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import numpy as np
import gradio as gr
from pathlib import Path
import os
from PIL import Image
def prime_factors(n):
"""
Compute the prime factorization of a positive integer.
Args:
n (int): The integer to factorize. Must be greater than 1.
Returns:
List[int]: A list of prime factors in ascending order.
Raises:
ValueError: If n is not greater than 1.
"""
n = int(n)
if n <= 1:
raise ValueError("Input must be an integer greater than 1.")
factors = []
while n % 2 == 0:
factors.append(2)
n //= 2
divisor = 3
while divisor * divisor <= n:
while n % divisor == 0:
factors.append(divisor)
n //= divisor
divisor += 2
if n > 1:
factors.append(n)
return factors
def generate_cheetah_image():
"""
Generate a cheetah image.
Returns:
The generated cheetah image.
"""
return Path(os.path.dirname(__file__)) / "cheetah.jpg"
def image_orientation(image: Image.Image) -> str:
"""
Returns whether image is portrait or landscape.
Args:
image (Image.Image): The image to check.
Returns:
str: "Portrait" if image is portrait, "Landscape" if image is landscape.
"""
return "Portrait" if image.height > image.width else "Landscape"
def sepia(input_img):
"""
Apply a sepia filter to the input image.
Args:
input_img (str): The input image to apply the sepia filter to.
Returns:
The sepia filtered image.
"""
sepia_filter = np.array([
[0.393, 0.769, 0.189],
[0.349, 0.686, 0.168],
[0.272, 0.534, 0.131]
])
sepia_img = input_img.dot(sepia_filter.T)
sepia_img /= sepia_img.max()
return sepia_img
demo = gr.TabbedInterface(
[
gr.Interface(prime_factors, gr.Textbox(), gr.Textbox(), api_name="prime_factors"),
gr.Interface(generate_cheetah_image, None, gr.Image(), api_name="generate_cheetah_image"),
gr.Interface(image_orientation, gr.Image(type="pil"), gr.Textbox(), api_name="image_orientation"),
gr.Interface(sepia, gr.Image(), gr.Image(), api_name="sepia"),
],
[
"Prime Factors",
"Cheetah Image",
"Image Orientation Checker",
"Sepia Filter",
]
)
if __name__ == "__main__":
demo.launch(mcp_server=True)
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