File size: 3,114 Bytes
6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 1277f89 6026000 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 |
import gradio as gr
import spaces
from model import ModelHandler
from generator import Generator
from config import Config
# 1. Initialize Models
print("Initializing Application...")
handler = ModelHandler()
handler.load_models()
gen = Generator(handler)
# 2. Define GPU Inference Function
@spaces.GPU(duration=20)
def process_text(
prompt,
negative_prompt,
cfg_scale,
steps,
seed
):
try:
print("--- Starting Generation ---")
result = gen.predict(
user_prompt=prompt,
negative_prompt=negative_prompt,
guidance_scale=cfg_scale,
num_inference_steps=steps,
seed=seed
)
print("--- Generation Complete ---")
return result
except Exception as e:
print(f"Error during generation: {e}")
raise gr.Error(f"An error occurred: {str(e)}")
# 3. Build Gradio Interface
with gr.Blocks(title="Pixel Art Generator", theme=gr.themes.Soft()) as demo:
gr.Markdown(
"""
# 🎮 Text to Pixel Art
Type a prompt to generate high-quality pixel art scenes.
"""
)
with gr.Row():
with gr.Column(scale=2):
prompt = gr.Textbox(
label="Prompt",
placeholder="e.g. cyberpunk city street at night, rain",
info="The trigger words 'p1x3l4rt, pixel art' are added automatically."
)
negative_prompt = gr.Textbox(
label="Negative Prompt",
placeholder="e.g., blurry, text, watermark, bad art...",
value=Config.DEFAULT_NEGATIVE_PROMPT
)
with gr.Accordion("Settings", open=True):
seed = gr.Number(
label="Seed",
value=-1,
info="-1 for random",
precision=0
)
cfg_scale = gr.Slider(
elem_id="cfg_scale",
minimum=1.0,
maximum=5.0,
step=0.1,
value=Config.CGF_SCALE,
label="CFG Scale"
)
steps = gr.Slider(
elem_id="steps",
minimum=4,
maximum=20,
step=1,
value=Config.STEPS_NUMBER,
label="Steps"
)
run_btn = gr.Button("Generate", variant="primary")
with gr.Column(scale=1):
output_img = gr.Image(label="Result")
# Event Handler
all_inputs = [
prompt,
negative_prompt,
cfg_scale,
steps,
seed
]
run_btn.click(
fn=process_text,
inputs=all_inputs,
outputs=[output_img]
)
# 4. Launch
if __name__ == "__main__":
demo.queue(max_size=20, api_open=True)
demo.launch(
server_name="0.0.0.0",
server_port=7860,
show_api=True
) |