Update app.py

app.py

@@ -1,22 +1,28 @@
 import os
+import sys
 import cv2
 import numpy as np
 import requests
-from PIL import Image, ImageEnhance, ImageOps
+from PIL import Image, ImageEnhance, ImageFilter
 from rembg import remove, new_session
 import mediapipe as mp
 import gradio as gr
 
 # Force MediaPipe to use its internal stable solutions
-mp_face_detection = mp.solutions.face_detection
+# This handles the AttributeError: module 'mediapipe' has no attribute 'solutions'
+try:
+    import mediapipe.python.solutions.face_detection as mp_face_detection
+except:
+    import mediapipe.solutions.face_detection as mp_face_detection
 
 # Initialize AI Models at startup
-print("Loading Pro-Grade AI Models...")
-# birefnet-portrait is the world-class cutout model
+print("Step 1: Loading Pro-Grade AI Models...")
+# birefnet-portrait is the industry standard for high-end cutouts
 session = new_session("birefnet-portrait")
 face_detector = mp_face_detection.FaceDetection(model_selection=1, min_detection_confidence=0.5)
 
 # Download Professional Suit Assets
+print("Step 2: Downloading Suit Assets...")
 SUITS = {
     "Navy Blue Business": "https://raw.githubusercontent.com/AIGuy-Official/Passport-Assets/main/suit1.png",
     "Classic Black Formal": "https://raw.githubusercontent.com/AIGuy-Official/Passport-Assets/main/suit2.png"
@@ -24,16 +30,17 @@ SUITS = {
 
 os.makedirs('suits', exist_ok=True)
 for name, url in SUITS.items():
-    if not os.path.exists(f"suits/{name}.png"):
+    suit_path = f"suits/{name}.png"
+    if not os.path.exists(suit_path):
         try:
             r = requests.get(url, timeout=10)
-            with open(f"suits/{name}.png", 'wb') as f: f.write(r.content)
+            with open(suit_path, 'wb') as f: f.write(r.content)
         except: pass
 
 def make_passport(input_image, suit_choice, bg_color):
     if input_image is None: return None
     
-    # 1. Image Preparation
+    # 1. Prepare Images
     pil_img = Image.fromarray(input_image).convert("RGBA")
     np_img = cv2.cvtColor(input_image, cv2.COLOR_RGB2BGR)
     h, w, _ = np_img.shape
@@ -43,76 +50,78 @@ def make_passport(input_image, suit_choice, bg_color):
     if not results.detections:
         return None 
     
-    # Get coordinates
+    # Get Detection Box
     bbox = results.detections[0].location_data.relative_bounding_box
     fx, fy, fw, fh = int(bbox.xmin * w), int(bbox.ymin * h), int(bbox.width * w), int(bbox.height * h)
     
-    # 3. Professional Passport Math (Compliance)
-    # Head must be 50-70% of the image height
-    margin_top = int(fh * 0.4)
-    margin_bottom = int(fh * 1.5)
+    # 3. Calculated Passport Crop (Professional Rules)
+    # Head should take up roughly 60% of the vertical space
+    margin_top = int(fh * 0.5) 
+    margin_bottom = int(fh * 1.8) # Room for suit/shoulders
     
     crop_y1 = max(0, fy - margin_top)
     crop_y2 = min(h, fy + fh + margin_bottom)
     
-    # Crop to maintain aspect ratio for a square 1:1 passport
-    crop_width = (crop_y2 - crop_y1)
+    # Keep it 1:1 Aspect Ratio (Square)
+    crop_h = crop_y2 - crop_y1
     center_x = fx + (fw // 2)
-    crop_x1 = max(0, center_x - (crop_width // 2))
-    crop_x2 = min(w, center_x + (crop_width // 2))
+    crop_x1 = max(0, center_x - (crop_h // 2))
+    crop_x2 = min(w, center_x + (crop_h // 2))
     
     person_crop = pil_img.crop((crop_x1, crop_y1, crop_x2, crop_y2))
 
-    # 4. Expert Background Removal
+    # 4. Premium Background Removal
+    # We remove BG from the crop for maximum speed and quality
     no_bg = remove(person_crop, session=session, alpha_matting=True)
 
