Update app.py

app.py

@@ -9,6 +9,7 @@ import re
 from PIL import Image
 from gradio_client import Client, handle_file
 from huggingface_hub import login
+from gradio_imageslider import ImageSlider
 
 MAX_SEED = np.iinfo(np.int32).max
 
@@ -45,7 +46,7 @@ def gen(prompt, basemodel, width, height, scales, steps, seed, upscale_factor, p
 
     image, seed = generate_image(prompt, model, "", width, height, scales, steps, seed)
     if image is None:
-        return [None]
+        return [None, None]
     
     image_path = "temp_image.jpg"
     image.save(image_path, format="JPEG")
@@ -55,13 +56,12 @@ def gen(prompt, basemodel, width, height, scales, steps, seed, upscale_factor, p
         if upscale_image_path is not None:
             upscale_image = Image.open(upscale_image_path)
             upscale_image.save("upscale_image.jpg", format="JPEG")
-            return [upscale_image]
+            return [image_path, "upscale_image.jpg"]
         else:
             print("Error: The scaled image path is None")
-            return [image]
+            return [image_path, image_path]
     else:
-        return [image]
-
+        return [image_path, image_path]
 
 css = """
 #col-container{ margin: 0 auto; max-width: 1024px;}
@@ -71,7 +71,7 @@ with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
         with gr.Row():
             with gr.Column(scale=3):
-                output_res = gr.Image(label="Generated Image")  # Using gr.Image instead of ImageSlider
+                output_res = ImageSlider(label="Flux / Upscaled")
             with gr.Column(scale=2):
                 prompt = gr.Textbox(label="Image Description")
                 basemodel_choice = gr.Dropdown(label="Model", choices=["black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-DEV", "enhanceaiteam/Flux-uncensored", "Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro", "Shakker-Labs/FLUX.1-dev-LoRA-add-details", "city96/FLUX.1-dev-gguf"], value="black-forest-labs/FLUX.1-schnell")
@@ -89,5 +89,4 @@ with gr.Blocks(css=css) as demo:
     
                 btn = gr.Button("Generate")
                 btn.click(fn=gen, inputs=[prompt, basemodel_choice, width, height, scales, steps, seed, upscale_factor, process_upscale, lora_model_choice, process_lora], outputs=output_res,)
-
-    demo.launch()
+    demo.launch()