Update app.py

app.py

@@ -3,58 +3,14 @@ from gradio_client import Client, handle_file
 from PIL import Image
 import tempfile, os, time, random
 
-# ══════════════════════════════════════════════════════════════════
-# CPU-ONLY VERSION — No GPU needed, No ZeroGPU subscription
-# Strategy: Call HF Space APIs (3 backup spaces)
-#           If all busy → friendly retry message
-# ══════════════════════════════════════════════════════════════════
-
-# Multiple backup spaces — tries each one
 SPACES = [
     "yisol/IDM-VTON",
-    "yisol/IDM-VTON-DC",
     "Nymbo/Virtual-Try-On",
 ]
 
-def save_tmp(img: Image.Image) -> str:
-    p = tempfile.mktemp(suffix=".jpg")
-    img.save(p, quality=95)
-    return p
-
-def cleanup(*paths):
-    for p in paths:
-        try:
-            if p and os.path.exists(p): os.remove(p)
-        except: pass
-
-def auto_crop(cloth: Image.Image) -> bool:
-    return (cloth.height / max(cloth.width, 1)) > 1.3
-
-def try_space(space, person, cloth, steps, seed):
-    """Try one HF Space — returns result image or raises."""
-    p, c = save_tmp(person), save_tmp(cloth)
-    try:
-        client = Client(space, verbose=False)
-        result = client.predict(
-            dict={"background": handle_file(p), "layers": [], "composite": None},
-            garm_img        = handle_file(c),
-            garment_des     = "clothing item",
-            is_checked      = True,
-            is_checked_crop = auto_crop(cloth),
-            denoise_steps   = steps,
-            seed            = seed,
-            api_name        = "/tryon"
-        )
-        cleanup(p, c)
-        return Image.open(result[0]).convert("RGB")
-    except Exception as e:
-        cleanup(p, c)
-        raise e
-
-
 def virtual_tryon(person_img, cloth_img, quality):
     if person_img is None:
-        return None, "⚠️ Please upload your photo first!"
+        return None, "⚠️ Please upload your photo!"
     if cloth_img is None:
         return None, "⚠️ Please upload a clothing image!"
 
@@ -62,99 +18,128 @@ def virtual_tryon(person_img, cloth_img, quality):
     seed  = random.randint(0, 9999)
     t0    = time.time()
 
-    last_error = ""
+    # Save uploaded images to temp files
+    p_path = tempfile.mktemp(suffix=".jpg")
+    c_path = tempfile.mktemp(suffix=".jpg")
+    person_img.save(p_path)
+    cloth_img.save(c_path)
+
+    # Auto detect dress vs top
+    is_dress = (cloth_img.height / max(cloth_img.width, 1)) > 1.3
+
     for space in SPACES:
         try:
             print(f"Trying {space}...")
-            result = try_space(space, person_img, cloth_img, steps, seed)
-            elapsed = time.time() - t0
-            short = space.split("/")[-1]
-            return result, f"✅ Done in {elapsed:.1f}s via {short}!"
+            client = Client(space, verbose=False)
+            result = client.predict(
+                dict={
+                    "background": handle_file(p_path),
+                    "layers": [],
+                    "composite": None
+                },
+                garm_img        = handle_file(c_path),
+                garment_des     = "dress" if is_dress else "shirt",
+                is_checked      = True,
+                is_checked_crop = is_dress,
+                denoise_steps   = steps,
+                seed            = seed,
+                api_name        = "/tryon"
+            )
+            # Cleanup temp files
+            try: os.remove(p_path)
+            except: pass
+            try: os.remove(c_path)
+            except: pass
+
+            result_img = Image.open(result[0]).convert("RGB")
+            elapsed    = time.time() - t0
+            return result_img, f"✅ Done in {elapsed:.1f}s!"
+
         except Exception as e:
-            last_error = str(e)
-            if "TooManyRequests" in last_error or "429" in last_error:
-                print(f"⏳ {space} busy, trying next...")
-                time.sleep(5)
-                continue
-            print(f"❌ {space} error: {last_error[:80]}")
+            print(f"❌ {space} failed: {str(e)[:80]}")
+            time.sleep(3)
             continue
 
-    # All spaces failed
-    if "TooManyRequests" in last_error or "429" in last_error:
-        return None, (
-            "⏳ All servers are busy right now.\n"
-            "Please wait 2-3 minutes and try again!\n"
-            "💡 Tip: Try during off-peak hours (early morning or late night)"
-        )
-    return None, f"❌ Could not connect. Please try again. ({last_error[:100]})"
+    # Cleanup
+    try: os.remove(p_path)
+    except: pass
+    try: os.remove(c_path)
+    except: pass
+
+    return None, "⏳ Servers busy — please wait 2 minutes and try again!"
 
