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"""
Image Enhancer App
------------------
Aplikasi berbasis Gradio untuk meningkatkan kualitas gambar dengan berbagai teknik pemrosesan citra
seperti perbaikan resolusi, penajaman, dan penghilangan noise.
Dapat digunakan secara lokal maupun sebagai web-app AI image enhancement.
Created by _drat | 2025
"""
# Import library standar dan eksternal yang dibutuhkan
import os
import subprocess
import spaces # Library dari HuggingFace untuk GPU management & dekorator
import torch # Library untuk deep learning, cek GPU
import cv2 # OpenCV untuk pengolahan gambar
import uuid # Untuk generate nama file unik
import gradio as gr # Untuk membuat UI web berbasis Python
import numpy as np # Operasi numerik, termasuk array
from PIL import Image # Untuk memproses dan menyimpan gambar
# Import arsitektur model dan utilitas untuk enhancement & upscaling
from basicsr.archs.srvgg_arch import SRVGGNetCompact
from gfpgan.utils import GFPGANer
from realesrgan.utils import RealESRGANer
import warnings
warnings.filterwarnings("ignore")
# Fungsi untuk menjalankan command shell (misal: wget file model)
def runcmd(cmd, verbose = False):
process = subprocess.Popen(
cmd,
stdout = subprocess.PIPE,
stderr = subprocess.PIPE,
text = True,
shell = True
)
std_out, std_err = process.communicate()
if verbose:
print(std_out.strip(), std_err)
pass
# Pastikan model AI (GFPGAN dan RealESRGAN) sudah terdownload. Jika belum, otomatis download.
if not os.path.exists('GFPGANv1.4.pth'):
runcmd("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth -P .")
if not os.path.exists('realesr-general-x4v3.pth'):
runcmd("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth -P .")
# Inisialisasi model Real-ESRGAN untuk upscaling gambar
model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
model_path = 'realesr-general-x4v3.pth'
half = True if torch.cuda.is_available() else False # Pakai mode half-precision jika ada GPU (lebih cepat)
upsampler = RealESRGANer(
scale=4, model_path=model_path, model=model,
tile=0, tile_pad=10, pre_pad=0, half=half
)
# Fungsi utama untuk enhance gambar (dipanggil saat tombol di UI ditekan)
@spaces.GPU(duration=15)
def enhance_image(
input_image: Image, # Gambar input dari user (PIL Image)
scale: int, # Skala upscaling (misal: 2x, 4x)
enhance_mode: str, # Mode enhance: face saja, image saja, atau keduanya
):
only_face = enhance_mode == "Only Face Enhance"
# Pilih mode enhancer: hanya wajah, hanya gambar, atau kombinasi
if enhance_mode == "Only Face Enhance":
face_enhancer = GFPGANer(
model_path='GFPGANv1.4.pth', upscale=scale,
arch='clean', channel_multiplier=2
)
elif enhance_mode == "Only Image Enhance":
face_enhancer = None # Tidak enhance wajah, hanya upscaling gambar saja
else:
face_enhancer = GFPGANer(
model_path='GFPGANv1.4.pth', upscale=scale,
arch='clean', channel_multiplier=2, bg_upsampler=upsampler
)
# Konversi gambar input ke format BGR (OpenCV)
img = cv2.cvtColor(np.array(input_image), cv2.COLOR_RGB2BGR)
h, w = img.shape[0:2]
# Optional: perbesar gambar jika terlalu kecil (kurang dari 300px)
if h < 300:
img = cv2.resize(img, (w * 2, h * 2), interpolation=cv2.INTER_LANCZOS4)
# Proses enhance gambar (tergantung mode)
if face_enhancer is not None:
# Enhance wajah (GFPGAN), output gambar hasil enhancement
_, _, output = face_enhancer.enhance(
img, has_aligned=False, only_center_face=only_face, paste_back=True
)
else:
# Hanya upscaling image (tanpa enhance wajah)
output, _ = upsampler.enhance(img, outscale=scale)
# --- Optional resize (tidak digunakan)
# if scale != 2:
# interpolation = cv2.INTER_AREA if scale < 2 else cv2.INTER_LANCZOS4
# h, w = img.shape[0:2]
# output = cv2.resize(output, (int(w * scale / 2), int(h * scale / 2)), interpolation=interpolation)
# Batasi hasil enhance agar tidak lebih dari 3480px (biar aman dan efisien)
h, w = output.shape[0:2]
