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import os | |
import gradio as gr | |
from PIL import Image | |
import torch | |
from diffusers import DiffusionPipeline | |
import tempfile | |
# Check for GPU availability | |
DEVICE = "cuda" if torch.cuda.is_available() else "cpu" | |
def initialize_model(): | |
"""Initialize the Animator2D model.""" | |
try: | |
# Initialize the pipeline | |
pipeline = DiffusionPipeline.from_pretrained( | |
"Lod34/Animator2D", | |
trust_remote_code=True, | |
device=DEVICE | |
) | |
return pipeline | |
except Exception as e: | |
raise Exception(f"Error initializing model: {str(e)}") | |
def generate_animation( | |
description: str, | |
action: str, | |
direction: str, | |
num_frames: int | |
): | |
"""Generate animation based on input parameters.""" | |
try: | |
# Input validation | |
if not all([description, action, direction]): | |
raise ValueError("All text fields must be filled") | |
# Initialize model | |
pipeline = initialize_model() | |
# Prepare prompt | |
prompt = f"A sprite of {description} {action}, facing {direction}" | |
# Generate animation | |
output = pipeline( | |
prompt=prompt, | |
num_frames=num_frames, | |
num_inference_steps=50 | |
) | |
# Save animation as GIF | |
temp_dir = tempfile.mkdtemp() | |
output_path = os.path.join(temp_dir, "animation.gif") | |
# Convert output frames to GIF | |
frames = [Image.fromarray(frame) for frame in output.frames] | |
frames[0].save( | |
output_path, | |
save_all=True, | |
append_images=frames[1:], | |
duration=100, | |
loop=0 | |
) | |
return output_path | |
except Exception as e: | |
raise gr.Error(f"Generation failed: {str(e)}") | |
def create_interface(): | |
"""Create and launch the Gradio interface.""" | |
with gr.Blocks(title="Animator2D Sprite Generator") as interface: | |
gr.Markdown("# Animator2D Sprite Generator") | |
gr.Markdown("Generate animated sprites using AI") | |
with gr.Row(): | |
with gr.Column(): | |
# Input components | |
description = gr.Textbox( | |
label="Sprite Description", | |
placeholder="E.g., a cute pixel art cat" | |
) | |
action = gr.Textbox( | |
label="Sprite Action", | |
placeholder="E.g., walking, jumping" | |
) | |
direction = gr.Dropdown( | |
label="Direction", | |
choices=["North", "South", "East", "West"], | |
value="South" | |
) | |
num_frames = gr.Slider( | |
label="Number of Frames", | |
minimum=2, | |
maximum=24, | |
value=8, | |
step=1 | |
) | |
generate_btn = gr.Button("Generate Animation") | |
with gr.Column(): | |
# Output components | |
output_image = gr.Image(label="Generated Animation", type="filepath") | |
# Connect components | |
generate_btn.click( | |
fn=generate_animation, | |
inputs=[description, action, direction, num_frames], | |
outputs=output_image | |
) | |
return interface | |
# Launch the application | |
if __name__ == "__main__": | |
interface = create_interface() | |
interface.launch(share=True) |