Hf Ready

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Weights filter=lfs diff=lfs merge=lfs -text
+Weights/* filter=lfs diff=lfs merge=lfs -text

.github/.devcontainer.json

@@ -0,0 +1,10 @@
+{
+    "name": "Python Development Container",
+    "image": "mcr.microsoft.com/devcontainers/base:ubuntu",
+    "features": {
+      "ghcr.io/devcontainers/features/python": {
+        "version": "latest"
+      }
+    },
+    "postCreateCommand": "pip install -e ."
+}

.github/ISSUE_TEMPLATE/bug_report.yaml

@@ -0,0 +1,75 @@
+name: "\U0001F41B Bug Report"
+description: Submit a bug report to help us improve
+title: "[BUG]: "
+projects:
+  - "project-name"
+labels:
+  - bug
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Thanks for taking the time to fill out this bug report!
+        Please make sure you have searched for a similar [issue](https://github.com/mozilla-ai/project-name/issues) before submitting a new one.
+
+  - type: textarea
+    id: description
+    attributes:
+      label: Description
+      description: A clear and concise description of what the bug is.
+      placeholder: |
+        When I try to...
+    validations:
+      required: true
+
+  - type: textarea
+    id: reproduction
+    attributes:
+      label: Reproduction
+      description: |
+        Provide  a numbered list of steps that one can follow to reproduce this behavior.
+      placeholder: |
+        Steps to reproduce the behavior:
+          1.
+          2.
+          3.
+    validations:
+      required: true
+
+  - type: textarea
+    id: logs
+    attributes:
+      label: Relevant log output
+      description: |
+        Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks.
+      render: shell
+    validations:
+      required: false
+
+  - type: textarea
+    id: expected-behavior
+    attributes:
+      label: Expected behavior
+      description: A clear description of what you would expect to happen.
+      placeholder: "I would expect to..."
+    validations:
+      required: true
+
+  - type: textarea
+    id: system-info
+    attributes:
+      label: System Info
+      description: Please share your system info with us.
+      placeholder: |
+        - OS: [e.g., macOS Sonoma]
+        - Project-name version: [e.g. commit SHA]
+    validations:
+      required: true
+
+  - type: checkboxes
+    id: search
+    attributes:
+      label: Have you searched for similar issues before submitting this one?
+      options:
+        - label: Yes, I have searched for similar issues
+          required: true

.github/ISSUE_TEMPLATE/feature_request.yaml

@@ -0,0 +1,55 @@
+name: "\U0001F680 Feature Request"
+description: Suggest an idea for this project
+title: "[FEATURE]: "
+projects:
+  - "Project-name"
+labels:
+  - enhancement
+body:
+  - type: markdown
+    attributes:
+      value: |
+        Thanks for taking the time to fill out this form!
+        Please make sure you have searched for a similar [issue](https://github.com/mozilla-ai/project-name/issues) before submitting a new one.
+
+  - type: textarea
+    id: motivation
+    attributes:
+      label: Motivation
+      description: |
+        A clear and concise description of the proposal and why this is important.
+      placeholder: |
+          I'm always frustrated when...
+    validations:
+      required: true
+
+  - type: textarea
+    id: alternatives
+    attributes:
+      label: Alternatives
+      description: |
+        A clear and concise description of any alternative solutions or features you've considered.
+      placeholder: |
+          I've considered...
+    validations:
+      required: false
+
+  - type: textarea
+    id: contribution
+    attributes:
+      label: Contribution
+      description: |
+        Is there any way that you could help, e.g. by submitting a PR?
+        Make sure to read the [contribution guidelines](https://github.com/mozilla-ai/project-name/blob/main/CONTRIBUTING.md).
+      placeholder: |
+        I could help by...
+    validations:
+      required: false
+
+  - type: checkboxes
+    id: search
+    attributes:
+      label: Have you searched for similar issues before submitting this one?
+      options:
+        - label: Yes, I have searched for similar issues
+          required: true

.github/pull_request_template.md

@@ -0,0 +1,27 @@
+# What's changing
+
+Provide a clear and concise description of the content changes you're proposing. List all the
+changes you are making to the content.
+
+> If this PR is related to an issue or closes one, please link it here.
+
+Refs #...
+Closes #...
+
+# How to test it
+
+Steps to test the changes:
+
+1.
+2.
+3.
+
+# Additional notes for reviewers
+
+Anything you'd like to add to help the reviewer understand the changes you're proposing.
+
+# I already...
+
+- [ ] Tested the changes in a working environment to ensure they work as expected
+- [ ] Added some tests for any new functionality
+- [ ] Updated the documentation (both comments in code and under `/docs`)

.github/workflows/docs.yaml

@@ -0,0 +1,48 @@
+name: Documentation
+
+on:
+  push:
+    branches: [main]
+    paths:
+      - mkdocs.yml
+      - 'docs/**'
+      - 'src/**'
+  pull_request:
+    paths:
+      - mkdocs.yml
+      - 'docs/**'
+      - 'src/**'
+  workflow_dispatch:
+
+jobs:
+  docs:
+    permissions:
+      contents: write
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check out the repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.10'
+          cache: "pip"
+
+      - name: Configure git
+        run: |
+          git config user.name 'github-actions[bot]'
+          git config user.email 'github-actions[bot]@users.noreply.github.com'
+
+      - name: Install requirements
+        run: pip install -e '.[docs]'
+
+      - name: Build docs
+        if: github.event_name == 'pull_request'
+        run: mkdocs build -s
+
+      - name: Publish docs
+        if: ${{ github.event_name == 'push' || github.event_name == 'workflow_dispatch' }}
+        run: mkdocs gh-deploy

