,0 +1,40 @@
+import gradio as gr
+import inference
+
+
+def classify_tokens(image, annots_file, annots_format):
+    if image is None:
+        raise gr.Error("Please upload an image.")
+    if annots_file is None:
+        raise gr.Error("Please upload an annotation file.")
+    if annots_format is None:
+        raise gr.Error("Please choose annotation foramt.")
+
+    annot_image, labeled_annot_file = inference.perform_inference(
+        image, annots_file, annots_format
+    )
+
+    return annot_image, labeled_annot_file
+
+
+iface = gr.Interface(
+    fn=classify_tokens,
+    inputs=[
+        gr.Image(type="pil", label="Input image"),
+        gr.File(label="Annotation file"),
+        gr.Dropdown(
+            choices=["STD", "ICPR22", "EconBiz & CHIMIE-R"],
+            label="Annotation file format",
+            value="STD",
+        ),
+    ],
+    outputs=[
+        gr.Image(type="pil", label="Annotated image"),
+        gr.File(label="Labeled annotation file"),
+    ],
+    title="Chart Text Role Classification Demo",
+    description="Upload an image and an annotation file to classify token roles. The application will return the annotated image and the labeled annotation file.",
+)
+
+if __name__ == "__main__":
+    iface.launch()

src/inference.py

@@ -0,0 +1,61 @@
+from utils import load_annots, normalize_bbox, annotate_image
+from transformers import AutoModelForTokenClassification, AutoProcessor
+import os
+import pandas as pd
+
+
+model = AutoModelForTokenClassification.from_pretrained(
+    "nassimb0u/chart-text-role-classification-model"
+)
+processor = AutoProcessor.from_pretrained(
+    "nassimb0u/chart-text-role-classification-model"
+)
+
+
+def process_image_and_annot(image, annots_data):
+    prepro_annots_data = {"text": [], "bbox": []}
+
+    for b, t in zip(annots_data["bbox"], annots_data["text"]):
+        prepro_annots_data["bbox"].append(normalize_bbox(b, image.size, type="polygon"))
+        prepro_annots_data["text"].append(t)
+    return image.convert("RGB"), annots_data
+
+
+def perform_inference(image, annots_file, annots_format):
+    annots_data = load_annots(annots_file, annots_format)
+    _, prepro_annots_data = process_image_and_annot(
+        image,
+        annots_data,
+    )
+
+    encoding = processor(
+        image,
+        prepro_annots_data["text"],
+        boxes=prepro_annots_data["bbox"],
+        return_tensors="pt",
+    )
+    outputs = model(**encoding)
+    predictions = outputs.logits.argmax(-1)
+
+    labels = [model.config.id2label[idx.item()] for idx in predictions[0]]
+    mask = []
+    for i in range(encoding["bbox"].shape[1]):
+        zero = True
+        equal_to_pred = True
+        for j in range(encoding["bbox"].shape[2]):
+            if encoding["bbox"][0][i][j] != 0:
+                zero = False
+            if i > 0 and encoding["bbox"][0][i - 1][j] != encoding["bbox"][0][i][j]:
+                equal_to_pred = False
+
+        mask.append(not (zero or equal_to_pred))
+
+    annots_data["labels"] = [label for (m, label) in zip(mask, labels) if m]
+
+    image = annotate_image(image, annots_data)
+
+    out_file_name = f"out/{os.path.basename(annots_file).split(".")[0]}_labeled.json"
+    df = pd.DataFrame(annots_data)
+    df.to_json(out_file_name, orient="records", lines=False, indent=2)
+
+    return image, out_file_name

