app.py

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("""
    <div id="header">
        <h1>🚀 4K AI Upscaler</h1>
        <p>যেকোনো ছবি আপলোড করুন — AI স্বয়ংক্রিয়ভাবে বিশ্লেষণ করে ৪K Ultra HD তে রূপান্তর করবে</p>
        <div class="badge-row">
            <span class="badge">⚡ Real-ESRGAN</span>
            <span class="badge">🎯 3840×2160 Output</span>
            <span class="badge">🧠 AI Powered</span>
            <span class="badge">🆓 সম্পূর্ণ বিনামূল্যে</span>
        </div>
    </div>
    """)
    timer_display = gr.HTML(
        '<div id="timer-box">⏳ ছবি আপলোড করুন এবং বাটন চাপুন</div>',
        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("""
    <div style="text-align:center; padding: 20px; color: #555577; font-size:0.85rem;">
        Powered by Real-ESRGAN • Hosted on Hugging Face Spaces 🤗
    </div>
    """)
    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'<div id="timer-box">{timer}</div>'
            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()