.github/workflows/lint.yaml

@@ -0,0 +1,32 @@
+name: Lint
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+  workflow_dispatch:
+
+jobs:
+  run-linter:
+    timeout-minutes: 30
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Check out the repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.10'
+
+      - name: Install pre-commit
+        run: pip install pre-commit
+
+      - uses: actions/cache@v4
+        with:
+          path: ~/.cache/pre-commit/
+          key: pre-commit-4|${{ env.pythonLocation }}|${{ hashFiles('.pre-commit-config.yaml') }}
+
+      - name: pre-commit
+        run: pre-commit run --all-files

.github/workflows/package.yaml

@@ -0,0 +1,39 @@
+name: Create and publish a Docker image
+
+on:
+  push:
+    branches:
+      - 'main'
+    tags:
+      - 'v*'
+  workflow_dispatch:
+
+jobs:
+  build-and-push-image:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Log in to DockerHub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+
+      - name: Extract metadata (tags, labels) for Docker
+        id: meta
+        uses: docker/metadata-action@v5
+        with:
+          images: mzdotai/blueprint
+          flavor: |
+            latest=auto
+
+      - name: Build and push Docker image
+        id: push
+        uses: docker/build-push-action@v6
+        with:
+          context: .
+          push: true
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}

.github/workflows/release.yaml

@@ -0,0 +1,39 @@
+name: Release
+
+on:
+  release:
+    types: [published]
+  workflow_dispatch:
+
+jobs:
+  release:
+    environment: pypi
+    permissions:
+      contents: read
+      id-token: write
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check out the repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.10'
+
+      - name: Upgrade pip
+        run: |
+          pip install --upgrade pip
+          pip --version
+
+      - name: Install
+        run: python -m pip install build setuptools
+
+      - name: Build package
+        run: python -m build
+
+      - name: Upload package
+        if: github.event_name == 'release'
+        uses: pypa/gh-action-pypi-publish@release/v1

.github/workflows/tests.yaml

@@ -0,0 +1,34 @@
+name: Tests
+
+on:
+  push:
+    branches: [main]
+    paths:
+      - 'src/**'
+      - 'tests/**'
+  pull_request:
+    paths:
+      - 'src/**'
+      - 'tests/**'
+  workflow_dispatch:
+
+jobs:
+  run-tests:
+    timeout-minutes: 30
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Check out the repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.10'
+          cache: "pip"
+
+      - name: Install
+        run: pip install -e '.[tests]'
+
+      - name: Run tests
+        run: pytest -v tests

.gitignore

@@ -0,0 +1,164 @@
+# 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
+
+# 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
+
+# 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
+
+# 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
+.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/
+.vscode/

.pre-commit-config.yaml

@@ -0,0 +1,27 @@
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v5.0.0
+    hooks:
+      - id: check-added-large-files
+      - id: check-case-conflict
+      - id: check-json
+      - id: check-merge-conflict
+        args: ['--assume-in-merge']
+      - id: check-toml
+      - id: check-yaml
+      - id: end-of-file-fixer
+      - id: mixed-line-ending
+        args: ['--fix=lf']
+      - id: sort-simple-yaml
+      - id: trailing-whitespace
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: 'v0.7.3'
+    hooks:
+      - id: ruff
+        args: [--fix, --exit-non-zero-on-fix]
+      - id: ruff-format
+  - repo: https://github.com/codespell-project/codespell
+    rev: v2.3.0
+    hooks:
+      - id: codespell
+        exclude: CODE_OF_CONDUCT.md

CODE_OF_CONDUCT.md

@@ -0,0 +1,76 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+In the interest of fostering an open and welcoming environment, we as
+contributors and maintainers pledge to making participation in our project and
+our community a harassment-free experience for everyone, regardless of age, body
+size, disability, ethnicity, sex characteristics, gender identity and expression,
+level of experience, education, socio-economic status, nationality, personal
+appearance, race, religion, or sexual identity and orientation.
+
+## Our Standards
+
+Examples of behavior that contributes to creating a positive environment
+include:
+
+* Using welcoming and inclusive language
+* Being respectful of differing viewpoints and experiences
+* Gracefully accepting constructive criticism
+* Focusing on what is best for the community
+* Showing empathy towards other community members
+
+Examples of unacceptable behavior by participants include:
+
+* The use of sexualized language or imagery and unwelcome sexual attention or
+  advances
+* Trolling, insulting/derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or electronic
+  address, without explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+  professional setting
+
+## Our Responsibilities
+
+Project maintainers are responsible for clarifying the standards of acceptable
+behavior and are expected to take appropriate and fair corrective action in
+response to any instances of unacceptable behavior.
+
+Project maintainers have the right and responsibility to remove, edit, or
+reject comments, commits, code, wiki edits, issues, and other contributions
+that are not aligned to this Code of Conduct, or to ban temporarily or
+permanently any contributor for other behaviors that they deem inappropriate,
+threatening, offensive, or harmful.
+
+## Scope
+
+This Code of Conduct applies both within project spaces and in public spaces
+when an individual is representing the project or its community. Examples of
+representing a project or community include using an official project e-mail
+address, posting via an official social media account, or acting as an appointed
+representative at an online or offline event. Representation of a project may be
+further defined and clarified by project maintainers.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported by contacting the team at mozilla.ai. All
+complaints will be reviewed and investigated and will result in a response that
+is deemed necessary and appropriate to the circumstances. The project team is
+obligated to maintain confidentiality with regard to the reporter of an incident.
+Further details of specific enforcement policies may be posted separately.
+
+Project maintainers who do not follow or enforce the Code of Conduct in good
+faith may face temporary or permanent repercussions as determined by other
+members of the project's leadership.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
+available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
+
+[homepage]: https://www.contributor-covenant.org
+
+For answers to common questions about this code of conduct, see
+https://www.contributor-covenant.org/faq

