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import gradio as gr
from diffusers import AutoPipelineForText2Image
import torch
# Model ve pipeline kurulumu
device = "cuda" if torch.cuda.is_available() else "cpu"
pipeline = AutoPipelineForText2Image.from_pretrained(
"black-forest-labs/FLUX.1-dev",
torch_dtype=torch.float16
).to(device)
# LoRA modelini yükle
pipeline.load_lora_weights("codermert/gamzekocc_fluxx", weight_name="lora.safetensors")
def generate_image(prompt, negative_prompt, guidance_scale):
# TOK trigger'ını otomatik ekle
if not prompt.startswith("TOK"):
prompt = "TOK, " + prompt
# Görseli oluştur
image = pipeline(
prompt=prompt,
negative_prompt=negative_prompt,
guidance_scale=float(guidance_scale)
).images[0]
return image
# Gradio arayüzü
with gr.Blocks(title="Mert Baba'nın Görsel Oluşturucusu") as demo:
gr.Markdown("""
# 🎨 Mert Baba'nın AI Görsel Oluşturucusu
FLUX LoRA modeli ile özel görseller oluşturun!
""")
with gr.Row():
with gr.Column():
prompt = gr.Textbox(
label="Prompt",
placeholder="Görsel için açıklama girin...",
lines=3
)
negative_prompt = gr.Textbox(
label="Negative Prompt",
value="blurry, bad quality, worst quality, jpeg artifacts",
lines=2
)
guidance_scale = gr.Slider(
minimum=1,
maximum=20,
value=7.5,
step=0.5,
label="Guidance Scale"
)
generate_btn = gr.Button("Görsel Oluştur 🎨")
with gr.Column():
output_image = gr.Image(label="Oluşturulan Görsel")
# Örnek promptlar
gr.Examples(
examples=[
["A striking woman lit with bi-color directional lighting poses",
"blurry, bad quality, worst quality, jpeg artifacts",
7.5],
["A beautiful portrait photo in a city",
"blurry, bad quality",
7.5],
],
inputs=[prompt, negative_prompt, guidance_scale],
outputs=output_image,
fn=generate_image,
cache_examples=True,
)
# Butona tıklayınca çalışacak fonksiyon
generate_btn.click(
fn=generate_image,
inputs=[prompt, negative_prompt, guidance_scale],
outputs=output_image
)
demo.launch() |