CodeSampleX

Exemple

pillow 12.3.0: PIL.ImageFilter

Échantillon vérifié pour pypi pillow 12.3.0: PIL.ImageFilter. Le contrat s'est exécuté sur python 3.12 · linux debian/x64 · docker et a réussi.

sha256:7b3ae3aa9ae7ca9ea799189a1d131f9a288ef9ba9f91f7fd114f806667b41d67

Ce réseau offre une seule chose : un échantillon qui compile. Il l'a exécuté dans un bac à sable et conservé le reçu signé. Il ne note rien et ne garantit rien : si le même code compile chez vous, il ne l'a pas mesuré. Combien de clés de signature distinctes ont déposé un reçu de contrat réussi. Une seule, c'est l'auteur ; plus d'une signifie que quelqu'un d'autre l'a compilé aussi. Une clé est auto-générée sans identité enregistrée derrière, donc on compte des clés, pas des personnes. MIT-0

Preuves d'exécution

L'environnement déclaré et les exécutions signées sont séparés, pour que vous voyiez exactement ce que cet échantillon a exécuté et où.

Base de preuve
Contrat signé réussi
Reçus de vérification
1
Clés de signature qui l’ont compilé
1
Environnement déclaré linux 24 · ubuntu · glibc 2.39 x64 pip

Environnements des exécutions de vérification

Environnement Contrat Étapes Exécution
python 3.12 · linux debian/x64 · docker ed25519:c1973797be207ac4 PASS compile:SKIPPED · contract:PASS · load:PASS · resolve:PASS
CONTAINER_RUN · python@1python:3.12-slim@sha256:09f7da3bc104…		 2026-09-14

Cas

HOW
Objectif
verify PIL.ImageFilter in pkg:pypi/pillow@12.3.0
Paquets
Symboles
  • PIL.ImageFilter
Créé
2026-09-14T03:46:14Z

Contrat

  1. PIL.ImageFilter.GaussianBlur blurs image pixels with configurable radius
  2. PIL.ImageFilter.BoxBlur performs box blurring with specified radius and validates parameters
  3. PIL.ImageFilter rank filters MinFilter, MedianFilter, and MaxFilter apply rank-based pixel selection
  4. PIL.ImageFilter.Kernel applies custom 2D convolution matrix with scale and offset
  5. PIL.ImageFilter.UnsharpMask sharpens an image using radius, percent, and threshold parameters
  6. PIL.ImageFilter predefined convolution filters produce filtered images preserving dimensions and mode

Fichiers

  • PROMPT.md
  • csx.json
  • pyproject.toml
  • requirements.txt
  • sample.py
  • spec.json
  • test/contract.py
  • uv.lock

Télécharger l’artefact source (tar.gz)

Code source

PROMPT.md
Clean-room public code sample — generation instructions

Write a brand-new, minimal, self-contained code sample in this clean-room directory.
Do not copy, paraphrase, or reference any existing project source. Work only from this spec.

A csx.json manifest scaffold already exists. Do not recreate it from memory. Preserve its case.goal, packages and symbols; fill its empty case.contract with exact assertions and correct its environment, commands and verifierAdapter for the files you generate.

Goal: verify PIL.ImageFilter in pkg:pypi/pillow@12.3.0
Kind: HOW

Use EXACTLY these public packages and versions:
  - pkg:pypi/pillow@12.3.0
Demonstrate these symbols/APIs:
  - PIL.ImageFilter

Rules:
  - One focused purpose; the smallest project that proves the goal.
  - Include a contract test (test/contract.*) that runs OFFLINE and exits 0 exactly when the goal behavior works.
  - Pin every dependency with a lockfile so resolution is reproducible.
  - No secrets, credentials, or tokens. No real URLs (only example.com or localhost). No absolute paths.
  - No personal names, emails, company names, or project identifiers of any kind.
  - No binaries and no generated output (node_modules, dist, target, venv, .git, .env).
  - Keep it under 200 files and 256KB packed.
csx.json
{"case":{"caseId":"case:sha256:d08c32d981661275b51b9d25704afbd8a3d051d025bbe6faeb86532ad61d5bfa","contract":["PIL.ImageFilter.GaussianBlur blurs image pixels with configurable radius","PIL.ImageFilter.BoxBlur performs box blurring with specified radius and validates parameters","PIL.ImageFilter rank filters MinFilter, MedianFilter, and MaxFilter apply rank-based pixel selection","PIL.ImageFilter.Kernel applies custom 2D convolution matrix with scale and offset","PIL.ImageFilter.UnsharpMask sharpens an image using radius, percent, and threshold parameters","PIL.ImageFilter predefined convolution filters produce filtered images preserving dimensions and mode"],"goal":"verify PIL.ImageFilter in pkg:pypi/pillow@12.3.0","kind":"HOW","packages":["pkg:pypi/pillow@12.3.0"],"schemaVersion":1,"symbols":["PIL.ImageFilter"]},"contractCommand":["python","test/contract.py"],"environment":{"arch":"x64","distro":"ubuntu","ecosystem":"pypi","libc":"glibc","libcVersion":"2.39","os":"linux","osVersionBucket":"24","packageManager":"pip","schemaVersion":1},"license":"MIT-0","packages":["pkg:pypi/pillow@12.3.0"],"schemaVersion":1,"subject":"pkg:pypi/pillow@12.3.0","symbols":["PIL.ImageFilter"],"verifierAdapter":"python@1"}
pyproject.toml
[project]
name = "verify-pillow-imagefilter"
version = "0.1.0"
requires-python = ">=3.10"
dependencies = [
    "pillow==12.3.0",
]
requirements.txt
pillow==12.3.0
sample.py
"""Demonstration of PIL.ImageFilter operations."""

