Update app.py

app.py

@@ -32,8 +32,16 @@ async def generate_image(prompt, model, lora_word, width, height, scales, steps,
         print(f"Error generating image: {e}")
         return None, None
 
+def get_upscale_finegrain(prompt, img_path, upscale_factor):
+    try:
+        client = Client("finegrain/finegrain-image-enhancer", hf_token=HF_TOKEN_UPSCALER)
+        result = client.predict(input_image=handle_file(img_path), prompt=prompt, negative_prompt="", seed=42, upscale_factor=upscale_factor, controlnet_scale=0.6, controlnet_decay=1, condition_scale=6, tile_width=112, tile_height=144, denoise_strength=0.35, num_inference_steps=18, solver="DDIM", api_name="/process")
+        return result[1]
+    except Exception as e:
+        print(f"Error upscale image: {e}")
+        return None
+
 async def gen(prompt, basemodel, width, height, scales, steps, seed, upscale_factor, process_upscale, lora_model, process_lora):
-    """Genera una imagen y la ajusta"""
     model = enable_lora(lora_model, basemodel) if process_lora else basemodel
     image, seed = await generate_image(prompt, model, "", width, height, scales, steps, seed)
     if image is None:
@@ -44,20 +52,11 @@ async def gen(prompt, basemodel, width, height, scales, steps, seed, upscale_fac
     
     if process_upscale:
         upscale_image = get_upscale_finegrain(prompt, image_path, upscale_factor)
+        upscale_image_path = "upscale_image.jpg"
+        upscale_image.save(upscale_image_path, format="JPEG")
+        return [image_path, upscale_image_path]
     else:
-        upscale_image = image_path
-    
-    return [image_path, upscale_image]
-
-def get_upscale_finegrain(prompt, img_path, upscale_factor):
-    """Ajusta la imagen"""
-    try:
-        client = Client("finegrain/finegrain-image-enhancer", hf_token=HF_TOKEN_UPSCALER)
-        result = client.predict(input_image=handle_file(img_path), prompt=prompt, negative_prompt="", seed=42, upscale_factor=upscale_factor, controlnet_scale=0.6, controlnet_decay=1, condition_scale=6, tile_width=112, tile_height=144, denoise_strength=0.35, num_inference_steps=18, solver="DDIM", api_name="/process")
-        return result[1]
-    except Exception as e:
-        print(f"Error upscale image: {e}")
-        return None
+        return [image_path, image_path]
 
 css = """
 #col-container{ margin: 0 auto; max-width: 1024px;}