CONTRIBUTING.md

@@ -0,0 +1,7 @@
+# Contributing to mozilla.ai Blueprints
+
+We welcome contributions of all kinds! Whether you're a seasoned developer or just starting out, your help is greatly appreciated.
+
+# How to Contribute
+
+---

Dockerfile

@@ -0,0 +1,36 @@
+FROM python:3.10-slim
+
+RUN pip3 install --no-cache-dir --upgrade pip
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    software-properties-common \
+    git \
+    ffmpeg \
+    libsm6 \
+    libxext6 \
+    cmake \
+    libgl1-mesa-glx
+
+RUN pip3 install streamlit
+
+RUN groupadd --gid 1000 appuser \
+    && useradd --uid 1000 --gid 1000 -ms /bin/bash appuser
+
+RUN mkdir -p /home/appuser/.cache /home/appuser/.config \
+    && chown -R appuser:appuser /home/appuser
+
+WORKDIR /home/appuser/blueprint
+COPY --chown=appuser:appuser . .
+
+RUN chmod +x demo/run.sh
+
+USER appuser
+
+ENV PATH="/home/appuser/.local/bin:${PATH}"
+RUN mkdir -p /home/appuser/tmp && chmod 777 /home/appuser/tmp
+ENV TMPDIR=/home/appuser/tmp
+
+RUN pip3 install -e .
+
+EXPOSE 8501
+ENTRYPOINT ["./demo/run.sh"]

LICENSE

@@ -0,0 +1,201 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
+      "You" (or "Your") shall mean an individual or Legal Entity
+      exercising permissions granted by this License.
+
+      "Source" form shall mean the preferred form for making modifications,
+      including but not limited to software source code, documentation
+      source, and configuration files.
+
+      "Object" form shall mean any form resulting from mechanical
+      transformation or translation of a Source form, including but
+      not limited to compiled object code, generated documentation,
+      and conversions to other media types.
+
+      "Work" shall mean the work of authorship, whether in Source or
+      Object form, made available under the License, as indicated by a
+      copyright notice that is included in or attached to the work
+      (an example is provided in the Appendix below).
+
+      "Derivative Works" shall mean any work, whether in Source or Object
+      form, that is based on (or derived from) the Work and for which the
+      editorial revisions, annotations, elaborations, or other modifications
+      represent, as a whole, an original work of authorship. For the purposes
+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
+      the Work and Derivative Works thereof.
+
+      "Contribution" shall mean any work of authorship, including
+      the original version of the Work and any modifications or additions
+      to that Work or Derivative Works thereof, that is intentionally
+      submitted to Licensor for inclusion in the Work by the copyright owner
+      or by an individual or Legal Entity authorized to submit on behalf of
+      the copyright owner. For the purposes of this definition, "submitted"
+      means any form of electronic, verbal, or written communication sent
+      to the Licensor or its representatives, including but not limited to
+      communication on electronic mailing lists, source code control systems,
+      and issue tracking systems that are managed by, or on behalf of, the
+      Licensor for the purpose of discussing and improving the Work, but
+      excluding communication that is conspicuously marked or otherwise
+      designated in writing by the copyright owner as "Not a Contribution."
+
+      "Contributor" shall mean Licensor and any individual or Legal Entity
+      on behalf of whom a Contribution has been received by Licensor and
+      subsequently incorporated within the Work.
+
+   2. Grant of Copyright License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      copyright license to reproduce, prepare Derivative Works of,
+      publicly display, publicly perform, sublicense, and distribute the
+      Work and such Derivative Works in Source or Object form.
+
+   3. Grant of Patent License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      (except as stated in this section) patent license to make, have made,
+      use, offer to sell, sell, import, and otherwise transfer the Work,
+      where such license applies only to those patent claims licensable
+      by such Contributor that are necessarily infringed by their
+      Contribution(s) alone or by combination of their Contribution(s)
+      with the Work to which such Contribution(s) was submitted. If You
+      institute patent litigation against any entity (including a
+      cross-claim or counterclaim in a lawsuit) alleging that the Work
+      or a Contribution incorporated within the Work constitutes direct
+      or contributory patent infringement, then any patent licenses
+      granted to You under this License for that Work shall terminate
+      as of the date such litigation is filed.
+
+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or
+          Derivative Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
+          that You distribute, all copyright, patent, trademark, and
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+
+      (d) If the Work includes a "NOTICE" text file as part of its
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+
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+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
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+      the terms of any separate license agreement you may have executed
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+   6. Trademarks. This License does not grant permission to use the trade
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+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
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+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
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+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
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+
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+
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+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.

