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| import cv2 | |
| import numpy as np | |
| import gradio as gr | |
| from PIL import Image, ImageDraw, ImageFont | |
| def generate_text_image(text, style, width, height): | |
| """Generate an image of the input text with the selected style.""" | |
| font_path = { | |
| "Bold": "arialbd.ttf", | |
| "Italic": "ariali.ttf", | |
| "Graffiti": "graffiti.ttf", # Provide custom font if needed | |
| "Calligraphy": "calligraphy.ttf" # Provide custom font if needed | |
| } | |
| img = Image.new("RGBA", (width, height), (255, 255, 255, 0)) | |
| draw = ImageDraw.Draw(img) | |
| try: | |
| font = ImageFont.truetype(font_path[style], size=80) | |
| except: | |
| font = ImageFont.load_default() | |
| 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] | |
| position = ((width - text_width) // 2, (height - text_height) // 2) | |
| draw.text(position, text, font=font, fill=(0, 0, 0, 255)) | |
| return img | |
| def apply_displacement_map(text_img, clothing_img, strength=20): | |
| """Apply displacement map to blend text onto clothing.""" | |
| gray = cv2.cvtColor(clothing_img, cv2.COLOR_BGR2GRAY) | |
| grad_x = cv2.Sobel(gray, cv2.CV_32F, 1, 0, ksize=5) | |
| grad_y = cv2.Sobel(gray, cv2.CV_32F, 0, 1, ksize=5) | |
| grad_x = cv2.normalize(grad_x, None, 0, 1, cv2.NORM_MINMAX) | |
| grad_y = cv2.normalize(grad_y, None, 0, 1, cv2.NORM_MINMAX) | |
| displacement_map = np.zeros_like(clothing_img, dtype=np.float32) | |
| displacement_map[:, :, 0] = grad_x * strength | |
| displacement_map[:, :, 1] = grad_y * strength | |
| text_warped = cv2.remap(text_img, | |
| displacement_map[:, :, 0].astype(np.float32), | |
| displacement_map[:, :, 1].astype(np.float32), | |
| interpolation=cv2.INTER_LINEAR) | |
| return text_warped | |
| def overlay_text_on_clothing(clothing_image, text_input, style, strength=20, alpha=0.7): | |
| """Blend generated text onto the clothing image.""" | |
| clothing_img = cv2.imread(clothing_image) # Read image from file path | |
| # Generate text image dynamically | |
| text_img_pil = generate_text_image(text_input, style, clothing_img.shape[1], clothing_img.shape[0]) | |
| text_img = cv2.cvtColor(np.array(text_img_pil), cv2.COLOR_RGBA2BGRA) | |
| alpha_channel = text_img[:, :, 3] / 255.0 | |
| text_img = text_img[:, :, :3] | |
| text_warped = apply_displacement_map(text_img, clothing_img, strength) | |
| for c in range(3): | |
| clothing_img[:, :, c] = (1 - alpha_channel) * clothing_img[:, :, c] + alpha_channel * text_warped[:, :, c] | |
| # Convert the final blended image back to a PIL Image and return | |
| blended_img = Image.fromarray(cv2.cvtColor(clothing_img, cv2.COLOR_BGR2RGB)) | |
| return blended_img | |
| interface = gr.Interface( | |
| fn=overlay_text_on_clothing, | |
| inputs=[ | |
| gr.Image(type="filepath", label="Upload Clothing Image", interactive=True), | |
| gr.Textbox(label="Enter Text for Design"), | |
| gr.Radio(["Bold", "Italic", "Graffiti", "Calligraphy"], label="Select Style", value="Bold"), | |
| gr.Slider(10, 50, step=5, value=20, label="Displacement Strength"), | |
| gr.Slider(0.1, 1.0, step=0.1, value=0.7, label="Alpha Blending") | |
| ], | |
| outputs=gr.Image(type="pil", label="Final Design"), | |
| title="AI-Powered Clothing Text Overlay", | |
| description="Upload a clothing image, enter a text design, and select a style to blend them onto clothing with displacement mapping.", | |
| allow_flagging="never" | |
| ) | |
| if __name__ == "__main__": | |
| interface.launch() |