from PIL import Image from rembg import remove import cairosvg import io import numpy as np from sklearn.cluster import KMeans from PIL import Image, ImageDraw, ImageFont import random import gradio as gr def generate(logo=None, Vtubername="", sdkey=""): if(logo==None): gr.Warning('Please Select Your Photo📸') if(Vtubername==""): Vtubername = "unkown" gr.Warning('Please Select Your Name😱') if(sdkey==""): gr.Warning('Please Set valid Stability AI API Key🔑') def extract_dominant_colors(img, num_colors=3, ignore_edges=True): if img.mode == 'RGBA': image = img.convert('RGB') else: image = img image = image.resize((150, 150)) data = np.array(image) pixels = data.reshape(-1, 3) if ignore_edges: edge_pixels = np.concatenate([data[0, :, :], data[-1, :, :], data[:, 0, :], data[:, -1, :]], axis=0) edge_colors, counts = np.unique(edge_pixels, axis=0, return_counts=True) background_color = edge_colors[counts.argmax()] pixels = pixels[~np.all(pixels == background_color, axis=1)] if len(pixels) == 0: return np.array([background_color,np.array([60,60,60]),np.array([255,255,255])]) elif len(pixels) == 1: return np.array([pixels[0],np.array([60,60,60]),np.array([255,255,255])]) elif len(pixels) == 2: return np.array([pixels[0],pixels[1],np.array([60,60,60])]) model = KMeans(n_clusters=3) model.fit(pixels) colors = model.cluster_centers_ colors = colors.round(0).astype(int) return colors dominant_colors = extract_dominant_colors(logo, num_colors=3) template_prime_colors = { "black color": [0, 0, 0], "white": [255, 255, 255], "red": [255, 0, 0], "lightgreen": [0, 255, 0], "blue": [0, 0, 255], "yellow": [255, 255, 0], "lightblue": [0, 255, 255], "pink": [255, 0, 255], "gray": [128, 128, 128], "maroon": [128, 0, 0], "olive": [128, 128, 0], "green": [0, 128, 0], "purple": [128, 0, 128], "navy": [0, 0, 128], "orange": [255, 165, 0], "bluegreen": [0, 128, 128], "lightpurple": [128, 128, 255], "skyblue color": [0, 128, 255], "brown": [139,69,19], } _primary_color = dominant_colors[0] closest_color = "black color" for color in template_prime_colors: if np.linalg.norm(np.array(template_prime_colors[color]) - _primary_color) < np.linalg.norm(np.array(template_prime_colors[closest_color]) - _primary_color): closest_color = color primary_color = closest_color print(primary_color) secondary_color=str("rgb("+str(dominant_colors[1][0])+", "+str(dominant_colors[1][1])+", "+str(dominant_colors[1][2])+")") third_color=str("rgb("+str(dominant_colors[2][0])+", "+str(dominant_colors[2][1])+", "+str(dominant_colors[2][2])+")") import requests from huggingface_hub import InferenceClient client = InferenceClient(model="mistralai/Mixtral-8x7B-Instruct-v0.1") output = client.text_generation("Make this english to Japanese Hiragana. ex. Robert->はろー HuggingFace->はぎんぐふぇいす "+Vtubername+"->") hiragana = "" for char in output: if '\u3040' <= char <= '\u309f': hiragana += char response = requests.post( f"https://api.stability.ai/v2beta/stable-image/generate/sd3", headers={ "authorization": f"Bearer "+sdkey, "accept": "image/*" }, files={"none": ''}, data={ "model": "sd3", "prompt": "pop sweety cute kawaii font anime title logo drawn by adobe illustorator. Logo for kids amime. The title logo text is \""+Vtubername+"\""+", The logo text color:"+primary_color + ". Single Logo only.", "negative_prompt": "subtitle,face, ruby text, smoke, subscript, superscript, multiple titles, character, ugly, blurry, dirty, character face, face, watermark, low res, cropped, worst quality, jpeg artifacts, , picture frame, out of frame,animal, person face, low-res, blurry, blur, out of focus, disgusting", "output_format": "jpeg", }, ) image = None if response.status_code == 200: image = response.content else: gr.Warning('Your message is not allowed!') raise Exception(str(response.json())) image = Image.open(io.BytesIO(response.content)) title_logo=remove(image) def get_brightness(color): red, green, blue = color return (red * 0.299 + green * 0.587 + blue * 0.114) / 255 brighter_color = secondary_color if get_brightness(dominant_colors[1]) > get_brightness(dominant_colors[2]) else third_color darker_cplor = secondary_color if get_brightness(dominant_colors[1]) < get_brightness(dominant_colors[2]) else third_color font_color=brighter_color font_size=100 stroke_width=int(100*0.1) stroke_color=darker_cplor # Load the font font = ImageFont.truetype("oshigo.otf", size=font_size) japanese_text = hiragana # Image setup tile_width, tile_height = int(font_size*1.4), int(font_size*1.4) # Size of individual tiles num_tiles = len(japanese_text) total_width = tile_width * num_tiles total_height = tile_height # Create a new blank image result_image = Image.new('RGBA', (total_width, total_height), (0, 0, 0, 0)) draw = ImageDraw.Draw(result_image) for i, char in enumerate(japanese_text): # Create an image for each character with transparency tile_image = Image.new('RGBA', (tile_width, tile_height), (0, 0, 0, 0)) tile_draw = ImageDraw.Draw(tile_image) # Calculate text position: random within the tile text_width, text_height = draw.textsize(char, font=font) x = random.randint(0, (tile_width - text_width)//1.25) y = random.randint(0, (tile_height - text_height)//1.25) # Draw text on the tile tile_draw.text((x, y), char, font=font, fill="white", stroke_width=stroke_width, stroke_fill=stroke_color) # Paste the tile into the result image result_image.paste(tile_image, (i * tile_width, 0), tile_image) # Save or display the image caption = result_image def resize_caption_to_logo(logo, caption): if caption.width > logo.width: scaler = 2.4 resized_caption = caption.resize((int(logo.width*scaler), int(scaler*caption.height * logo.width / caption.width ))) print("resizing") return resized_caption else: return caption caption = resize_caption_to_logo(logo, caption) center=((title_logo.width - caption.width) // 2,title_logo.height//2) bottom=(title_logo.width-caption.width)//2,int(title_logo.height-caption.height-100) lower_right=(title_logo.width-caption.width-40,int(title_logo.height-caption.height-80)) upper_right=(title_logo.width-caption.width-40,int(caption.height+80)) # Define the possible positions positions = [ ("center", center), ("bottom", bottom), ("lower_right", lower_right), ("upper_right", upper_right), ] # Randomly select a position position, coordinates = random.choice(positions) # Paste the caption at the selected position title_logo.paste(caption, coordinates, caption) return title_logo css=""" .gradio-container{ background-color: #fff; background-image: radial-gradient(#b4f3ea 0%, transparent 30%), radial-gradient(#ffffcc 0%, transparent 30%); background-size: 40px 40px; background-position: 0 0, 20px 20px; } h1{ font-size: 400%!important; background: linear-gradient(to bottom, pink, white); -webkit-background-clip: text; -webkit-text-fill-color: transparent; -webkit-text-stroke: 2px pink; -webkit-text-stroke-width: 2px; -webkit-text-stroke-color: pink; } """ import os iface = gr.Interface( theme=gr.themes.Default(primary_hue="pink",font=[gr.themes.GoogleFont("Mochiy Pop One")]), css=css, fn=generate, inputs=[gr.Image(label="Your Photo", type="pil"), gr.Textbox(label="Your Name(*alphabet only!*)"), gr.Textbox(label="Stability AI API Key")], outputs=gr.Image(label="Generated Logo"), title="Kawaii Logo Generator", description="①Upload photo you wanna make Kawaii❤️
② Input the name(*alphabet only!*)⭐️
③ Set your Stability AI API key🔑(https://platform.stability.ai/account/keys)
④Press Submit🧙", #examples=[["image.jpeg", "gojiteji", os.environ["sdkey"]]], allow_flagging=False ) # Launch the interface iface.launch(debug=True)