Upload app.py

app.py

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+import gradio as gr
+import torch
+import os
+import sys
+from huggingface_hub import login
+import base64
+import io
+from PIL import Image
+import requests
+import tempfile
+
+# Force CPU usage if needed
+device = "cuda" if torch.cuda.is_available() else "cpu"
+print(f"Using device: {device}")
+
+# More details about the environment
+print(f"Gradio version: {gr.__version__}")
+print(f"Python version: {sys.version}")
+
+# Hugging Face API token'ı - önce environment variable olarak ara, 
+# sonra Hugging Face Secrets sisteminde ara
+hf_token = os.environ.get("HUGGINGFACE_TOKEN")
+if hf_token:
+    print("Found HUGGINGFACE_TOKEN in environment variables")
+    # Token ile giriş yap
+    login(token=hf_token)
+    print("Logged in with Hugging Face token")
+else:
+    print("HUGGINGFACE_TOKEN not found in environment variables")
+    # Hugging Face Spaces bu değişkeni otomatik olarak yükleyecek
+    # eğer Spaces UI üzerinden secret olarak eklediyseniz
+
+# WebP formatını PNG'ye dönüştürme yardımcı fonksiyonu
+def convert_webp_to_png(input_data):
+    """WebP formatındaki bir görseli PNG formatına dönüştürür"""
+    try:
+        # Farklı input türlerini işle
+        img = None
+        
+        # URL ise
+        if isinstance(input_data, str) and (input_data.startswith('http://') or input_data.startswith('https://')):
+            response = requests.get(input_data)
+            img = Image.open(io.BytesIO(response.content))
+        
+        # Base64 kodlu ise
+        elif isinstance(input_data, str) and input_data.startswith('data:'):
+            format, imgstr = input_data.split(';base64,')
+            img = Image.open(io.BytesIO(base64.b64decode(imgstr)))
+        
+        # Bytecode ise
+        elif isinstance(input_data, bytes):
+            img = Image.open(io.BytesIO(input_data))
+        
+        # Dosya yolu ise
+        elif isinstance(input_data, str) and os.path.exists(input_data):
+            img = Image.open(input_data)
+        
+        # PIL Image ise
+        elif isinstance(input_data, Image.Image):
+            img = input_data
+            
+        # Görsel açılamadıysa
+        if img is None:
+            print(f"Couldn't process image data: {type(input_data)}")
+            return input_data
+            
+        # Geçici dosya oluştur
+        temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
+        temp_filename = temp_file.name
+        temp_file.close()
+        
+        # RGBA modundaysa RGB'ye dönüştür
+        if img.mode == 'RGBA':
+            img = img.convert('RGB')
+            
+        # PNG olarak kaydet
+        img.save(temp_filename, format="PNG")
+        print(f"Converted image saved to {temp_filename}")
+        
+        return temp_filename
+    except Exception as e:
+        print(f"Error converting image: {str(e)}")
+        return input_data
+
+def custom_handler(model_result):
+    """Model sonucunu işle ve PNG'ye dönüştür"""
+    try:
+        print(f"Processing model result: {type(model_result)}")
+        
+        # Liste sonucu (tipik API dönüşü)
+        if isinstance(model_result, list):
+            if len(model_result) > 0:
+                # İlk elemanı al
+                result_item = model_result[0]
+                return convert_webp_to_png(result_item)
+        
+        # Tek sonuç
+        return convert_webp_to_png(model_result)
+    except Exception as e:
+        print(f"Error in custom handler: {str(e)}")
+        return model_result
+
+def load_model():
+    try:
+        print("Setting up a custom interface...")
+        
+        # Doğrudan bir arayüz oluştur
+        def generate_3d_render(prompt):
+            try:
+                print(f"Processing prompt: {prompt}")
+                # Doğrudan Hugging Face Spaces API'sini çağır
+                import gradio.external as ext
+                result = ext.call_space(
+                    name="goofyai/3d_render_style_xl",
+                    fn_index=0,
+                    inputs=[prompt]
+                )
+                print(f"Got result from API: {type(result)}")
+                
+                # Sonucu işle ve PNG'ye dönüştür
+                processed_result = custom_handler(result)
+                return processed_result
+            except Exception as e:
+                print(f"Error in generation: {str(e)}")
+                return None
+        
+        # Arayüz oluştur
+        interface = gr.Interface(
+            fn=generate_3d_render,
+            inputs=gr.Textbox(label="Input", placeholder="Enter a prompt for 3D rendering"),
+            outputs=gr.Image(label="Output", type="filepath"),
+            title="3D Render Style XL",
+            description="Enter a prompt to generate a 3D render in game-icon style"
+        )
+        return interface
+    except Exception as e:
+        print(f"Error setting up interface: {str(e)}")
+        return None
+
+# Create the interface
+try:
+    interface = load_model()
+    if interface:
+        print("Interface set up successfully, launching...")
+        interface.launch(
+            share=False,
+            server_name="0.0.0.0",
+            server_port=7860,
+            show_error=True
+        )
+    else:
+        print("Failed to set up the interface")
+except Exception as e:
+    print(f"Error launching interface: {str(e)}")