import random
import os
import uuid
from datetime import datetime
import gradio as gr
import numpy as np
import spaces
import torch
from diffusers import DiffusionPipeline
from PIL import Image
# Create permanent storage directory
SAVE_DIR = "saved_images" # Gradio will handle the persistence
if not os.path.exists(SAVE_DIR):
os.makedirs(SAVE_DIR, exist_ok=True)
# Load the default image
DEFAULT_IMAGE_PATH = "cover1.webp"
device = "cuda" if torch.cuda.is_available() else "cpu"
repo_id = "black-forest-labs/FLUX.1-dev"
adapter_id = "strangerzonehf/Ctoon-Plus-Plus"
pipeline = DiffusionPipeline.from_pretrained(repo_id, torch_dtype=torch.bfloat16)
pipeline.load_lora_weights(adapter_id)
pipeline = pipeline.to(device)
MAX_SEED = np.iinfo(np.int32).max
MAX_IMAGE_SIZE = 1024
def save_generated_image(image, prompt):
# Generate unique filename with timestamp
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
unique_id = str(uuid.uuid4())[:8]
filename = f"{timestamp}_{unique_id}.png"
filepath = os.path.join(SAVE_DIR, filename)
# Save the image
image.save(filepath)
# Save metadata
metadata_file = os.path.join(SAVE_DIR, "metadata.txt")
with open(metadata_file, "a", encoding="utf-8") as f:
f.write(f"{filename}|{prompt}|{timestamp}\n")
return filepath
@spaces.GPU(duration=120)
def inference(
prompt: str,
seed: int,
randomize_seed: bool,
width: int,
height: int,
guidance_scale: float,
num_inference_steps: int,
lora_scale: float,
progress: gr.Progress = gr.Progress(track_tqdm=True),
):
if randomize_seed:
seed = random.randint(0, MAX_SEED)
generator = torch.Generator(device=device).manual_seed(seed)
image = pipeline(
prompt=prompt,
guidance_scale=guidance_scale,
num_inference_steps=num_inference_steps,
width=width,
height=height,
generator=generator,
joint_attention_kwargs={"scale": lora_scale},
).images[0]
# Save the generated image
filepath = save_generated_image(image, prompt)
# Return the image and seed (gallery removed)
return image, seed
examples = [
"A cartoon drawing of a majestic Persian cat wearing a tiny golden hanbok and crown. The cat has sparkling blue eyes and perfectly groomed white fur that seems to glow. It sits with regal posture on a traditional Korean cushion decorated with cloud patterns. The background is a soft pink with delicate cherry blossom petals floating around. The cat's expression shows a mix of dignity and subtle amusement. [trigger]",
"A cartoon drawing of an enthusiastic orange tabby cat in a puffy white chef's hat. The cat stands on its hind legs at a tiny wooden counter, wearing a white apron covered in flour pawprints. Its green eyes are focused intently on the cookie dough it's rolling with a miniature rolling pin. The background is a warm cream color with tiny floating cooking utensils and swirling steam patterns. [trigger]",
"A cartoon drawing of a sophisticated tuxedo cat photographer with round wire-rimmed glasses perched on its nose. The cat balances carefully on a tree branch, one paw holding a vintage camera while its tail curls in concentration. It wears a tiny brown beret and leather camera bag. The background is a soft blue with playful butterfly silhouettes and floating leaves. [trigger]",
"A cartoon drawing of a chubby Scottish Fold cat floating in a space capsule. The cat wears an adorable white spacesuit with colorful patches, its round face visible through the helmet visor. Its paws are batting at star-shaped toys that float around in zero gravity. The background shows a stylized view of Earth and twinkling stars through the capsule window. [trigger]",
"A cartoon drawing of an elegant Siamese ballet dancer cat in mid-twirl. The cat wears a sparkly pink tutu that flares out perfectly, with tiny satin ribbons wrapped around its ankles. Its blue eyes are closed in graceful concentration as it performs a pirouette. The background is a soft lavender with swirling musical notes and floating rose petals. [trigger]",
"A cartoon drawing of an adventurous calico cat riding atop a smiling elephant. The cat wears a tiny khaki explorer's vest filled with equipment, and a safari hat tilted at a jaunty angle. It holds a comically large map while the elephant's trunk curls up playfully. The background is a warm orange sunset with stylized acacia trees and cartoon birds soaring past. [trigger]"
]
css = """
footer {
visibility: hidden;
}
"""
with gr.Blocks(theme=gr.themes.Soft(), css=css, analytics_enabled=False) as demo:
gr.HTML('<div class="title"> Cartoon Image Generation </div>')
gr.HTML("""<a href="https://visitorbadge.io/status?path=https%3A%2F%2Fginigen-cartoon.hf.space">
<img src="https://api.visitorbadge.io/api/visitors?path=https%3A%2F%2Fginigen-cartoon.hf.space&countColor=%23263759" />
</a>""")
with gr.Tab("Generation"):
with gr.Column(elem_id="col-container"):
with gr.Row():
prompt = gr.Text(
label="Prompt",
show_label=False,
max_lines=1,
placeholder="Enter your prompt",
container=False,
)
run_button = gr.Button("Run", scale=0)
result = gr.Image(
label="Result",
show_label=False,
value=DEFAULT_IMAGE_PATH
)
with gr.Accordion("Advanced Settings", open=False):
seed = gr.Slider(
label="Seed",
minimum=0,
maximum=MAX_SEED,
step=1,
value=42,
)
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
with gr.Row():
width = gr.Slider(
label="Width",
minimum=256,
maximum=MAX_IMAGE_SIZE,
step=32,
value=1024,
)
height = gr.Slider(
label="Height",
minimum=256,
maximum=MAX_IMAGE_SIZE,
step=32,
value=768,
)
with gr.Row():
guidance_scale = gr.Slider(
label="Guidance scale",
minimum=0.0,
maximum=10.0,
step=0.1,
value=3.5,
)
num_inference_steps = gr.Slider(
label="Number of inference steps",
minimum=1,
maximum=50,
step=1,
value=30,
)
lora_scale = gr.Slider(
label="LoRA scale",
minimum=0.0,
maximum=1.0,
step=0.1,
value=1.0,
)
gr.Examples(
examples=examples,
inputs=[prompt],
outputs=[result, seed],
)
gr.on(
triggers=[run_button.click, prompt.submit],
fn=inference,
inputs=[
prompt,
seed,
randomize_seed,
width,
height,
guidance_scale,
num_inference_steps,
lora_scale,
],
outputs=[result, seed],
)
demo.queue()
demo.launch()