README.md

@@ -1,10 +1,55 @@
 ---
-title: WIPDockerBP
-emoji: 🐨
-colorFrom: blue
-colorTo: indigo
+title: Wip1docker
+emoji: 👀
+colorFrom: green
+colorTo: purple
 sdk: docker
+app_port: 8501
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+
+
+<p align="center"><img src="./images/Blueprints-logo.png" width="35%" alt="Project logo"/></p>
+
+This blueprint guides you to ...
+
+### 👉 📖 For more detailed guidance on using this project, please visit our [Docs here](https://mozilla-ai.github.io/Blueprint-template/)
+
+### Built with
+- Python 3.10+
+- Open-Source Tool 1
+- Open-Source Tool 2
+- ...
+
+## Quick-start
+
+
+## How it Works
+
+
+## Pre-requisites
+
+- **System requirements**:
+  - OS: Windows, macOS, or Linux
+  - Python 3.10 or higher
+  - Minimum RAM:
+  - Disk space:
+
+- **Dependencies**:
+  - Dependencies listed in `pyproject.toml`
+
+
+## Troubleshooting
+
+
+## License
+
+This project is licensed under the Apache 2.0 License. See the [LICENSE](LICENSE) file for details.
+
+## Contributing
+
+Contributions are welcome! To get started, you can check out the [CONTRIBUTING.md](CONTRIBUTING.md) file.
+
+## WIP

Weights/shape_predictor_81_face_landmarks.dat

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8cae4375589dd915d9a0a881101bed1bbb4e9887e35e63b024388f1ca25ff869
+size 19743860

Weights/weights.tar

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5c100e98694faa776fcf71990377f9c4eca46568417339c06843cdcf2a78d35d
+size 141291061

