Update app.py

app.py

@@ -34,11 +34,34 @@ pipe.to("cuda")
 
 #pipe.enable_model_cpu_offload()
 
+from PIL import Image
+
+def resize_image(input_path, output_path, target_height):
+    # Open the input image
+    img = Image.open(input_path)
+
+    # Calculate the aspect ratio of the original image
+    original_width, original_height = img.size
+    original_aspect_ratio = original_width / original_height
+
+    # Calculate the new width while maintaining the aspect ratio and the target height
+    new_width = int(target_height * original_aspect_ratio)
+
+    # Resize the image while maintaining the aspect ratio and fixing the height
+    img = img.resize((new_width, target_height), Image.LANCZOS)
+
+    # Save the resized image
+    img.save(output_path)
+
+    return output_path
+
 def infer(use_custom_model, model_name, custom_lora_weight, image_in, prompt, negative_prompt, preprocessor, controlnet_conditioning_scale, guidance_scale, inf_steps, seed, progress=gr.Progress(track_tqdm=True)):
     prompt = prompt
     negative_prompt = negative_prompt
     generator = torch.Generator(device="cuda").manual_seed(seed)
     
+    image_in = resize_image(image_in, "resized_input.jpg", 1024)
+    
     if preprocessor == "canny":
 
         image = load_image(image_in)