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BigCodeBench / BigCodeBench v0.1.0_hf 5c94be10-cac4-5760-b36e-cb602ad1be96

Problem

Answer published by the source. Consult the official source to check your work against its answer.

complete prompt

import numpy as np
import cv2
import os

def task_func(image_path='image.jpg', threshold=128):
    """
    Read an RGB image, convert it to grayscale, binarize it using a given threshold, and return both the original and binarized images as numpy arrays.
    The function checks for the existence of the image file and validates the threshold value.

    Parameters:
    - image_path (str): Path to the image file. Defaults to 'image.jpg'.
    - threshold (int): Threshold value for binarization. Must be an integer in the range 0-255. Defaults to 128.

    Returns:
    - tuple: A tuple containing two numpy arrays. The first array represents the original grayscale image,
             and the second array represents the binarized image.

    Raises:
    - FileNotFoundError: If the image file does not exist at the specified path.
    - ValueError: If the threshold is not an integer or not in the range 0-255.

    Requirements:
    - opencv
    - numpy
    - os
    - PIL

    Example:
    >>> img_path = 'image.jpg'
    >>> create_dummy_image(img_path)
    >>> original_img_array, binary_img_array = task_func(img_path, 128)
    >>> os.remove(img_path)
    >>> original_img_array.shape, binary_img_array.shape # ((image_height, image_width), (image_height, image_width))
    ((20, 20), (20, 20))
    """

instruct prompt

Read an RGB image, convert it to grayscale, binarize it using a given threshold, and return both the original and binarized images as numpy arrays. The function checks for the existence of the image file and validates the threshold value.
The function should raise the exception for: FileNotFoundError: If the image file does not exist at the specified path. ValueError: If the threshold is not an integer or not in the range 0-255.
The function should output with:
    tuple: A tuple containing two numpy arrays. The first array represents the original grayscale image,
    and the second array represents the binarized image.
You should write self-contained code starting with:

Code

import numpy as np
import cv2
import os
def task_func(image_path='image.jpg', threshold=128):

code prompt

Code

import numpy as np
import cv2
import os
def task_func(image_path='image.jpg', threshold=128):

entry point

task_func

libs

  • numpy
  • cv2
  • os

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Source and history

task_id
5c94be10-cac4-5760-b36e-cb602ad1be96
task_key
default--v0~2e1~2e0~5fhf--5c94be10-cac4-5760-b36e-cb602ad1be96
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import