demo/app.py

@@ -0,0 +1,224 @@
+import streamlit as st
+import warnings
+import cv2
+import dlib
+from pytorch_grad_cam.utils.image import show_cam_on_image
+from pytorch_grad_cam.utils.model_targets import ClassifierOutputTarget
+import numpy as np
+import torch
+from retinaface.pre_trained_models import get_model
+from blueprint.model import create_model, create_cam
+from blueprint.preprocess import crop_face, extract_face, extract_frames
+from pathlib import Path
+import tempfile
+import os
+import io
+
+warnings.filterwarnings('ignore')
+ROOT_DIR = Path(__file__).parent.parent
+
+def aca(img):
+    if len(img.shape) == 3 and img.shape[2] == 3:
+        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    img_float = img.astype(np.float32) / 255.0
+    channels = np.moveaxis(img_float, -1, 0)
+    sorted_idx = np.argsort(channels, axis=0)
+    sorted_values = np.take_along_axis(channels, sorted_idx, axis=0)
+    L = sorted_values[0]
+    M = sorted_values[1]
+    U = sorted_values[2]
+    eps = 1e-10
+    L_U = L / (U + eps)
+    L_M = L / (M + eps)
+    M_U = M / (U + eps)
+    kernel = np.array([[1, 0, 1], [0, -4, 0], [1, 0, 1]], dtype=np.float32)
+    L_U_filtered = cv2.filter2D(np.log(L_U + eps), -1, kernel)
+    L_M_filtered = cv2.filter2D(np.log(L_M + eps), -1, kernel)
+    M_U_filtered = cv2.filter2D(np.log(M_U + eps), -1, kernel)
+    residuals = np.abs(L_U_filtered) + np.abs(L_M_filtered) + np.abs(M_U_filtered)
+    p1, p99 = np.percentile(residuals[residuals > 0], (1, 99))
+    normalized = np.clip((residuals - p1) / (p99 - p1), 0, 1)
+    significant = normalized > 0.1
+    result = np.zeros((*residuals.shape, 3), dtype=np.float32)
+    result[significant, 0] = 255
+    intensity = np.expand_dims(normalized, -1)
+    result = result * intensity
+    return result.astype(np.uint8)
+
+def perform_ela(img, quality=95, scale=15):
+    buffer = io.BytesIO()
+    if len(img.shape) == 3 and img.shape[2] == 3:
+        working_img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
+    else:
+        working_img = img.copy()
+    img_bytes = cv2.imencode('.jpg', working_img, [cv2.IMWRITE_JPEG_QUALITY, quality])[1].tobytes()
+    buffer.write(img_bytes)
+    buffer.seek(0)
+    compressed_img = cv2.imdecode(np.frombuffer(buffer.read(), np.uint8), cv2.IMREAD_COLOR)
+    difference = np.abs(working_img.astype(np.float32) - compressed_img.astype(np.float32)) * scale
+    difference = np.clip(difference, 0, 255).astype(np.uint8)
+    difference_rgb = cv2.cvtColor(difference, cv2.COLOR_BGR2RGB)
+    luminance = np.sum(difference_rgb * np.array([0.299, 0.587, 0.114]), axis=2)
+    enhanced = np.zeros_like(difference_rgb)
+    for i in range(3):
+        enhanced[:,:,i] = np.minimum(difference_rgb[:,:,i] * 2, 255)
+    mask = luminance < np.mean(luminance) * 0.5
+    enhanced[mask] = [0, 0, 0]
+    gamma = 1.4
+    enhanced = (((enhanced / 255.0) ** (1/gamma)) * 255).astype(np.uint8)
+    return difference, enhanced
+
+@st.cache_resource
+def load_models():
+    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+    sbcl = create_model(str(ROOT_DIR / "Weights/weights.tar"), device)
+    face_detector = get_model("resnet50_2020-07-20", max_size=1024, device=device)
+    face_detector.eval()
+    cam_sbcl = create_cam(sbcl)
+    dlib_face_detector = dlib.get_frontal_face_detector()
+    dlib_face_predictor = dlib.shape_predictor(str(ROOT_DIR / "Weights/shape_predictor_81_face_landmarks.dat"))
+    return device, sbcl, face_detector, cam_sbcl, dlib_face_detector, dlib_face_predictor
+
+def predict_image(inp, models):
+    device, sbcl, face_detector, cam_sbcl = models[:4]
+    targets = [ClassifierOutputTarget(1)]
+    if inp is None:
+        return None, None
+    face_list = extract_face(inp, face_detector)
+    if len(face_list) == 0:
+        return None, None
+    try:
+        img = torch.tensor(face_list).to(device)
+        if device.type == 'cuda':
+            img = img.half()
+        img = img / 255
+        with torch.no_grad():
+            pred = sbcl(img).float().softmax(1)[:, 1].cpu().numpy().tolist()[0]
+            confidences = {'Real': 1 - pred, 'Fake': pred}
+        img.requires_grad = True
+        grayscale_cam = cam_sbcl(input_tensor=img, targets=targets, aug_smooth=True)
+        grayscale_cam = grayscale_cam[0, :]
+        cam_image = show_cam_on_image(face_list[0].transpose(1, 2, 0) / 255, grayscale_cam, use_rgb=True)
+        return confidences, cam_image
+    except Exception as e:
+        st.error(f"Error during prediction: {str(e)}")
+        return None, None
+
+def predict_video(inp, models):
+    device, sbcl, face_detector, cam_sbcl = models[:4]
+    targets = [ClassifierOutputTarget(1)]
+    if inp is None:
+        return None, None
+    try:
+        face_list, idx_list = extract_frames(inp, 10, face_detector)
+        if not face_list:
+            return None, None
+        img = torch.tensor(face_list).to(device)
+        if device.type == 'cuda':
+            img = img.half()
+        img = img / 255
+        with torch.no_grad():
+            pred = sbcl(img).float().softmax(1)[:, 1]
+            pred_list = []
+            idx_img = -1
+            for i in range(len(pred)):
+                if idx_list[i] != idx_img:
+                    pred_list.append([])
+                    idx_img = idx_list[i]
+                pred_list[-1].append(pred[i].item())
+            pred_res = np.array([max(p) for p in pred_list])
+            pred = float(pred_res.mean())
+        most_fake = np.argmax(pred_res)
+        img_for_cam = img[most_fake].unsqueeze(0)
+        img_for_cam.requires_grad = True
+        grayscale_cam = cam_sbcl(input_tensor=img_for_cam, targets=targets, aug_smooth=True)
+        grayscale_cam = grayscale_cam[0, :]
+        cam_image = show_cam_on_image(face_list[most_fake].transpose(1, 2, 0) / 255, grayscale_cam, use_rgb=True)
+        return {'Real': 1 - pred, 'Fake': pred}, cam_image
+    except Exception as e:
+        st.error(f"Error during video prediction: {str(e)}")
+        return None, None
+
+def main():
+    with st.sidebar:
+        st.title("Deepfake Detection")
+        tab = st.radio("Select Input Type:", ["Image", "Video"])
+        if tab == "Image":
+            st.subheader("Analysis Visualization Options")
+            show_gradcam = st.checkbox("GradCAM", value=True)
+            show_aca = st.checkbox("ACA", value=False)
+            show_ela = st.checkbox("ELA", value=False)
+            if show_ela:
+                quality = st.slider("JPEG Quality", 0, 100, 95)
+                scale = st.slider("ELA Scale", 1, 50, 15)
+
+    models = load_models()
+    
+    if tab == "Image":
+        st.header("Image Deepfake Detection")
+        num_cols = 1 + sum([show_gradcam, show_aca, show_ela])
+        cols = st.columns(num_cols)
+        col_idx = 0
+        
+        with cols[col_idx]:
+            st.subheader("Input")
+            image = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+            if image is not None:
+                image = cv2.imdecode(np.frombuffer(image.read(), np.uint8), cv2.IMREAD_COLOR)
+                image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+                st.image(image, caption="Input", use_container_width=True)
+                
+                if st.button("Analyze"):
+                    with st.spinner("Processing..."):
+                        confidences, cam_image = predict_image(image, models)
+                        if show_gradcam:
+                            col_idx += 1
+                            with cols[col_idx]:
+                                st.subheader("GradCAM")
+                                if confidences and cam_image is not None:
+                                    st.image(cam_image, caption="Model Focus", use_container_width=True)
+                                    for label, conf in confidences.items():
+                                        st.progress(conf, text=f"{label}: {conf*100:.1f}%")
+                                else:
+                                    st.warning("No face detected!")
+                        if show_aca:
+                            col_idx += 1
+                            with cols[col_idx]:
+                                st.subheader("ACA")
+                                color_map = aca(image)
+                                st.image(color_map, use_container_width=True)
+                        if show_ela:
+                            col_idx += 1
+                            with cols[col_idx]:
+                                st.subheader("ELA")
+                                _, ela_map = perform_ela(image, quality=quality, scale=scale)
+                                st.image(ela_map, use_container_width=True)
+    else:
+        st.header("Video Deepfake Detection")
+        col1, col2 = st.columns(2)
+        with col1:
+            st.subheader("Input")
+            video = st.file_uploader("Choose a video...", type=["mp4", "avi", "mov"])
+            if video is not None:
+                with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4', dir='/home/appuser') as tmp_file:
+                    tmp_file.write(video.read())
+                    video_path = tmp_file.name
+                st.video(video)
+                if st.button("Analyze"):
+                    with st.spinner("Processing..."):
+                        try:
+                            confidences, cam_image = predict_video(video_path, models)
+                            with col2:
+                                st.subheader("Results")
+                                if confidences and cam_image is not None:
+                                    st.image(cam_image, caption="GradCAM", use_container_width=True)
+                                    for label, conf in confidences.items():
+                                        st.progress(conf, text=f"{label}: {conf*100:.1f}%")
+                                else:
+                                    st.warning("No faces detected!")
+                        finally:
+                            if os.path.exists(video_path):
+                                os.unlink(video_path)
+
+if __name__ == "__main__":
+    main()

