Initial Commit

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$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
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+# Sphinx documentation
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+# PyBuilder
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+target/
+
+# Jupyter Notebook
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+
+# 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
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+#Pipfile.lock
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+# UV
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+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#uv.lock
+
+# poetry
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+#   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
+
+# 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
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
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+/site
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+# mypy
+.mypy_cache/
+.dmypy.json
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+.pytype/
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+cython_debug/
+
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+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+.idea/
+
+# Ruff stuff:
+.ruff_cache/
+
+# PyPI configuration file
+.pypirc

main.py

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+import streamlit as st
+from transformers import pipeline
+
+st.logo("NLP_Group_logo.svg", size="large")
+main_page = st.Page("main_page.py", title="Main Page", icon="🏠")
+sketch2diagram_page = st.Page("sketch2diagram.py", title="Sketch2Diagram", icon="🖼️")
+# Add pages to the main page
+pg = st.navigation([main_page, sketch2diagram_page])
+
+pg.run()
+
+@st.cache_resource
+def get_model():
+    # Load the model here
+    model = pipeline("image-to-text", model="itsumi-st/imgtikz_qwen2vl")
+    return model

main_page.py

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+import streamlit as st
+
+st.title("Tohoku NLP Group - Language and Information Science Laboratory ")
+st.write("Welcome to the Language and Information Science Laboratory!")
+st.write("We are working on various projects and research focused on Visual Language Models.")

requirements.txt

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+streamlit~=1.43.2
+transformers~=4.50.0
+pillow~=11.1.0

sketch2diagram.py

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+import streamlit as st
+from PIL import Image
+
+from main import get_model
+
+# Sidebar Setup
+st.sidebar.title("Model Configuration")
+inference_strat = st.sidebar.selectbox("Inference Strategy", ["Iterative", "Multi-candidate"],
+                                       help="Choose the inference strategy for the model. Iterative generates one candidate at a time until an output compiles, while Multi-candidate generates multiple candidates in parallel.")
+
+# Introduction Section
+st.title("Sketch2Diagram")
+
+st.write("This is a runnable demo of ImgTikZ model introduced in the Sketch2Diagram paper.")
+st.write("Please refer to the [original paper](https://openreview.net/pdf?id=KvaDHPhhir) for more details.")
+st.write("The model is trained to convert sketches into TikZ code, which can be used to generate vectorized diagrams.")
+st.write(f"Inference Strategy: {inference_strat}")
+
+# User Input Section
+st.subheader("Upload your sketch")
+
+input_method = st.selectbox("Input Method", ["Upload", "Camera"],
+                            help="Choose how you want to input your sketch. You can either upload an image or take a picture using your webcam.")
+
+input_file = None
+if input_method == "Camera":
+    input_file = st.camera_input("Take a picture of your sketch")
+    # Implement camera input functionality here
+else:
+    input_file = st.file_uploader("Upload an image of your sketch", type=["png", "jpg", "jpeg"])
+
+generate_command = None
+# Display the uploaded image
+if input_file is not None:
+    st.image(input_file, caption="Uploaded Sketch")
+    generate_command = st.button("Generate TikZ Code")
+
+if generate_command:
+    model = get_model()
+    image = Image.open(input_file)
+    with st.spinner("Generating TikZ code..."):
+        output = model(image)
+
+    tikz_code = output[0]['generated_text']
+    st.subheader("Generated TikZ Code")
+    st.code(tikz_code, language='latex')