import gradio as gr
import numpy as np
import cv2
import os
import time
import requests
import sys
from PIL import Image
# ─── FIX FOR BASICSR & TORCHVISION ────────────────────────────────────────────
import torchvision.transforms.functional
sys.modules['torchvision.transforms.functional_tensor'] = torchvision.transforms.functional
# ──────────────────────────────────────────────────────────────────────────────
# ─── Model Download ───────────────────────────────────────────────────────────
MODEL_DIR = "weights"
MODEL_PATH = os.path.join(MODEL_DIR, "RealESRGAN_x4plus.pth")
MODEL_URL = "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth"
def download_model():
os.makedirs(MODEL_DIR, exist_ok=True)
if not os.path.exists(MODEL_PATH):
print("📥 মডেল ডাউনলোড হচ্ছে...")
r = requests.get(MODEL_URL, stream=True)
with open(MODEL_PATH, "wb") as f:
for chunk in r.iter_content(chunk_size=8192):
f.write(chunk)
print("✅ মডেল ডাউনলোড সম্পন্ন!")
download_model()
# ─── Real-ESRGAN Setup ────────────────────────────────────────────────────────
from basicsr.archs.rrdbnet_arch import RRDBNet
from realesrgan import RealESRGANer
def load_upsampler():
model = RRDBNet(
num_in_ch=3, num_out_ch=3,
num_feat=64, num_block=23, num_grow_ch=32, scale=4
)
upsampler = RealESRGANer(
scale=4,
model_path=MODEL_PATH,
model=model,
tile=128,
tile_pad=10,
pre_pad=0,
half=False
)
return upsampler
print("🔄 মডেল লোড হচ্ছে...")
upsampler = load_upsampler()
print("✅ মডেল রেডি!")
# ─── Image Analysis ───────────────────────────────────────────────────────────
def analyze_image(img: Image.Image) -> dict:
w, h = img.size
mp = (w * h) / 1_000_000
if w >= 3840 or h >= 2160:
quality_label = "4K বা তার বেশি (Ultra HD)"
quality_icon = "🟣"
elif w >= 1920 or h >= 1080:
quality_label = "1080p Full HD"
quality_icon = "🟢"
elif w >= 1280 or h >= 720:
quality_label = "720p HD"
quality_icon = "🟡"
elif w >= 854 or h >= 480:
quality_label = "480p SD"
quality_icon = "🟠"
else:
quality_label = "লো রেজোলিউশন"
quality_icon = "🔴"
mode_label = {"RGB": "রঙিন (RGB)", "RGBA": "রঙিন + Transparency", "L": "কালো-সাদা"}.get(img.mode, img.mode)
return {
"width": w, "height": h,
"megapixels": round(mp, 2),
"quality_label": quality_label,
"quality_icon": quality_icon,
"mode": mode_label,
"target_w": 3840, "target_h": 2160
}
# ─── Main Processing ──────────────────────────────────────────────────────────
def upscale_to_4k(pil_img):
if pil_img is None:
yield None, "❌ কোনো ছবি আপলোড করা হয়নি।", None, ""
return
t_start = time.time()
yield None, "🔍 **ছবি বিশ্লেষণ হচ্ছে...**", None, "⏳ প্রসেসিং শুরু হয়েছে"
time.sleep(0.3)
pil_img = pil_img.convert("RGB")
info = analyze_image(pil_img)
analysis_text = f"""
## 📊 ছবি বিশ্লেষণ ফলাফল
| তথ্য | মান |
| :--- | :--- |
| {info['quality_icon']} বর্তমান কোয়ালিটি | **{info['quality_label']}** |
| 📐 বর্তমান রেজোলিউশন | **{info['width']} × {info['height']} px** |
| 📷 মেগাপিক্সেল | **{info['megapixels']} MP** |
| 🎯 টার্গেট রেজোলিউশন | **3840 × 2160 (4K)** |
---
⚡ **AI Upscaling শুরু হচ্ছে (১-২ মিনিট সময় দিন)...**
"""
yield None, analysis_text, None, "🔄 AI প্রসেসিং চলছে..."
img_np = np.array(pil_img)
img_bgr = cv2.cvtColor(img_np, cv2.COLOR_RGB2BGR)
try:
output_bgr, _ = upsampler.enhance(img_bgr, outscale=4)
except Exception as e:
yield None, f"❌ **এরর:** সার্ভার ওভারলোড হয়েছে, আবার চেষ্টা করুন।", None, "❌ ব্যর্থ হয়েছে"
return
output_rgb = cv2.cvtColor(output_bgr, cv2.COLOR_BGR2RGB)
output_pil = Image.fromarray(output_rgb)
out_w, out_h = output_pil.size
if out_w != 3840 or out_h != 2160:
output_pil = output_pil.resize((3840, 2160), Image.LANCZOS)
t_end = time.time()
elapsed = t_end - t_start
mins = int(elapsed // 60)
secs = int(elapsed % 60)
time_str = f"{mins} মিনিট {secs} সেকেন্ড" if mins > 0 else f"{secs} সেকেন্ড"
out_path = "/tmp/4k_output.png"
output_pil.save(out_path, "PNG", optimize=False)
file_size_mb = os.path.getsize(out_path) / (1024 * 1024)
result_text = f"""