demo/run.sh

@@ -0,0 +1,27 @@
+#!/bin/bash
+
+APP_PID=
+stopRunningProcess() {
+    if test ! "${APP_PID}" = '' && ps -p ${APP_PID} > /dev/null ; then
+        > /proc/1/fd/1 echo "Stopping ${COMMAND_PATH} which is running with process ID ${APP_PID}"
+        kill -TERM ${APP_PID}
+        > /proc/1/fd/1 echo "Waiting for ${COMMAND_PATH} to process SIGTERM signal"
+        wait ${APP_PID}
+        > /proc/1/fd/1 echo "All processes have stopped running"
+    else
+        > /proc/1/fd/1 echo "${COMMAND_PATH} was not started when the signal was sent or it has already been stopped"
+    fi
+}
+
+trap stopRunningProcess EXIT TERM
+
+#HF workaround flags (ditch Xsrf flag locally)
+
+streamlit run ${HOME}/blueprint/demo/app.py \
+    --server.address=0.0.0.0 \
+    --server.enableCORS=false \
+    --server.enableXsrfProtection=false &
+
+APP_PID=${!}
+
+wait ${APP_PID}

docs/api.md

@@ -0,0 +1,3 @@
+# API Reference
+
+"::: blueprint.hello"

docs/assets/custom.css

@@ -0,0 +1,7 @@
+@import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&display=swap');
+
+:root {
+    --md-default-font: "Inter", sans-serif;
+    --md-code-font: "Fira Code", monospace;
+    --md-primary-font: "Inter", sans-serif;
+}

docs/customization.md

@@ -0,0 +1,22 @@
+# 🎨 **Customization Guide**
+
+This Blueprint is designed to be flexible and easily adaptable to your specific needs. This guide will walk you through some key areas you can customize to make the Blueprint your own.
+
+---
+
+## 🧠 **Changing the Model**
+
+
+
+## 📝 **Modifying the system Prompt**
+
+
+
+## 💡 Other Customization Ideas
+
+- other ideas..
+
+
+## 🤝 **Contributing to the Blueprint**
+
+Want to help improve or extend this Blueprint? Check out the **[Future Features & Contributions Guide](future-features-contributions.md)** to see how you can contribute your ideas, code, or feedback to make this Blueprint even better!

docs/future-features-contributions.md

@@ -0,0 +1,28 @@
+# 🚀 **Future Features & Contributions**
+
+This Blueprint is an evolving project designed to grow with the help of the open-source community. Whether you’re an experienced developer or just starting, there are many ways you can contribute and help shape the future of this tool.
+
+---
+
+## 🌟 **How You Can Contribute**
+
+### 🛠️ **Enhance the Blueprint**
+- Check the [Issues](https://github.com/mozilla-ai/blueprint-template/issues) page to see if there are feature requests you'd like to implement
+- Refer to our [Contribution Guide](https://github.com/mozilla-ai/blueprint-template/blob/main/CONTRIBUTING.md) for more details on contributions
+
+### 🎨 **Extensibility Ideas**
+
+This Blueprint is designed to be a foundation you can build upon. By extending its capabilities, you can open the door to new applications, improve user experience, and adapt the Blueprint to address other use cases. Here are a few ideas for how you can expand its potential:
+
+
+We’d love to see how you can enhance this Blueprint! If you create improvements or extend its capabilities, consider contributing them back to the project so others in the community can benefit from your work. Check out our [Contributions Guide](https://github.com/mozilla-ai/blueprint-template/blob/main/CONTRIBUTING.md) to get started!
+
+### 💡 **Share Your Ideas**
+Got an idea for how this Blueprint could be improved? You can share your suggestions through [GitHub Discussions](https://github.com/mozilla-ai/blueprint-template/discussions).
+
+### 🌍 **Build New Blueprints**
+This project is part of a larger initiative to create a collection of reusable starter code solutions that use open-source AI tools. If you’re inspired to create your own Blueprint, you can use the [Blueprint-template](https://github.com/new?template_name=Blueprint-template&template_owner=mozilla-ai) to get started.
+
+---
+
+Your contributions help make this Blueprint better for everyone 🎉

docs/getting-started.md

@@ -0,0 +1,9 @@
+Get started with this Blueprint using one of the options below:
+
+---
+
+### **Option 1:**
+
+
+
+###  **Option 2:**