src/utils.py

@@ -0,0 +1,149 @@
+import json
+import cv2
+from PIL import ImageDraw
+
+
+def load_annots(annots_file, annot_format):
+    with open(annots_file, "r") as f:
+        data = json.load(f)
+
+    annots = {"text": [], "bbox": []}
+    if annot_format == "STD":
+        for text_block in data:
+            annots["text"].append(text_block["text"])
+            annots["bbox"].append(text_block["bbox"])
+
+    elif annot_format == "ICPR22":
+        for text_block in data["task2"]["output"]["text_blocks"]:
+            annots["text"].append(text_block["text"])
+            annots["bbox"].append(quad_to_box(text_block["polygon"]))
+
+    elif annot_format == "EconBiz & CHIMIE-R":
+        for text_block in data["textelements"]:
+            annots["text"].append(text_block["content"])
+            annots["bbox"].append(
+                quad_to_box(
+                    get_quad(text_block["boundingbox"], data["width"], data["height"])
+                )
+            )
+    else:
+        raise ValueError(f"Unknown annotation format: {annot_format}")
+
+    return annots
+
+
+def annotate_image(image, labeled_annots_data):
+    draw = ImageDraw.Draw(image)
+    width, height = image.size
+
+    for b, label in zip(labeled_annots_data["bbox"], labeled_annots_data["labels"]):
+        x0, y0, x1, y1 = b
+        # Skip zero bboxes if needed
+        if (x0, y0, x1, y1) == (0, 0, 0, 0):
+            continue
+        draw.rectangle([x0, y0, x1, y1], outline="red", width=2)
+        draw.text((x0, y0 - 10), label, fill="red")
+
+    return image
+
+
+def normalize_bbox(bbox, size, type=None):
+    if type == "box":
+        height = int(bbox["height"])
+        width = int(bbox["width"])
+        left = max(0, bbox["x0"])
+        top = max(0, bbox["y0"])
+        right = left + width
+        bottom = top + height
+    if type == "polygon":
+        left = bbox[0]
+        top = bbox[1]
+        right = bbox[2]
+        bottom = bbox[3]
+    return [
+        int(1000 * left / size[0]),
+        int(1000 * top / size[1]),
+        int(1000 * right / size[0]),
+        int(1000 * bottom / size[1]),
+    ]
+
+
+def quad_to_box(quad):
+    box = (max(0, quad["x0"]), max(0, quad["y0"]), quad["x2"], quad["y2"])
+    if box[3] < box[1]:
+        bbox = list(box)
+        tmp = bbox[3]
+        bbox[3] = bbox[1]
+        bbox[1] = tmp
+        box = tuple(bbox)
+    if box[2] < box[0]:
+        bbox = list(box)
+        tmp = bbox[2]
+        bbox[2] = bbox[0]
+        bbox[0] = tmp
+        box = tuple(bbox)
+    return box
+
+
+def get_quad(bbox, width, height):
+    x0 = int(bbox["center_x"] - bbox["width"] / 2)
+    x1 = int(bbox["center_x"] + bbox["width"] / 2)
+    x2 = int(bbox["center_x"] + bbox["width"] / 2)
+    x3 = int(bbox["center_x"] - bbox["width"] / 2)
+    y0 = int(bbox["center_y"] - bbox["height"] / 2)
+    y1 = int(bbox["center_y"] - bbox["height"] / 2)
+    y2 = int(bbox["center_y"] + bbox["height"] / 2)
+    y3 = int(bbox["center_y"] + bbox["height"] / 2)
+
+    if bbox["orientation"] == 0:
+        return {
+            "x0": x0,
+            "x1": x1,
+            "x2": x2,
+            "x3": x3,
+            "y0": y0,
+            "y1": y1,
+            "y2": y2,
+            "y3": y3,
+        }
+
+    # rotate coordinates if orientation is not 0
+
+    cx, cy = (int(width / 2), int(height / 2))
+
+    bbox_tuple = [
+        (x0, y0),
+        (x1, y1),
+        (x2, y2),
+        (x3, y3),
+    ]
+
+    rotated_bbox = []
+
+    for i, coord in enumerate(bbox_tuple):
+        M = cv2.getRotationMatrix2D((cx, cy), bbox["orientation"], 1.0)
+        v = [coord[0], coord[1], 1]
+        adjusted_coord = np.matmul(M, v)
+        rotated_bbox.insert(i, (adjusted_coord[0], adjusted_coord[1]))
+
+    result = [int(x) for t in rotated_bbox for x in t]
+
+    # make sure resulting bbox coordinates are within the range of the image
+    for i, n in enumerate(result):
+        if i % 2 == 0 and n > width:
+            result[i] = width
+        elif i % 2 == 1 and n > height:
+            result[i] = height
+        elif n < 0:
+            result[i] = 0
+
+    return {
+        "x0": result[0],
+        "x1": result[2],
+        "x2": result[4],
+        "x3": result[6],
+        "y0": result[1],
+        "y1": result[3],
+        "y2": result[5],
+        "y3": result[7],
+    }