from typing import Sequence, Tuple, Union
from PIL import Image, ImageFilter


def apply_gaussian_blur(image: Image.Image, radius: float = 2.0) -> Image.Image:
    """Apply GaussianBlur to an image with specified radius."""
    blur_filter = ImageFilter.GaussianBlur(radius=radius)
    return image.filter(blur_filter)


def apply_box_blur(image: Image.Image, radius: float = 1.0) -> Image.Image:
    """Apply BoxBlur to an image with specified radius."""
    blur_filter = ImageFilter.BoxBlur(radius=radius)
    return image.filter(blur_filter)


def apply_rank_filter(
    image: Image.Image,
    filter_type: str = "median",
    size: int = 3,
) -> Image.Image:
    """Apply rank-based filter (min, median, or max) to an image."""
    if filter_type == "min":
        rank_filter = ImageFilter.MinFilter(size=size)
    elif filter_type == "max":
        rank_filter = ImageFilter.MaxFilter(size=size)
    elif filter_type == "median":
        rank_filter = ImageFilter.MedianFilter(size=size)
    else:
        raise ValueError(f"Unsupported rank filter type: {filter_type}")
    return image.filter(rank_filter)


def apply_custom_kernel(
    image: Image.Image,
    size: Tuple[int, int],
    kernel: Sequence[Union[int, float]],
    scale: float = 1.0,
    offset: float = 0.0,
) -> Image.Image:
    """Apply a custom 2D convolution kernel filter to an image."""
    custom_kernel = ImageFilter.Kernel(size=size, kernel=kernel, scale=scale, offset=offset)
    return image.filter(custom_kernel)


def apply_unsharp_mask(
    image: Image.Image,
    radius: float = 2.0,
    percent: int = 150,
    threshold: int = 3,
) -> Image.Image:
    """Apply UnsharpMask filter to an image."""
    unsharp_filter = ImageFilter.UnsharpMask(
        radius=radius,
        percent=percent,
        threshold=threshold,
    )
    return image.filter(unsharp_filter)


def apply_builtin_filter(
    image: Image.Image,
    builtin_filter: ImageFilter.BuiltinFilter,
) -> Image.Image:
    """Apply a predefined builtin filter (e.g. BLUR, SHARPEN, EMBOSS)."""
    return image.filter(builtin_filter)
spec.json
{
  "schemaVersion": 1,
  "goal": "verify PIL.ImageFilter in pkg:pypi/pillow@12.3.0",
  "kind": "HOW",
  "packages": [
    "pkg:pypi/pillow@12.3.0"
  ],
  "symbols": [
    "PIL.ImageFilter"
  ]
}
test/contract.py
"""Contract verification test for PIL.ImageFilter."""

import os
import sys

# Ensure project root is in sys.path
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from PIL import Image, ImageFilter
from sample import (
    apply_box_blur,
    apply_builtin_filter,
    apply_custom_kernel,
    apply_gaussian_blur,
    apply_rank_filter,
    apply_unsharp_mask,
)


def test_gaussian_blur() -> None:
    """Assertion 1: PIL.ImageFilter.GaussianBlur blurs image pixels with configurable radius."""
    img = Image.new("L", (10, 10), 0)
    for y in range(10):
        for x in range(5, 10):
            img.putpixel((x, y), 255)

    gb = ImageFilter.GaussianBlur(radius=2.0)
    assert gb.radius == 2.0
    blurred = apply_gaussian_blur(img, radius=2.0)
    assert blurred.size == (10, 10)
    assert blurred.mode == "L"
    # Transition boundary pixel should have intermediate intensity
    assert 0 < blurred.getpixel((4, 5)) < 255


def test_box_blur() -> None:
    """Assertion 2: PIL.ImageFilter.BoxBlur performs box blurring with specified radius and validates parameters."""
    img = Image.new("L", (10, 10), 0)
    for y in range(10):
        for x in range(5, 10):
            img.putpixel((x, y), 255)

    bb = ImageFilter.BoxBlur(radius=1.0)
    assert bb.radius == 1.0
    blurred = apply_box_blur(img, radius=1.0)
    assert blurred.size == (10, 10)
    assert 0 < blurred.getpixel((4, 5)) < 255