docs/index.md

@@ -0,0 +1,39 @@
+# **Welcome to the Blueprint docs**
+
+Blueprints are customizable workflows that help developers build AI applications using open-source tools and models
+
+These docs are your companion to mastering this Blueprint.
+
+### Built with
+- Python 3.10+
+- Tool 1
+- Tool 2
+
+
+---
+
+### 🚀 **Get Started Quickly**
+#### _Start building the Blueprint in minutes:_
+- **[Getting Started](getting-started.md):** Quick setup and installation instructions.
+
+### 🔍 **Understand the System**
+#### _Dive deeper into how the Blueprint works:_
+- **[Step-by-Step Guide](step-by-step-guide.md):** A detailed breakdown of the system’s design and workflow.
+- **[API Reference](api.md):** Explore the technical details of the core modules.
+
+### 🎨 **Make It Yours**
+#### _Customize the Blueprint to fit your needs:_
+- **[Customization Guide](customization.md):** Tailor project parameters to fit your needs
+
+### 🌟 **Join the Community**
+#### _Help shape the future of Blueprints:_
+- **[Future Features & Contributions](future-features-contributions.md):** Learn about exciting upcoming features and how to contribute to the project.
+
+
+Have more questions? Reach out to us on [GitHub Discussions](https://github.com/mozilla-ai/blueprint-template/discussions).
+
+---
+
+## **Why Blueprints?**
+
+Blueprints are more than starter code—they’re your gateway to building AI-powered solutions with confidence. With step-by-step guidance, modular design, and open-source tools, we make AI accessible for developers of all skill levels.

docs/step-by-step-guide.md

@@ -0,0 +1,27 @@
+# **Step-by-Step Guide: How this Blueprint Works**
+
+
+---
+
+## **Overview**
+
+
+---
+
+## **Step 1**
+
+
+## **Step 2**
+
+
+## **Step 3**
+
+
+
+## 🎨 **Customizing the Blueprint**
+
+To better understand how you can tailor this Blueprint to suit your specific needs, please visit the **[Customization Guide](customization.md)**.
+
+## 🤝 **Contributing to the Blueprint**
+
+Want to help improve or extend this Blueprint? Check out the **[Future Features & Contributions Guide](future-features-contributions.md)** to see how you can contribute your ideas, code, or feedback to make this Blueprint even better!

mkdocs.yml

@@ -0,0 +1,46 @@
+site_name: Blueprints Docs
+repo_url: https://github.com/mozilla-ai/blueprint-template
+repo_name: blueprint-template
+
+nav:
+  - Home: index.md
+  - Getting Started: getting-started.md
+  - Step-by-Step Guide: step-by-step-guide.md
+  - Customization Guide: customization.md
+  - API Reference: api.md
+  - Future Features & Contributions: future-features-contributions.md
+
+theme:
+  icon:
+    repo: fontawesome/brands/github
+  name: material
+  palette:
+    - scheme: default
+      primary: "#005F6F"
+      toggle:
+        icon: material/lightbulb
+        name: Switch to dark mode
+    - scheme: slate
+      primary: "#005F6F"
+      toggle:
+        icon: material/lightbulb-outline
+        name: Switch to light mode
+  extra_css:
+    - assets/custom.css
+
+markdown_extensions:
+  - pymdownx.highlight:
+      anchor_linenums: true
+      line_spans: __span
+      pygments_lang_class: true
+  - pymdownx.inlinehilite
+  - pymdownx.snippets
+  - pymdownx.superfences
+
+plugins:
+- search
+- mkdocstrings:
+    handlers:
+      python:
+        options:
+          show_root_heading: true

pyproject.toml

@@ -0,0 +1,41 @@
+[build-system]
+requires = ["setuptools>=48", "setuptools_scm[toml]>=6.3.1"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "blueprint"  
+readme = "README.md"
+license = {text = "Apache-2.0"}
+requires-python = ">=3.10"
+dynamic = ["version"]
+dependencies = [
+    "streamlit",
+    "torch>=2.0.0",
+    "opencv-python",
+    "numpy",
+    "dlib-binary",
+    "retinaface-pytorch",
+    "efficientnet_pytorch",
+    "albumentations",
+    "grad-cam==1.4.8",
+    "Pillow"
+]
+
+[project.optional-dependencies]
+docs = [
+    "mkdocs",
+    "mkdocs-material",
+    "mkdocstrings-python",
+]
+
+tests = [
+    "pytest>=8,<9",
+    "pytest-sugar>=0.9.6",
+]
+
+[tool.setuptools.packages.find]
+exclude = ["tests", "tests.*"]
+where = ["src"]
+namespaces = false
+
+[tool.setuptools_scm]

src/blueprint/hello.py

@@ -0,0 +1,8 @@
+def hello() -> str:
+    """
+    Greets the world
+
+    Returns:
+        str: "Hello, world!"
+    """
+    return "Hello, world!"

src/blueprint/model.py

@@ -0,0 +1,38 @@
+import torch
+from torch import nn
+from efficientnet_pytorch import EfficientNet
+from pytorch_grad_cam import GradCAMElementWise
+from pytorch_grad_cam.utils.model_targets import ClassifierOutputTarget
+
+class Detector(nn.Module):
+    def __init__(self):
+        super(Detector, self).__init__()
+        self.net = EfficientNet.from_pretrained("efficientnet-b4", advprop=True, num_classes=2)
+
+    def forward(self, x):
+        x = self.net(x)
+        return x
+
+def create_model(path="Weights/94_0.9485_val.tar", device=torch.device('cpu')):
+    model = Detector()
+    try:
+        if device.type == 'cuda':
+            model = model.half()
+    except:
+        model = model.float()
+    model = model.to(device)
+    if device == torch.device('cpu'):
+        cnn_sd = torch.load(path, map_location=torch.device('cpu'))["model"]
+    else:
+        cnn_sd = torch.load(path)["model"]
+    model.load_state_dict(cnn_sd)
+    model.eval()
+    return model
+
+def create_cam(model):
+    target_layers = [model.net._blocks[-1]]
+    targets = [ClassifierOutputTarget(1)]
+    cam_algorithm = GradCAMElementWise
+    use_cuda = torch.cuda.is_available() and next(model.parameters()).is_cuda
+    cam = cam_algorithm(model=model, target_layers=target_layers, use_cuda=use_cuda)
+    return cam

