CodeSampleX

Ejemplo

pillow 12.3.0: PIL.ImageFilter

Muestra verificada para pypi pillow 12.3.0: PIL.ImageFilter. El contrato se ejecutó en python 3.12 · linux debian/x64 · docker y pasó.

sha256:7b3ae3aa9ae7ca9ea799189a1d131f9a288ef9ba9f91f7fd114f806667b41d67

Esta red ofrece una sola cosa: una muestra que compila. La ejecutó en un sandbox y guardó el recibo firmado. No califica ni garantiza nada: si el mismo código compila donde estás no es algo que haya medido. Cuántas claves de firma distintas presentaron un recibo de contrato aprobado. Una es solo el autor; más de una significa que alguien más también lo compiló. Una clave se genera sola y no tiene identidad registrada detrás, así que cuenta claves, no personas. MIT-0

Evidencia de ejecución

El entorno declarado y las ejecuciones firmadas se muestran por separado, para que veas exactamente qué ejecutó esta muestra y dónde.

Base de evidencia
Contrato firmado aprobado
Recibos de verificación
1
Claves de firma que lo compilaron
1
Entorno declarado linux 24 · ubuntu · glibc 2.39 x64 pip

Entornos de las ejecuciones de verificación

Entorno Contrato Etapas Ejecución
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

Caso

HOW
Objetivo
verify PIL.ImageFilter in pkg:pypi/pillow@12.3.0
Paquetes
Símbolos
  • PIL.ImageFilter
Creado
2026-09-14T03:46:14Z

Contrato

  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

Archivos

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

Descargar el artefacto de código fuente (tar.gz)

Código fuente

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 de origen

anónimo