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import gradio as gr
from PIL import Image
import numpy as np
def image_to_ascii(image, width=100, chars="@%#*+=-:. "):
"""
Convert image to ASCII art
"""
# Convert image to grayscale
if image.mode != 'L':
image = image.convert('L')
# Resize image while maintaining aspect ratio
original_width, original_height = image.size
aspect_ratio = original_height / original_width
height = int(width * aspect_ratio * 0.55) # 0.55 to account for character aspect ratio
# Resize image
img_resized = image.resize((width, height))
# Convert to numpy array
pixels = np.array(img_resized)
# Normalize pixels to 0-1 range
pixels = pixels / 255.0
# Map pixels to ASCII characters
ascii_chars = list(chars)
num_chars = len(ascii_chars)
# Create ASCII art
ascii_art = []
for row in pixels:
line = ''.join(ascii_chars[min(int(pixel * num_chars), num_chars - 1)] for pixel in row)
ascii_art.append(line)
return '\n'.join(ascii_art)
def process_image(image, width, character_set):
"""
Process the uploaded image and convert to ASCII art
"""
if image is None:
return "Please upload an image first!"
try:
# Define character sets
char_sets = {
"Detailed (dense)": "@%#*+=-:. ",
"Simple (sparse)": "@#*+-. ",
"Blocks": "█▓▒░ ",
"Inverted": " .:-=+*#%@",
"Custom": character_set
}
chars = char_sets.get(character_set, "@%#*+=-:. ")
ascii_result = image_to_ascii(image, width, chars)
return f"```\n{ascii_result}\n```"
except Exception as e:
return f"Error processing image: {str(e)}"
# Create Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# Image to ASCII Art Converter")
gr.Markdown("Convert your images to ASCII art! Upload an image, adjust the width and character set, and see the text-based version of your image.")
with gr.Row():
with gr.Column():
image_input = gr.Image(type="pil", label="Upload Image")
width_slider = gr.Slider(minimum=50, maximum=200, value=100, step=10, label="ASCII Art Width")
char_set_dropdown = gr.Dropdown(
choices=["Detailed (dense)", "Simple (sparse)", "Blocks", "Inverted", "Custom"],
value="Detailed (dense)",
label="Character Set"
)
custom_chars = gr.Textbox(
value="@%#*+=-:. ",
label="Custom Character Set (used when 'Custom' is selected)",
placeholder="Enter characters from darkest to lightest"
)
submit_btn = gr.Button("Convert to ASCII")
with gr.Column():
output_text = gr.Textbox(
label="ASCII Art Result",
lines=20,
max_lines=50,
show_copy_button=True
)
output_image = gr.Image(label="ASCII Art Image Preview", type="pil")
# Update character set based on dropdown selection
def update_char_set(character_set, custom_chars):
char_sets = {
"Detailed (dense)": "@%#*+=-:. ",
"Simple (sparse)": "@#*+-. ",
"Blocks": "█▓▒░ ",
"Inverted": " .:-=+*#%@",
"Custom": custom_chars
}
return char_sets.get(character_set, "@%#*+=-:. ")
# Process function that uses the selected character set
def process_with_char_set(image, width, character_set, custom_chars):
char_sets = {
"Detailed (dense)": "@%#*+=-:. ",
"Simple (sparse)": "@#*+-. ",
"Blocks": "█▓▒░ ",
"Inverted": " .:-=+*#%@",
"Custom": custom_chars
}
chars = char_sets.get(character_set, "@%#*+=-:. ")
if image is None:
return "Please upload an image first!", None
try:
ascii_result = image_to_ascii(image, width, chars)
# Create image preview from ASCII
lines = ascii_result.split("\n")
h = len(lines)
w = max(len(line) for line in lines) if h > 0 else 0
if w == 0 or h == 0:
preview = None
else:
# Map characters to grayscale values
unique_chars = list(dict.fromkeys(chars))
num_chars = len(unique_chars)
char_to_val = {c: int((i / max(num_chars - 1, 1)) * 255) for i, c in enumerate(unique_chars)}
img_array = np.zeros((h, w), dtype=np.uint8)
for y, line in enumerate(lines):
for x, ch in enumerate(line):
img_array[y, x] = char_to_val.get(ch, 0)
preview = np.stack([img_array]*3, axis=-1)
return f"\n{ascii_result}\n", preview
except Exception as e:
return f"Error processing image: {str(e)}", None
# Connect the components
char_set_dropdown.change(
update_char_set,
inputs=[char_set_dropdown, custom_chars],
outputs=custom_chars
)
submit_btn.click(
process_with_char_set,
inputs=[image_input, width_slider, char_set_dropdown, custom_chars],
outputs=[output_text, output_image]
)
if __name__ == "__main__":
demo.launch() |