File size: 2,523 Bytes
64d8b45 | 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 | import gradio as gr
import torch
from diffusers import LTXVideoPipeline
from huggingface_hub import login
import os
# Memuat pipeline LTX-Video dasar dari Hugging Face
# Model LTX-Video membutuhkan tipe data bfloat16 untuk efisiensi VRAM
pipe = LTXVideoPipeline.from_pretrained(
"Lightricks/LTX-Video",
torch_dtype=torch.bfloat16
)
# Memuat bobot LoRA Black Magic milik FuzzPuppy ke dalam pipeline
pipe.load_lora_weights(
"FuzzPuppy/LTX-2.3-Black-Magic-LoRA",
weight_name="pytorch_lora_weights.safetensors",
adapter_name="black_magic"
)
pipe.to("cuda")
def generate_video(prompt, negative_prompt, num_frames, fps, guidance_scale):
# Mengonfigurasi parameter teks dan menjalankan inferensi
video_frames = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
num_inference_steps=30,
num_frames=int(num_frames),
guidance_scale=float(guidance_scale),
generator=torch.manual_seed(-1)
).frames[0]
# Menyimpan frame video sementara ke format MP4
output_path = "output_generated.mp4"
# Catatan: Diffusers LTXVideo memproses penyimpanan video internal atau menggunakan manual export
# Di bawah ini adalah contoh logika penyimpanan bawaan diffusers untuk video
from diffusers.utils import export_to_video
export_to_video(video_frames, output_path, fps=int(fps))
return output_path
# Membuat Antarmuka Grafis Menggunakan Gradio
with gr.Blocks() as demo:
gr.Markdown("# LTX-2.3 Black Magic LoRA Demo")
gr.Markdown("Buat video cinematic magis menggunakan model dasar LTX-Video yang dipadukan dengan LoRA Black Magic.")
with gr.Row():
with gr.Column():
prompt = gr.Textbox(label="Prompt", placeholder="A wizard casting a dark magic spell, cinematic lighting, 4k...")
negative_prompt = gr.Textbox(label="Negative Prompt", value="low quality, blurry, distorted")
frames = gr.Slider(minimum=16, maximum=64, step=8, value=32, label="Jumlah Frame (Durasi)")
fps = gr.Slider(minimum=8, maximum=24, step=2, value=16, label="FPS")
guidance = gr.Slider(minimum=1.0, maximum=10.0, step=0.5, value=5.0, label="Guidance Scale")
btn = gr.Button("Generate Video")
with gr.Column():
output_video = gr.Video(label="Hasil Video")
btn.click(
fn=generate_video,
inputs=[prompt, negative_prompt, frames, fps, guidance],
outputs=output_video
)
demo.launch()
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