 
-# ── UI ────────────────────────────────────────────────────────────
 with gr.Blocks(
-    title="👗 AI Virtual Try-On",
+    title="AI Virtual Try-On",
     theme=gr.themes.Soft(primary_hue="violet", secondary_hue="pink"),
-    css="""
-    .tip { background:linear-gradient(135deg,#f0e8ff,#ffe8f4);
-           border-radius:14px; padding:12px 16px;
-           font-size:.85em; color:#555; margin-top:8px;
-           border:1px solid #e0d0ff }
-    footer { display:none !important }
-    """
 ) as demo:
 
     gr.HTML("""
-    <div style="text-align:center;padding:24px 0 12px">
-      <h1 style="font-size:2.4em;font-weight:900;
-                 background:linear-gradient(90deg,#7c3aed,#db2777);
-                 -webkit-background-clip:text;-webkit-text-fill-color:transparent">
+    <div style='text-align:center;padding:20px 0'>
+      <h1 style='font-size:2.2em;font-weight:900;
+        background:linear-gradient(90deg,#7c3aed,#db2777);
+        -webkit-background-clip:text;-webkit-text-fill-color:transparent'>
         👗 AI Virtual Try-On
       </h1>
-      <p style="color:#888;font-size:1em;margin-top:4px">
-        Upload your photo + clothing — see how it looks on you!<br>
-        <b style="color:#7c3aed">Powered by IDM-VTON · Auto-detects garment type</b>
-      </p>
+      <p style='color:#888'>Upload your photo + clothing — AI shows how it looks on you!</p>
     </div>
     """)
 
-    with gr.Row(equal_height=True):
+    with gr.Row():
         with gr.Column():
             gr.Markdown("### 📷 Step 1 — Your Photo")
-            p_in = gr.Image(label="Upload full-body photo", type="pil", height=380)
-            gr.HTML('<div class="tip">💡 Stand straight · Full body visible · Good lighting · Plain background</div>')
+            p_in = gr.Image(label="Full-body photo", type="pil", height=380)
+            gr.HTML("<div style='background:#f5f0ff;border-radius:12px;padding:10px 14px;font-size:.85em;color:#555;margin-top:8px'>💡 Stand straight · Good lighting · Plain background</div>")
 
         with gr.Column():
             gr.Markdown("### 👗 Step 2 — Clothing Item")
-            c_in = gr.Image(label="Upload clothing product photo", type="pil", height=380)
-            gr.HTML('<div class="tip">💡 White background product photo · AI auto-detects dress vs top</div>')
+            c_in = gr.Image(label="Clothing product photo", type="pil", height=380)
+            gr.HTML("<div style='background:#f5f0ff;border-radius:12px;padding:10px 14px;font-size:.85em;color:#555;margin-top:8px'>💡 White background · AI detects garment type automatically</div>")
 
         with gr.Column():
-            gr.Markdown("### ✨ Step 3 — Result")
+            gr.Markdown("### ✨ Step 3 — Your Result")
             r_out  = gr.Image(label="Try-On Result", type="pil", height=380)
-            status = gr.Textbox(label="Status", interactive=False,
-                                placeholder="Result will appear here…")
+            status = gr.Textbox(label="Status", interactive=False)
 
     with gr.Row():
         quality = gr.Radio(
             ["Fast ⚡", "Balanced ⚖️", "Best Quality 💎"],
             value="Balanced ⚖️",
             label="Quality",
-            info="Fast=20 steps · Balanced=30 · Best=40",
-            scale=2,
+            scale=2
         )
-        gr.Button("🚀 Generate Try-On!", variant="primary", size="lg", scale=1).click(
+        gr.Button(
+            "🚀 Generate Try-On!", variant="primary", size="lg", scale=1
+        ).click(
             fn=virtual_tryon,
             inputs=[p_in, c_in, quality],
-            outputs=[r_out, status],
+            outputs=[r_out, status]
         )
 
     gr.HTML("""
-    <div style="text-align:center;margin-top:18px;padding:14px;
-                background:linear-gradient(135deg,#f5f0ff,#fff0f8);
-                border-radius:14px;color:#666;font-size:.85em;
-                border:1px solid #e8d8ff">
-      🤖 Uses <b>IDM-VTON API</b> with 3 backup servers ·
-      Auto-retries if busy · No GPU subscription needed · 100% Free
+    <div style='text-align:center;margin-top:16px;padding:12px;
+      background:#f8f4ff;border-radius:12px;color:#666;font-size:.83em'>
+      🤖 Powered by IDM-VTON · Auto-detects garment type · 100% Free
     </div>
     """)
 
-demo.launch()
+demo.launch()
+```
+
+---
+
+## Fix `README.md` — paste this:
+```
+---
+title: AI Virtual Try-On
+emoji: 👗
+colorFrom: purple
+colorTo: pink
+sdk: gradio
+sdk_version: 5.23.0
+app_file: app.py
+pinned: true
+license: mit
+---
+
+# 👗 AI Virtual Try-On