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| import streamlit as st | |
| from diffusers import StableDiffusionImg2ImgPipeline | |
| import torch | |
| from PIL import Image | |
| import os | |
| # Inisialisasi pipeline model | |
| def load_model(): | |
| model = StableDiffusionImg2ImgPipeline.from_pretrained( | |
| "runwayml/stable-diffusion-v1-5", | |
| torch_dtype=torch.float16 | |
| ) | |
| model.to("cuda") # Gunakan GPU untuk performa optimal | |
| return model | |
| # Header aplikasi | |
| st.title("Stable Diffusion Image-to-Image Generator") | |
| st.write("🎨 Unggah gambar dan tambahkan deskripsi untuk menghasilkan gambar baru!") | |
| # Input teks dari pengguna | |
| prompt = st.text_input("Masukkan teks deskripsi gambar:", "") | |
| negative_prompt = st.text_input("Masukkan teks untuk menghindari elemen tertentu (Negative Prompt):", "") | |
| # Opsi parameter tambahan | |
| guidance_scale = st.slider("Guidance Scale (Semakin tinggi, semakin spesifik gambar)", 1.0, 20.0, 7.5) | |
| strength = st.slider("Strength (Pengaruh gambar asli, 0=mirip, 1=berbeda)", 0.1, 1.0, 0.75) | |
| steps = st.slider("Jumlah Langkah Inferensi", 10, 50, 30) | |
| # Input gambar dari pengguna | |
| uploaded_file = st.file_uploader("Unggah gambar awal (Input Image)", type=["jpg", "jpeg", "png"]) | |
| # Tombol untuk menghasilkan gambar | |
| if st.button("Generate") and prompt and uploaded_file: | |
| with st.spinner("Sedang menghasilkan gambar..."): | |
| # Load model | |
| model = load_model() | |
| # Buka dan proses gambar | |
| init_image = Image.open(uploaded_file).convert("RGB") | |
| init_image = init_image.resize((512, 512)) # Sesuaikan ukuran gambar ke 512x512 | |
| # Proses image-to-image | |
| image = model( | |
| prompt=prompt, | |
| negative_prompt=negative_prompt if negative_prompt else None, | |
| image=init_image, | |
| strength=strength, | |
| guidance_scale=guidance_scale, | |
| num_inference_steps=steps | |
| ).images[0] # Ambil gambar pertama dari hasil | |
| # Tampilkan hasil gambar | |
| st.image(image, caption="Gambar yang dihasilkan", use_column_width=True) | |
| # Simpan gambar ke folder assets | |
| if not os.path.exists("assets/"): | |
| os.makedirs("assets/") | |
| save_path = f"assets/{prompt.replace(' ', '_')}_neg_{negative_prompt.replace(' ', '_') if negative_prompt else 'none'}.png" | |
| image.save(save_path) | |
| st.success(f"Gambar telah disimpan di {save_path}") | |
| else: | |
| if not prompt: | |
| st.warning("Masukkan deskripsi untuk memulai.") | |
| if not uploaded_file: | |
| st.warning("Unggah gambar untuk memulai.") | |
| # Tampilan gambar sebelumnya | |
| st.subheader("Gambar Sebelumnya") | |
| if os.path.exists("assets/"): | |
| for img_file in os.listdir("assets/"): | |
| st.image(f"assets/{img_file}", caption=img_file, use_column_width=True) | |