pax_global_header00006660000000000000000000000064144101246050014507gustar00rootroot0000000000000052 comment=9706ca2168b32a15388a616b4795e8c0a8ff8297 thumbhash-py-0.1.2/000077500000000000000000000000001441012460500141205ustar00rootroot00000000000000thumbhash-py-0.1.2/.github/000077500000000000000000000000001441012460500154605ustar00rootroot00000000000000thumbhash-py-0.1.2/.github/workflows/000077500000000000000000000000001441012460500175155ustar00rootroot00000000000000thumbhash-py-0.1.2/.github/workflows/build-publish.yml000066400000000000000000000016641441012460500230120ustar00rootroot00000000000000name: Build and Publish on: push: tags: - v* jobs: build: name: Build wheels runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 - name: Install build dependencies run: python -m pip install --upgrade hatch - name: Build run: python -m hatch build - uses: actions/upload-artifact@v3 with: name: artifacts path: dist/* if-no-files-found: error publish: name: Publish release needs: - build runs-on: ubuntu-latest steps: - uses: actions/download-artifact@v3 with: name: artifacts path: dist - name: Push build artifacts to PyPI uses: pypa/gh-action-pypi-publish@v1.6.4 with: skip_existing: true user: __token__ password: ${{ secrets.PYPI_API_TOKEN }} - name: Publish Github Release uses: softprops/action-gh-release@v1 with: files: dist/* thumbhash-py-0.1.2/.gitignore000066400000000000000000000066451441012460500161230ustar00rootroot00000000000000# Created by https://www.toptal.com/developers/gitignore/api/python # Edit at https://www.toptal.com/developers/gitignore?templates=python ### Python ### # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] *$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/#use-with-ide .pdm.toml # 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/ ### Python Patch ### # Poetry local configuration file - https://python-poetry.org/docs/configuration/#local-configuration poetry.toml # ruff .ruff_cache/ # LSP config files pyrightconfig.json # End of https://www.toptal.com/developers/gitignore/api/pythonthumbhash-py-0.1.2/LICENSE000066400000000000000000000020471441012460500151300ustar00rootroot00000000000000MIT License Copyright (c) 2023 Justin Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. thumbhash-py-0.1.2/README.md000066400000000000000000000020351441012460500153770ustar00rootroot00000000000000 # thumbhash-py A Python port of the [thumbhash](https://github.com/evanw/thumbhash) encoder by [Evan Wallace](https://github.com/evanw) ## Installation Install thumbhash with pip ```sh pip install thumbhash-py ``` Optionally install with pillow support: ```sh pip install thumbhash-py[pillow] ``` ## Usage Encode a RGBA array to a ThumbHash ```py from thumbhash import rgba_to_thumb_hash rgba = [100, 85, 15, 255, 100, 84, 32, 255,...] width = 100 height = 75 thumb_hash = rgba_to_thumb_hash(rgba, width, height) # [86, 8, 10, 13, 128, 22, 234, 86, 111, 117, ...] ``` Open an image using pillow, scale down to max dimensions of 100x100 and encode to a ThumbHash ```py from thumbhash import image_to_thumb_hash thumb_hash = image_to_thumb_hash('image.jpg') # [86, 8, 10, 13, 128, 22, 234, 86, 111, 117, ...] ``` ## Features As of now this library only handles the conversion of images to hashes, not the reverse. thumbhash-py-0.1.2/pyproject.toml000066400000000000000000000031451441012460500170370ustar00rootroot00000000000000[build-system] requires = ["hatchling"] build-backend = "hatchling.build" [project] name = "thumbhash-py" description = 'A very compact representation of an image placeholder' readme = "README.md" requires-python = ">=3.7" license = "MIT" keywords = [] authors = [ { name = "Justin", email = "justin@forlenza.co" }, ] classifiers = [ "Development Status :: 4 - Beta", "Programming Language :: Python", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy", ] dependencies = [ ] dynamic = ["version"] [project.optional-dependencies] pillow = [ "pillow" ] [project.urls] Documentation = "https://github.com/justinforlenza/thumbhash-py#readme" Issues = "https://github.com/justinforlenza/thumbhash-py/issues" Source = "https://github.com/justinforlenza/thumbhash-py" [tool.hatch.version] path = "thumbhash/__about__.py" [tool.hatch.envs.default] dependencies = [ "pytest", "pytest-cov", ] [tool.hatch.envs.default.scripts] cov = "pytest --cov-report=term-missing --cov-config=pyproject.toml --cov=thumbhash --cov=tests {args}" no-cov = "cov --no-cov {args}" [[tool.hatch.envs.test.matrix]] python = ["37", "38", "39", "310", "311"] [tool.coverage.run] branch = true parallel = true omit = [ "thumbhash/__about__.py", ] [tool.coverage.report] exclude_lines = [ "no cov", "if __name__ == .