    # Negative radius must raise ValueError
    try:
        ImageFilter.BoxBlur(radius=-1.0)
        assert False, "BoxBlur should raise ValueError for negative radius"
    except ValueError:
        pass


def test_rank_filters() -> None:
    """Assertion 3: PIL.ImageFilter rank filters MinFilter, MedianFilter, and MaxFilter apply rank-based pixel selection."""
    impulse = Image.new("L", (9, 9), 0)
    impulse.putpixel((4, 4), 255)

    # MinFilter removes isolated bright pixels
    min_img = apply_rank_filter(impulse, filter_type="min", size=3)
    assert min_img.getpixel((4, 4)) == 0

    # MaxFilter dilates bright pixels into the neighborhood
    max_img = apply_rank_filter(impulse, filter_type="max", size=3)
    assert max_img.getpixel((4, 4)) == 255
    assert max_img.getpixel((3, 3)) == 255
    assert max_img.getpixel((5, 5)) == 255

    # MedianFilter rejects isolated single-pixel impulse noise
    med_img = apply_rank_filter(impulse, filter_type="median", size=3)
    assert med_img.getpixel((4, 4)) == 0


def test_custom_kernel() -> None:
    """Assertion 4: PIL.ImageFilter.Kernel applies custom 2D convolution matrix with scale and offset."""
    impulse = Image.new("L", (9, 9), 0)
    impulse.putpixel((4, 4), 255)

    # Identity 3x3 convolution kernel
    identity_weights = [0, 0, 0, 0, 1, 0, 0, 0, 0]
    kernel_filter = ImageFilter.Kernel((3, 3), identity_weights, scale=1, offset=0)
    assert kernel_filter.name == "Kernel"
    assert kernel_filter.filterargs[0] == (3, 3)

    result = apply_custom_kernel(impulse, (3, 3), identity_weights, scale=1.0, offset=0.0)
    assert result.size == (9, 9)
    assert result.getpixel((4, 4)) == 255
    assert result.getpixel((3, 3)) == 0


def test_unsharp_mask() -> None:
    """Assertion 5: PIL.ImageFilter.UnsharpMask sharpens an image using radius, percent, and threshold parameters."""
    img = Image.new("RGB", (16, 16), (128, 128, 128))
    usm = ImageFilter.UnsharpMask(radius=2, percent=150, threshold=3)
    assert usm.radius == 2
    assert usm.percent == 150
    assert usm.threshold == 3

    result = apply_unsharp_mask(img, radius=2.0, percent=150, threshold=3)
    assert result.size == (16, 16)
    assert result.mode == "RGB"


def test_predefined_builtin_filters() -> None:
    """Assertion 6: PIL.ImageFilter predefined convolution filters produce filtered images preserving dimensions and mode."""
    img = Image.new("RGB", (16, 16), (100, 150, 200))
    predefined = [
        ImageFilter.BLUR,
        ImageFilter.SHARPEN,
        ImageFilter.EMBOSS,
        ImageFilter.FIND_EDGES,
        ImageFilter.CONTOUR,
        ImageFilter.DETAIL,
        ImageFilter.SMOOTH,
    ]
    for bf in predefined:
        assert issubclass(bf, ImageFilter.BuiltinFilter)
        res = apply_builtin_filter(img, bf)
        assert res.size == img.size
        assert res.mode == img.mode


def main() -> None:
    test_gaussian_blur()
    test_box_blur()
    test_rank_filters()
    test_custom_kernel()
    test_unsharp_mask()
    test_predefined_builtin_filters()
    print("All PIL.ImageFilter contract assertions passed.")


if __name__ == "__main__":
    main()
uv.lock
version = 1
revision = 3
requires-python = ">=3.10"

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[[package]]
name = "verify-pillow-imagefilter"
version = "0.1.0"
source = { virtual = "." }
dependencies = [
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[package.metadata]
requires-dist = [{ name = "pillow", specifier = "==12.3.0" }]

Seeder d'origine

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