Update app.py

app.py

@@ -2,304 +2,68 @@ 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 ────────────────────────────────────────────
+
+# ─── বাগ ফিক্স ────────────────────────────────────────────────────────────────
 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 ────────────────────────────────────────────────────────
+
+# ─── মডেল সেটআপ ──────────────────────────────────────────────────────────────
+MODEL_PATH = "RealESRGAN_x4plus.pth"
+
+if not os.path.exists(MODEL_PATH):
+    r = requests.get("https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth", stream=True)
+    with open(MODEL_PATH, "wb") as f:
+        for chunk in r.iter_content(chunk_size=8192):
+            f.write(chunk)
+
 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
 
-| তথ���য | 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)** |
+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)
 
----
-⚡ **AI Upscaling শুরু হচ্ছে (১-২ মিনিট সময় দিন)...**
-"""
-    yield None, analysis_text, None, "🔄 AI প্রসেসিং চলছে..."
-    img_np = np.array(pil_img)
+# ─── মূল কাজ (কোনো ফ্যান্সি ডিজাইন ছাড়া) ──────────────────────────────────────
+def process_image(img):
+    if img is None:
+        return None, None
+        
+    # RGB থেকে BGR
+    img_np = np.array(img.convert("RGB"))
     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
+    
+    # 4K আপস্কেল
+    output_bgr, _ = upsampler.enhance(img_bgr, outscale=4)
+    
+    # BGR থেকে RGB
     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!
+    out_img = Image.fromarray(output_rgb)
+    
+    # 4K সাইজ নিশ্চিত করা
+    if out_img.size != (3840, 2160):
+        out_img = out_img.resize((3840, 2160), Image.LANCZOS)
+        
+    # সেভ করা
+    out_path = "/tmp/output.png"
+    out_img.save(out_path, "PNG")
+    
+    return out_img, out_path
 
-| 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
-            )
+# ─── সিম্পল ইউজার ইন্টারফেস ──────────────────────────────────────────────────
+with gr.Blocks() as demo:
+    gr.Markdown("# 🚀 4K AI Upscaler (Basic Version)")
+    gr.Markdown("সব ডিজাইন বাদ দেওয়া হয়েছে। শুধু ছবি আপলোড করুন এবং রেজাল্ট নিন।")
+    
     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]
-    )
+        inp = gr.Image(type="pil", label="ছবি আপলোড করুন")
+        out = gr.Image(type="pil", label="4K আউটপুট")
+        
+    btn = gr.Button("✨ 4K তে রূপান্তর করুন", variant="primary")
+    file_out = gr.File(label="4K ছবি ডাউনলোড করুন")
+    
+    btn.click(fn=process_image, inputs=inp, outputs=[out, file_out])
+
 if __name__ == "__main__":
-    demo.queue().launch()
+    demo.launch()