src/blueprint/preprocess.py

@@ -0,0 +1,119 @@
+import numpy as np
+import cv2
+
+def extract_frames(filename, num_frames, model, image_size=(380, 380)):
+    cap = cv2.VideoCapture(filename)
+    if not cap.isOpened():
+        return [], []
+    
+    frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+    frame_idxs = np.linspace(0, frame_count - 1, min(num_frames, frame_count), dtype=int)
+    
+    croppedfaces, idx_list = [], []
+    for idx in frame_idxs:
+        ret = cap.set(cv2.CAP_PROP_POS_FRAMES, idx)
+        if not ret:
+            continue
+        ret, frame = cap.read()
+        if not ret:
+            continue
+            
+        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        faces = extract_face(frame, model, image_size)
+        if faces:
+            croppedfaces.extend(faces)
+            idx_list.extend([idx] * len(faces))
+            
+    cap.release()
+    return croppedfaces, idx_list
+
+def extract_face(frame, model, image_size=(380, 380)):
+    faces = model.predict_jsons(frame)
+    if len(faces[0]['bbox']) == 0:
+        scale_factor = 0.5
+        small_frame = cv2.resize(frame, None, fx=scale_factor, fy=scale_factor)
+        faces = model.predict_jsons(small_frame)
+        if len(faces[0]['bbox']) == 0:
+            return []
+        for face in faces:
+            face['bbox'] = [coord/scale_factor for coord in face['bbox']]
+    
+    croppedfaces = []
+    for face_idx in range(len(faces)):
+        x0, y0, x1, y1 = faces[face_idx]['bbox']
+        bbox = np.array([[x0, y0], [x1, y1]])
+        face = crop_face(frame, None, bbox, False, crop_by_bbox=True, only_img=True, phase='test')
+        croppedfaces.append(cv2.resize(face, dsize=image_size).transpose((2, 0, 1)))
+    
+    return croppedfaces
+
+def crop_face(img, landmark=None, bbox=None, margin=False, crop_by_bbox=True, abs_coord=False, only_img=False, phase='test'):
+    assert phase in ['train', 'val', 'test']
+    assert landmark is not None or bbox is not None
+    
+    H, W = len(img), len(img[0])
+    
+    if crop_by_bbox:
+        x0, y0 = bbox[0]
+        x1, y1 = bbox[1]
+        w = x1 - x0
+        h = y1 - y0
+        w0_margin = w/4
+        w1_margin = w/4
+        h0_margin = h/4
+        h1_margin = h/4
+    else:
+        x0, y0 = landmark[:68,0].min(), landmark[:68,1].min()
+        x1, y1 = landmark[:68,0].max(), landmark[:68,1].max()
+        w = x1 - x0
+        h = y1 - y0
+        w0_margin = w/8
+        w1_margin = w/8
+        h0_margin = h/2
+        h1_margin = h/5
+    
+    if margin:
+        w0_margin *= 4
+        w1_margin *= 4
+        h0_margin *= 2
+        h1_margin *= 2
+    elif phase == 'train':
+        rand_factor = np.random.rand(4) * 0.6 + 0.2
+        w0_margin *= rand_factor[0]
+        w1_margin *= rand_factor[1]
+        h0_margin *= rand_factor[2]
+        h1_margin *= rand_factor[3]
+    else:
+        w0_margin *= 0.5
+        w1_margin *= 0.5
+        h0_margin *= 0.5
+        h1_margin *= 0.5
+            
+    y0_new = max(0, int(y0-h0_margin))
+    y1_new = min(H, int(y1+h1_margin)+1)
+    x0_new = max(0, int(x0-w0_margin))
+    x1_new = min(W, int(x1+w1_margin)+1)
+    
+    img_cropped = img[y0_new:y1_new, x0_new:x1_new]
+    
+    if only_img:
+        return img_cropped
+        
+    if landmark is not None:
+        landmark_cropped = np.zeros_like(landmark)
+        for i, (p,q) in enumerate(landmark):
+            landmark_cropped[i] = [p-x0_new, q-y0_new]
+    else:
+        landmark_cropped = None
+        
+    if bbox is not None:
+        bbox_cropped = np.zeros_like(bbox)
+        for i, (p,q) in enumerate(bbox):
+            bbox_cropped[i] = [p-x0_new, q-y0_new]
+    else:
+        bbox_cropped = None
+
+    if abs_coord:
+        return img_cropped, landmark_cropped, bbox_cropped, (y0-y0_new, x0-x0_new, y1_new-y1, x1_new-x1), y0_new, y1_new, x0_new, x1_new
+    else:
+        return img_cropped, landmark_cropped, bbox_cropped, (y0-y0_new, x0-x0_new, y1_new-y1, x1_new-x1)

tests/unit/test_hello.py

@@ -0,0 +1,5 @@
+from blueprint.hello import hello
+
+
+def test_hello():
+    assert hello() == "Hello, world!"