max_size = 3480
if h > max_size:
w = int(w * max_size / h)
h = max_size
if w > max_size:
h = int(h * max_size / w)
w = max_size
# Resize hasil akhir
output = cv2.resize(output, (w, h), interpolation=cv2.INTER_LANCZOS4)
# Konversi kembali ke RGB & PIL Image (untuk output Gradio)
enhanced_image = Image.fromarray(cv2.cvtColor(output, cv2.COLOR_BGR2RGB))
# Simpan gambar hasil enhance ke folder output dengan nama unik
tmpPrefix = "/tmp/gradio/"
extension = 'png'
# targetDir = f"{tmpPrefix}output/"
targetDir = "output/"
if not os.path.exists(targetDir):
os.makedirs(targetDir)
enhanced_path = f"{targetDir}{uuid.uuid4()}.{extension}"
enhanced_image.save(enhanced_path, quality=100)
return enhanced_image, enhanced_path # Return: image untuk preview dan path file untuk download
#
# DEMO DI SINI
#
def create_demo() -> gr.Blocks:
with gr.Blocks() as demo:
# Feature Image dengan border subtle & shadow
gr.HTML(
"""
<div style='display:flex; justify-content:center;'>
<img src='https://i.ibb.co/jkkT7MZQ/feature-image-enhancer.jpg'
alt='Feature Image'
style='height:200px; width:auto; border-radius:24px; box-shadow:0 4px 18px #ffa07430; border:2.5px solid #ffe0b3;'
id='feature-image'/>
</div>
"""
)
# Judul & Tagline dengan emoji & gradient text
gr.Markdown("""
<div style="text-align:center; margin-top: -10px; margin-bottom: 14px;">
<span style="font-size:2.1rem; font-family:'Quicksand',sans-serif; font-weight:800; background: linear-gradient(90deg,#d84040,#ff914d 60%); -webkit-background-clip: text; color:transparent; display:inline-block;">
<span style="vertical-align:middle;">📸</span> Image Enhancer <b>Pro</b> <span style="font-size:1.1em;vertical-align:middle;">✨</span>
</span><br>
<span style="font-size:1.12rem; color:#d84040; font-family:'Inter',sans-serif;">
<span style="vertical-align:middle;">🤖</span> Foto blur? Jadikan jernih & tajam pakai AI!
</span>
</div>
""")
# Input dan Output dalam card, dengan icon pada title
with gr.Row():
with gr.Column(scale=1):
with gr.Group(elem_id="input-card"):
gr.Markdown("<div class='card-title'><span style='font-size:1.3em;vertical-align:middle;'>🖼️</span> <b>Gambar Asli</b></div>")
input_image = gr.Image(label="", type="pil", elem_id="input-image", show_label=False)
gr.Markdown("<div class='hint'><span style='font-size:1.1em;'>⬆️</span> Upload foto format <b>JPG/PNG</b>, max 5MB</div>")
with gr.Column(scale=1):
with gr.Group(elem_id="output-card"):
gr.Markdown("<div class='card-title'><span style='font-size:1.3em;vertical-align:middle;'>🌈</span> <b>Hasil AI Enhance</b></div>")
output_image = gr.Image(label="", type="pil", interactive=False, elem_id="output-image", show_label=False)
enhance_image_path = gr.File(label="⬇️ Download (.png)", interactive=False, elem_id="download-btn")
gr.Markdown("""
<div class='hint' style="color:#ff914d;"><span style='font-size:1.2em;'>💡</span> Klik untuk download hasilnya!</div>
""")
# Kontrol dengan ikon pada label
with gr.Group(elem_id="control-card"):
with gr.Row():
scale = gr.Slider(
minimum=1,
maximum=4,
value=2,
step=1,
label="🔎 Upscale x",
elem_id="scale-slider"
)
enhance_mode = gr.Dropdown(
label="🛠️ Mode Enhance",
choices=[
"Only Face Enhance",
"Only Image Enhance",
"Face Enhance + Image Enhance",
],
value="Face Enhance + Image Enhance",
elem_id="mode-dropdown"
)
g_btn = gr.Button("🚀 Enhance Sekarang!", elem_id="enhance-btn", size="lg")
g_btn.click(
fn=enhance_image,
inputs=[input_image, scale, enhance_mode],
outputs=[output_image, enhance_image_path],
)
# Footer dengan ikon & sentuhan branding
# Tambahkan footer di bagian bawah
gr.HTML("""
<footer id="footer">
Transfer Energi Semesta Digital © 2024 | 🇮🇩 Untuk Indonesia Jaya!
</footer>
""")
return demo
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