__main__.:", "if TYPE_CHECKING:", ] thumbhash-py-0.1.2/requirements.txt000066400000000000000000000000061441012460500174000ustar00rootroot00000000000000pillowthumbhash-py-0.1.2/thumbhash/000077500000000000000000000000001441012460500161035ustar00rootroot00000000000000thumbhash-py-0.1.2/thumbhash/__about__.py000066400000000000000000000000251441012460500203600ustar00rootroot00000000000000__version__ = '0.1.2'thumbhash-py-0.1.2/thumbhash/__init__.py000066400000000000000000000120561441012460500202200ustar00rootroot00000000000000import math from typing import List, Tuple from pathlib import Path from itertools import chain try: from PIL import Image, ImageOps has_pil = True except ImportError: has_pil = False def rgba_to_thumb_hash(w: int, h: int, rgba: List[int]) -> List[int]: ''' Encodes an RGBA image to a ThumbHash ''' if w > 100 or h > 100: raise ValueError(f"{w}x{h} doesn't fit in 100x100") avg_r, avg_g, avg_b, avg_a = 0, 0, 0, 0 for i in range(w * h): j = i * 4 alpha = rgba[j + 3] / 255 avg_r += alpha / 255 * rgba[j] avg_g += alpha / 255 * rgba[j + 1] avg_b += alpha / 255 * rgba[j + 2] avg_a += alpha if avg_a: avg_r /= avg_a avg_g /= avg_a avg_b /= avg_a has_alpha = avg_a < w * h l_limit = 5 if has_alpha else 7 lx = max(1, round(l_limit * w / max(w, h))) ly = max(1, round(l_limit * h / max(w, h))) l, p, q, a = [], [], [], [] for i in range(w * h): j = i * 4 alpha = rgba[j + 3] / 255 r = avg_r * (1 - alpha) + alpha / 255 * rgba[j] g = avg_g * (1 - alpha) + alpha / 255 * rgba[j + 1] b = avg_b * (1 - alpha) + alpha / 255 * rgba[j + 2] l.append((r + g + b) / 3) p.append((r + g) / 2 - b) q.append(r - g) a.append(alpha) def encode_channel(channel: list, nx: int, ny: int): dc = 0 ac = [] scale = 0 fx = [0] * w for cy in range(ny): cx = 0 while cx * ny < nx * (ny - cy): f = 0.0 for x in range(w): fx[x] = math.cos(math.pi / w * cx * (x + 0.5)) for y in range(h): fy = math.cos(math.pi / h * cy * (y + 0.5)) for x in range(w): f += channel[x + y * w] * fx[x] * fy f /= (w * h) if cx > 0 or cy > 0: ac.append(f) scale = max(scale, abs(f)) else: dc = f cx += 1 if scale: for i in range(len(ac)): ac[i] = 0.5 + 0.5 / scale * ac[i] return dc, ac, scale l_dc, l_ac, l_scale = encode_channel(l, max(3, lx), max(3, ly)) p_dc, p_ac, p_scale = encode_channel(p, 3, 3) q_dc, q_ac, q_scale = encode_channel(q, 3, 3) a_dc, a_ac, a_scale = encode_channel(a, 5, 5) if has_alpha else 1.0, [], 1.0 is_landscape = w > h header24 = round(63 * l_dc) | (round(31.5 + 31.5 * p_dc) << 6) | (round(31.5 + 31.5 * q_dc) << 12) | (round(31 * l_scale) << 18) | (has_alpha << 23) header16 = (ly if is_landscape else lx) | (round(63 * p_scale) << 3) | (round(63 * q_scale) << 9) | (is_landscape << 15) thumb_hash = [header24 & 255, (header24 >> 8) & 255, header24 >> 16, header16 & 255, header16 >> 8] is_odd = False if has_alpha: thumb_hash.append(round(15 * a_dc) | (round(15 * a_scale) << 4)) for ac in [l_ac, p_ac, q_ac]: for f in ac: u = int(round(15.0 * f)) if is_odd: thumb_hash[-1] |= u << 4 else: thumb_hash.append(u) is_odd = not is_odd if has_alpha: for f in a_ac: u = int(round(15.0 * f)) if is_odd: thumb_hash[-1] |= u << 4 else: thumb_hash.append(u) is_odd = not is_odd return thumb_hash def image_to_thumb_hash(fp: str | bytes | Path) -> List[int]: ''' Opens given image file and encodes to a ThumbHash ''' if not has_pil: raise ImportError('Pillow not installed, please re-install with pillow extra') img = Image.open(fp) img = img.convert('RGBA') img.thumbnail((100, 100)) img = ImageOps.exif_transpose(img) rgba_2d = list(img.getdata()) rgba = list(chain(*rgba_2d)) thumb_hash = rgba_to_thumb_hash(img.width, img.height, rgba) return thumb_hash def thumb_hash_to_average_rgba(thumb_hash: List[int]) -> Tuple[int]: ''' Extracts the average color from a ThumbHash ''' if len(thumb_hash) < 5: return None header = thumb_hash[0] | (thumb_hash[1] << 8) | (thumb_hash[2] << 16) l = (header & 63) / 63.0 p = ((header >> 6) & 63) / 31.5 - 1.0 q = ((header >> 12) & 63) / 31.5 - 1.0 has_alpha = (header >> 23) != 0 a = (thumb_hash[5] & 15) / 15.0 if has_alpha else 1.0 b = l - 2.0 / 3.0 * p r = (3.0 * l - b + q) / 2.0 g = r - q return ( max(0.0, min(1.0, r)), max(0.0, min(1.0, g)), max(0.0, min(1.0, b)), a ) def thumb_hash_to_approximate_aspect_ratio(thumb_hash: List[int]) -> float: ''' Extracts approxmiate aspect ratio of a ThumbHash ''' if len(thumb_hash) < 5: return None has_alpha = (thumb_hash[2] & 0x80) != 0 l_max = 5 if has_alpha else 7 l_min = thumb_hash[3] & 7 is_landscape = (thumb_hash[4] & 0x80) != 0 lx = l_max if is_landscape else l_min ly = l_min if is_landscape else l_max return lx / ly