feat: add 2x upscale with high quality smoothing

app.py

@@ -7,65 +7,68 @@ import zipfile
 import tempfile
 import shutil
 
-def process_image(img, strength):
-    # Görseli gri tonlamaya çevir ve normalize et
+def process_image(img, strength, upscale=False):
+    if upscale:
+        # Resize to 2x using LANCZOS for high-quality smoothing
+        new_size = (img.width * 2, img.height * 2)
+        img = img.resize(new_size, resample=Image.LANCZOS)
+
+    # Convert to grayscale and normalize
     img_cv = np.array(img.convert('L'))
     img_cv = img_cv.astype(np.float32) / 255.0
 
-    # Sobel filtresi ile X ve Y yönlerindeki gradyanları (eğimleri) hesapla
+    # Sobel filters for gradients
     sobelx = cv2.Sobel(img_cv, cv2.CV_64F, 1, 0, ksize=3)
     sobely = cv2.Sobel(img_cv, cv2.CV_64F, 0, 1, ksize=3)
 
-    # Normal vektörü bileşenlerini hesapla (-dz/dx, -dz/dy, 1)
+    # Normal vector components (-dz/dx, -dz/dy, 1)
     nx = -sobelx * strength
     ny = -sobely * strength
     nz = np.ones_like(img_cv)
 
-    # Vektörleri normalize et (uzunluklarını 1 yap)
+    # Normalize vectors
     length = np.sqrt(nx**2 + ny**2 + nz**2)
     nx /= length
     ny /= length
     nz /= length
 
-    # [-1, 1] aralığını RGB için [0, 255] aralığına çevir
+    # Convert [-1, 1] to [0, 255] for RGB
     nx = (nx + 1) / 2 * 255
     ny = (ny + 1) / 2 * 255
     nz = (nz + 1) / 2 * 255
 
-    # R=X, G=Y, B=Z olacak şekilde birleştir
+    # Merge to RGB (R=X, G=Y, B=Z)
     normal_map = np.stack((nx, ny, nz), axis=-1).astype(np.uint8)
     return Image.fromarray(normal_map)
 
-def process_single(image, strength):
+def process_single(image, strength, upscale):
     if image is None:
         return None
-    return process_image(image, strength)
+    return process_image(image, strength, upscale)
 
-def process_files(file_objs, strength):
+def process_files(file_objs, strength, upscale):
     if not file_objs:
         return None
     
-    # Geçici bir klasör ve ZIP dosyası oluştur
+    # Create temp directory and ZIP file
     temp_dir = tempfile.mkdtemp()
     zip_filename = "normal_maps.zip"
     zip_path = os.path.join(tempfile.gettempdir(), zip_filename)
     
     with zipfile.ZipFile(zip_path, 'w') as zipf:
         for file_obj in file_objs:
-            # Gradio dosya yollarını liste olarak verir
             file_path = file_obj.name if hasattr(file_obj, 'name') else file_obj
             file_name = os.path.basename(file_path)
             
             if file_name.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.webp')):
                 try:
                     img = Image.open(file_path)
-                    normal_map = process_image(img, strength)
+                    normal_map = process_image(img, strength, upscale)
                     
                     base_name, ext = os.path.splitext(file_name)
                     out_name = f"{base_name}_normalmap{ext}"
                         
                     out_path = os.path.join(temp_dir, out_name)
-                    # Orijinal uzantıya göre kaydetmeye çalış, hata olursa PNG yap
                     try:
                         normal_map.save(out_path)
                     except:
@@ -75,9 +78,9 @@ def process_files(file_objs, strength):
                         
                     zipf.write(out_path, arcname=out_name)
                 except Exception as e:
-                    print(f"Hata ({file_path}): {e}")
+                    print(f"Error ({file_path}): {e}")
     
-    # Geçici klasörü temizle
+    # Cleanup temp directory
     shutil.rmtree(temp_dir)
     return zip_path
 
@@ -93,11 +96,12 @@ with gr.Blocks(title="Normal Map Generator", theme=gr.themes.Soft()) as demo:
                 with gr.Column():
                     img_input = gr.Image(type="pil", label="Input Image")
                     strength_slider_1 = gr.Slider(minimum=0.1, maximum=10.0, value=2.0, step=0.1, label="Normal Map Strength")
+                    upscale_check_1 = gr.Checkbox(label="Upscale 2x (High Quality Smoothing)", value=False)
                     btn_single = gr.Button("Generate", variant="primary")
                 with gr.Column():
                     img_output = gr.Image(type="pil", label="Normal Map Result", format="png")
             
-            btn_single.click(fn=process_single, inputs=[img_input, strength_slider_1], outputs=img_output)
+            btn_single.click(fn=process_single, inputs=[img_input, strength_slider_1, upscale_check_1], outputs=img_output)
             
         # FOLDER/BATCH TAB
         with gr.Tab("Folder (Batch Processing)"):
@@ -107,11 +111,12 @@ with gr.Blocks(title="Normal Map Generator", theme=gr.themes.Soft()) as demo:
                     # file_count="directory" allows folder upload
                     folder_input = gr.File(file_count="directory", label="Upload Folder / Files")
                     strength_slider_2 = gr.Slider(minimum=0.1, maximum=10.0, value=2.0, step=0.1, label="Normal Map Strength")
+                    upscale_check_2 = gr.Checkbox(label="Upscale 2x (High Quality Smoothing)", value=False)
                     btn_folder = gr.Button("Generate Batch and Download", variant="primary")
                 with gr.Column():
                     file_output = gr.File(label="Download ZIP File")
             
-            btn_folder.click(fn=process_files, inputs=[folder_input, strength_slider_2], outputs=file_output)
+            btn_folder.click(fn=process_files, inputs=[folder_input, strength_slider_2, upscale_check_2], outputs=file_output)
 
 if __name__ == "__main__":
     demo.launch()