SingleStore April Challenge: Haiku ASCII

1!pip install matplotlib --quiet

1import numpy as np2import matplotlib.pyplot as plt3from matplotlib.colors import LinearSegmentedColormap4import matplotlib.image as mpimg  # Import for loading the logo image5import requests  # Import requests to download the logo6from PIL import Image  # Import PIL to handle the image7from io import BytesIO  # Import BytesIO to handle the image as a byte stream8
9# Seasonal Transition Haiku Generator10def generate_seasonal_transition_haiku():11    seasons = ["Winter", "Spring", "Summer", "Fall"]12    transitions = {13        ("Winter", "Spring"): [14            "Data thaws with grace,",  # 5 syllables15            "Queries swiftly bloom, unfurl,",  # 7 syllables16            "Insight crisp and clear."  # 5 syllables17        ],18        ("Spring", "Summer"): [19            "Insights grow in light,",  # 5 syllables20            "Data scales the bright, warm sun,",  # 7 syllables21            "Wisdom on full show."  # 5 syllables22        ],23        ("Summer", "Fall"): [24            "Leaves of data turn,",  # 5 syllables25            "Decisions ripe and well-earned,",  # 7 syllables26            "Change whispers anew."  # 5 syllables27        ],28        ("Fall", "Winter"): [29            "Data's frost sets in,",  # 5 syllables30            "Vector cycles glean insights,",  # 7 syllables31            "Silence holds the keys."  # 5 syllables32        ],33    }34
35    # Randomly select a transition36    start_season = np.random.choice(seasons)37    end_season = seasons[(seasons.index(start_season) + 1) % len(seasons)]38
39    haiku_lines = transitions[(start_season, end_season)]40
41    return haiku_lines, start_season, end_season42
43# Visualization with Gradient44def visualize_seasonal_transition(haiku, start_season, end_season):45    fig, ax = plt.subplots(figsize=(10, 6))46    ax.axis('off')47
48    # Seasonal Colors49    colors = {50        "Winter": "#ffffff",51        "Spring": "#4caf50",52        "Summer": "#ffa726",53        "Fall": "#fb8c00"54    }55
56    # Create Gradient57    cmap = LinearSegmentedColormap.from_list("season_transition", [colors[start_season], colors[end_season]])58    gradient = np.linspace(0, 1, 256)59    gradient = np.vstack((gradient, gradient))60
61    ax.imshow(gradient, aspect='auto', cmap=cmap, extent=[0, 10, 0, 10])62
63    # Display Haiku64    ax.text(5, 5, "\n".join(haiku), ha='center', va='center', fontsize=14, color="black")65
66    # Download the logo67    logo_url = "https://raw.githubusercontent.com/singlestore-labs/spaces-notebooks/master/common/images/singlestore-logo-vertical.png"68    response = requests.get(logo_url)69    logo_img = Image.open(BytesIO(response.content))70
71    # Convert the Image object to a NumPy array and display it72    logo = np.array(logo_img)73    ax_logo = fig.add_axes([0.75, -0.05, 0.15, 0.15])  # Adjust these values to position and scale the logo74    ax_logo.imshow(logo)75    ax_logo.axis('off')  # Hide the axis of the logo subplot76
77    plt.show()78
79# Generate and Visualize80haiku, start_season, end_season = generate_seasonal_transition_haiku()81visualize_seasonal_transition(haiku, start_season, end_season)

1!pip install Pillow requests --quiet

1import requests2from PIL import Image3from io import BytesIO4
5# Define the ASCII characters that will be used to replace the pixels.6ASCII_CHARS = ["@", "#", "S", "%", "?", "*", "+", ";", ":", ",", "."]7
8def resize_image(image, new_width=100):9    width, height = image.size10    ratio = height / width / 1.65  # Correct for aspect ratio11    new_height = int(new_width * ratio)12    resized_image = image.resize((new_width, new_height))13    return resized_image14
15def grayify(image):16    grayscale_image = image.convert("L")17    return grayscale_image18
19def pixels_to_ascii(image):20    pixels = image.getdata()21    ascii_str = ''22    for pixel in pixels:23        ascii_str += ASCII_CHARS[pixel // 25]  # Map the pixel value to ASCII_CHARS24    return ascii_str25
26def process_image_from_url(image_url, new_width=100):27    # Fetch the image from the URL28    response = requests.get(image_url)29    if response.status_code == 200:30        # Open the image from the bytes in response content31        image = Image.open(BytesIO(response.content))32
33        # Process the image34        image = resize_image(image, new_width)35        image = grayify(image)36        ascii_str = pixels_to_ascii(image)37
38        # Format the ASCII string so that each line has `new_width` characters.39        img_width = image.width40        ascii_str_len = len(ascii_str)41        ascii_img = ""42        for i in range(0, ascii_str_len, img_width):43            ascii_img += ascii_str[i:i+img_width] + "\n"44
45        # Print the ASCII art46        print(ascii_img)47    else:48        print("Failed to retrieve the image from the URL")49
50# Example usage with a public image URL51image_url = 'https://raw.githubusercontent.com/singlestore-labs/spaces-notebooks/master/common/images/singlestore-banner.png'  # Replace with your image's URL52process_image_from_url(image_url, 100)