## ✅ 4K Upscaling সম্পন্ন!
| ফলাফল | মান |
| :--- | :--- |
| 🎯 আউটপুট রেজোলিউশন | **3840 × 2160 (4K Ultra HD)** |
| 📁 ফাইল সাইজ | **{file_size_mb:.1f} MB** |
| ⏱️ সময় লেগেছে | **{time_str}** |
| ✨ আপস্কেল রেশিও | **অটোম্যাটিক 4K এনালাইসিস** |
| 🧠 মডেল | **Real-ESRGAN x4plus** |
---
💾 নিচের ছবিতে রাইট ক্লিক করে **"Save Image"** দিয়ে ডাউনলোড করুন অথবা ডাউনলোড বাটনে চাপুন।
"""
time_display = f"✅ {time_str} এ সম্পন্ন | 3840×2160 (4K)"
yield output_pil, result_text, out_path, time_display
# ─── Custom CSS ───────────────────────────────────────────────────────────────
CSS = """
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;600;700&display=swap');
* { font-family: 'Inter', sans-serif; box-sizing: border-box; }
body, .gradio-container {
background: #0a0a0f !important;
color: #e8e8f0 !important;
}
.gradio-container {
max-width: 1100px !important;
margin: 0 auto !important;
padding: 20px !important;
}
#header {
text-align: center;
padding: 40px 20px 30px;
background: linear-gradient(135deg, #1a1a2e 0%, #16213e 50%, #0f3460 100%);
border-radius: 20px;
margin-bottom: 24px;
border: 1px solid #2a2a4a;
}
#header h1 {
font-size: 2.8rem;
font-weight: 700;
background: linear-gradient(90deg, #00d4ff, #7b2ff7, #ff6b6b);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
margin: 0 0 10px;
}
#header p {
color: #8888aa;
font-size: 1.05rem;
margin: 0;
}
.badge-row {
display: flex;
justify-content: center;
gap: 12px;
flex-wrap: wrap;
margin-top: 16px;
}
.badge {
background: rgba(0,212,255,0.1);
border: 1px solid rgba(0,212,255,0.3);
color: #00d4ff;
padding: 5px 14px;
border-radius: 20px;
font-size: 0.82rem;
font-weight: 600;
}
#timer-box {
background: linear-gradient(135deg, #1a1a2e, #0f1923);
border: 1px solid #2a3a5a;
border-radius: 14px;
padding: 16px 24px;
text-align: center;
font-size: 1.1rem;
font-weight: 600;
color: #00d4ff;
margin-bottom: 16px;
min-height: 54px;
display: flex;
align-items: center;
justify-content: center;
}
.upload-zone label {
font-size: 1rem !important;
font-weight: 600 !important;
color: #aaaacc !important;
}
#upscale-btn {
background: linear-gradient(135deg, #7b2ff7, #00d4ff) !important;
border: none !important;
color: white !important;
font-size: 1.1rem !important;
font-weight: 700 !important;
padding: 14px 32px !important;
border-radius: 12px !important;
cursor: pointer !important;
transition: all 0.3s !important;
width: 100% !important;
letter-spacing: 0.5px !important;
}
#upscale-btn:hover {
transform: translateY(-2px) !important;
box-shadow: 0 8px 30px rgba(123,47,247,0.5) !important;
}
.panel {
background: #111122 !important;
border: 1px solid #2a2a4a !important;
border-radius: 16px !important;
padding: 20px !important;
}
.result-markdown {
background: #0d0d1f !important;
border-radius: 12px;
padding: 16px;
}
footer { display: none !important; }
"""
# ─── UI Layout ────────────────────────────────────────────────────────────────
with gr.Blocks(css=CSS, title="4K AI Upscaler") as demo:
gr.HTML("""
""")
timer_display = gr.HTML(
'⏳ ছবি আপলোড করুন এবং বাটন চাপুন
',
elem_id="timer-container"
)
with gr.Row():
with gr.Column(scale=1, elem_classes="panel"):
input_img = gr.Image(
label="📤 ছবি আপলোড করুন",
type="pil",
sources=["upload", "clipboard"],
height=320,
elem_classes="upload-zone"
)
upscale_btn = gr.Button(
"✨ 4K তে রূপান্তর করুন",
elem_id="upscale-btn",
variant="primary"
)
with gr.Column(scale=1, elem_classes="panel"):
output_img = gr.Image(
label="📥 4K আউটপুট",
type="pil",
height=320,
interactive=False
)
with gr.Row():
with gr.Column():
result_md = gr.Markdown(
value="*এখানে বিশ্লেষণ ও ফলাফল দেখাবে...*",
elem_classes="result-markdown"
)
with gr.Column():
download_file = gr.File(
label="💾 4K ফাইল ডাউনলোড করুন",
interactive=False
)
gr.HTML("""
Powered by Real-ESRGAN • Hosted on Hugging Face Spaces 🤗
""")
def run(img_pil):
last = None, "", None, ""
gen = upscale_to_4k(img_pil)
for out_img, md, path, timer in gen:
last = (out_img, md, path, timer)
timer_html = f'{timer}
'
yield out_img, md, path, timer_html
return
upscale_btn.click(
fn=run,
inputs=[input_img],
outputs=[output_img, result_md, download_file, timer_display]
)
if __name__ == "__main__":
demo.queue().launch()