import gradio as gr from PIL import Image, ImageDraw, ImageFont import numpy as np import os from PIL import Image from gradio_client import Client, handle_file import uuid client = Client("ysharma/BiRefNet_for_text_writing") def add_text_with_stroke(draw, text, x, y, font, text_color, stroke_width): """Helper function to draw text with stroke""" # Draw the stroke/outline for adj_x in range(-stroke_width, stroke_width + 1): for adj_y in range(-stroke_width, stroke_width + 1): draw.text((x + adj_x, y + adj_y), text, font=font, fill=text_color) def remove_background(image): # Save the image to a specific location filename = f"image_{uuid.uuid4()}.png" # Generates a universally unique identifier (UUID) for the filename image.save(filename) # Call gradio client for background removal result = client.predict(images=handle_file(filename), api_name="/image") return Image.open(result[0]) def superimpose(image_with_text, overlay_image): # Open image as RGBA to handle transparency overlay_image = overlay_image.convert("RGBA") # Paste overlay on the background image_with_text.paste(overlay_image, (0, 0), overlay_image) # Save the final image # image_with_text.save("output_image.png") return image_with_text def add_text_to_image( input_image, text, font_size, color, opacity, x_position, y_position, thickness ): """ Add text to an image with customizable properties """ # Convert gradio image (numpy array) to PIL Image if input_image is None: return None image = Image.fromarray(input_image) # remove background overlay_image = remove_background(image) # Create a transparent overlay for the text txt_overlay = Image.new('RGBA', image.size, (255, 255, 255, 0)) draw = ImageDraw.Draw(txt_overlay) # Create a font with specified size try: font = ImageFont.truetype("DejaVuSans.ttf", int(font_size)) except: # If DejaVu font is not found, try to use Arial or default try: font = ImageFont.truetype("arial.ttf", int(font_size)) except: print("Using default font as system fonts not found") font = ImageFont.load_default() # Convert color name to RGB color_map = { 'White': (255, 255, 255), 'Black': (0, 0, 0), 'Red': (255, 0, 0), 'Green': (0, 255, 0), 'Blue': (0, 0, 255), 'Yellow': (255, 255, 0), 'Purple': (128, 0, 128) } rgb_color = color_map.get(color, (255, 255, 255)) # Get text size for positioning text_bbox = draw.textbbox((0, 0), text, font=font) text_width = text_bbox[2] - text_bbox[0] text_height = text_bbox[3] - text_bbox[1] # Calculate actual x and y positions based on percentages actual_x = int((image.width - text_width) * (x_position / 100)) actual_y = int((image.height - text_height) * (y_position / 100)) # Create final color with opacity text_color = (*rgb_color, int(opacity)) # Draw the text with stroke for thickness add_text_with_stroke( draw, text, actual_x, actual_y, font, text_color, int(thickness) ) # Combine the original image with the text overlay if image.mode != 'RGBA': image = image.convert('RGBA') output_image = Image.alpha_composite(image, txt_overlay) # Convert back to RGB for display output_image = output_image.convert('RGB') # superimpose images output_image = superimpose(output_image, overlay_image) # Convert PIL image back to numpy array for Gradio return np.array(output_image) # Create the Gradio interface def create_interface(): with gr.Blocks() as app: gr.Markdown("# Add Text Behind Image") gr.Markdown("Upload an image and customize text properties to add text overlay.") with gr.Row(): with gr.Column(): # Input components input_image = gr.Image(label="Upload Image", type="numpy") text_input = gr.Textbox(label="Enter Text", placeholder="Type your text here...") font_size = gr.Slider(minimum=10, maximum=800, value=400, step=10, label="Font Size") thickness = gr.Slider(minimum=0, maximum=20, value=0, step=1, label="Text Thickness") color_dropdown = gr.Dropdown( choices=["White", "Black", "Red", "Green", "Blue", "Yellow", "Purple"], value="White", label="Text Color" ) opacity_slider = gr.Slider(minimum=0, maximum=255, value=255, step=1, label="Opacity") x_position = gr.Slider(minimum=0, maximum=100, value=50, step=1, label="X Position (%)") y_position = gr.Slider(minimum=0, maximum=100, value=50, step=1, label="Y Position (%)") with gr.Column(): # Output image output_image = gr.Image(label="Output Image") # Process button process_btn = gr.Button("Add Text to Image") # Connect the input components to the processing function process_btn.click( fn=add_text_to_image, inputs=[ input_image, text_input, font_size, color_dropdown, opacity_slider, x_position, y_position, thickness ], outputs=output_image ) # Add example inputs gr.Examples( examples=[ [ "pink_convertible.webp", "EPIC", 420, "Purple", 150, 50, 21, 9 ], [ "pear.jpg", "PEAR", 350, "Black", 100, 50, 2, 5 ], [ "sample_text_image.jpeg", "LIFE", 400, "Black", 150, 50, 2, 8 ], ], inputs=[ input_image, text_input, font_size, color_dropdown, opacity_slider, x_position, y_position, thickness ], outputs=output_image, fn=add_text_to_image, cache_examples=True, ) return app # Launch the app if __name__ == "__main__": # Try to install required font try: import subprocess subprocess.run(['apt-get', 'update']) subprocess.run(['apt-get', 'install', '-y', 'fonts-dejavu']) print("Font installed successfully") except: print("Could not install font automatically. Please install DejaVu font manually.") # Create and launch the interface app = create_interface() app.launch()