     # 5. Create Background Layer
-    hex_c = bg_color.lstrip('#')
-    rgb_c = tuple(int(hex_c[i:i+2], 16) for i in (0, 2, 4))
-    canvas = Image.new("RGBA", no_bg.size, rgb_c + (255,))
+    bg_hex = bg_color.lstrip('#')
+    bg_rgb = tuple(int(bg_hex[i:i+2], 16) for i in (0, 2, 4))
+    canvas = Image.new("RGBA", no_bg.size, bg_rgb + (255,))
 
-    # 6. Apply Suit (The Layering Trick)
-    if suit_choice != "None":
+    # 6. Advanced Suit Layering
+    if suit_choice != "None" and os.path.exists(f"suits/{suit_choice}.png"):
         suit_img = Image.open(f"suits/{suit_choice}.png").convert("RGBA")
         
-        # Scale suit to 3.2x face width
-        target_sw = int((fw/w * no_bg.width) * 3.2)
+        # Scale suit width to be 3.4x the detected face width
+        target_suit_w = int((fw / w * no_bg.width) * 3.4)
         aspect = suit_img.size[1] / suit_img.size[0]
-        suit_res = suit_img.resize((target_sw, int(target_sw * aspect)), Image.Resampling.LANCZOS)
+        suit_res = suit_img.resize((target_suit_w, int(target_suit_w * aspect)), Image.Resampling.LANCZOS)
         
-        # Calculate neck position
-        px = (canvas.width - target_sw) // 2
-        py = int((fy - crop_y1)/person_crop.height * canvas.height + (fh/person_crop.height * canvas.height) * 0.9)
+        # Place suit exactly under the chin
+        px = (canvas.width - target_suit_w) // 2
+        py = int((fy - crop_y1) / person_crop.height * canvas.height + (fh / person_crop.height * canvas.height) * 0.95)
         
-        # Paste suit ONTO background first
+        # Paste suit on BG, THEN paste person on top (collars look real)
         canvas.paste(suit_res, (px, py), suit_res)
         
-    # Paste person ONTO the canvas (covering the suit collar correctly)
+    # Layer the person over the suit
     canvas.paste(no_bg, (0, 0), no_bg)
 
-    # 7. Final High-Quality Resize & Polish
+    # 7. Final Polish (DSLR Quality)
     final = canvas.resize((600, 600), Image.Resampling.LANCZOS)
     
-    # Auto-leveling (Studio lighting effect)
-    final = ImageEnhance.Sharpness(final).enhance(1.4)
-    final = ImageEnhance.Contrast(final).enhance(1.1)
+    # Enhance sharpness and contrast for a "studio" look
+    final = ImageEnhance.Sharpness(final).enhance(1.5)
+    final = ImageEnhance.Contrast(final).enhance(1.15)
+    final = ImageEnhance.Brightness(final).enhance(1.05)
     
     return final.convert("RGB")
 
 # --- CUSTOM THEME UI ---
-with gr.Blocks(theme=gr.themes.Soft()) as app:
-    gr.Markdown("# 👔 AI Studio Passport Maker")
-    gr.Markdown("Zero-cost, High-Quality, and Unlimited.")
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue")) as app:
+    gr.Markdown("# 👔 AI Passport Photo Studio (Expert Version)")
+    gr.Markdown("High-quality, Auto-Crop, and Suit Alignment. Unlimited usage.")
     
     with gr.Row():
         with gr.Column():
             img_in = gr.Image(label="1. Upload Selfie", type="numpy")
-            suit_in = gr.Dropdown(choices=["None"] + list(SUITS.keys()), label="2. Choose Suit", value="None")
+            suit_in = gr.Dropdown(choices=["None"] + list(SUITS.keys()), label="2. Select Suit", value="None")
             bg_in = gr.ColorPicker(label="3. Background Color", value="#FFFFFF")
-            btn = gr.Button("Generate Passport Photo", variant="primary")
+            btn = gr.Button("Generate Professional Passport", variant="primary")
         
         with gr.Column():
-            img_out = gr.Image(label="Download Result (600x600px)")
+            img_out = gr.Image(label="Result (600x600px Print Ready)")
 
     btn.click(make_passport, inputs=[img_in, suit_in, bg_in], outputs=img_out)