Update app.py

app.py

@@ -20,14 +20,14 @@ models = preload_models_from_standard_weights(model_file, Device)
 @spaces.GPU(duration=242)
 def generate_image(mode, prompt, strength, seed, n_inference_steps, input_image=None):
     if mode == "Text-to-Image":
-        # If Text-to-Image, ignore the input image
+        # Ignore the input image
         output_image = generate(
             prompt=prompt,
-            uncond_prompt="",  ##negative prompt
+            uncond_prompt="",
             input_image=None,
-            strength=strength,  ##strength for skippin steps
-            do_cfg=True,  ##cassifier free guidance
-            cfg_scale=8, 
+            strength=strength,
+            do_cfg=True,
+            cfg_scale=8,
             sampler_name="ddpm",
             n_inference_steps=n_inference_steps,
             seed=seed,
@@ -36,8 +36,8 @@ def generate_image(mode, prompt, strength, seed, n_inference_steps, input_image=
             idle_device="cpu",
             tokenizer=tokenizer,
         )
-    elif mode == "Image-to-Image":
-        # If Image-to-Image, use the uploaded image
+    elif mode == "Image-to-Image" and input_image is not None:
+        # Use the uploaded image
         output_image = generate(
             prompt=prompt,
             uncond_prompt="",
@@ -53,9 +53,12 @@ def generate_image(mode, prompt, strength, seed, n_inference_steps, input_image=
             idle_device="cpu",
             tokenizer=tokenizer,
         )
+    else:
+        return "Please upload an image for Image-to-Image mode."
+    
     return Image.fromarray(output_image)
 
-# Gradio interface with additional inputs for mode selection and inference steps
+# Gradio interface with inputs for mode selection and inference steps
 iface = gr.Interface(
     fn=generate_image,
     inputs=[
@@ -64,7 +67,7 @@ iface = gr.Interface(
         gr.Slider(0, 1, step=0.01, label="Strength (For Image-2-Image)"),  # Slider for strength
         gr.Number(label="Seed"),  # Seed for reproducibility
         gr.Slider(1, 1000, step=1, label="Number of Inference Steps"),  # Slider for inference steps
-        gr.Image(label="Input Image (For Image-to-Image)", optional=True),  # Optional input image
+        gr.Image(label="Input Image (For Image-to-Image)"),  # Input image without optional flag
     ],
     outputs=gr.Image(label="Generated Image"),  # Output generated image
     title="Stable Diffusion Image Generator",
@@ -72,4 +75,4 @@ iface = gr.Interface(
 )
 
 # Launch the Gradio interface with public sharing enabled
-iface.launch(share=True, debug=True)
+iface.launch(share=True, debug=True)