Update app.py

app.py

@@ -454,15 +454,31 @@ def generate_image(prompt_mash, steps, seed, cfg_scale, width, height, progress)
             output_type="pil",
             good_vae=good_vae,
         ):
-            # Debugging: Check image type before yielding
-            print(f"Debug: Yielding image of type {type(img)}")  # Debugging
-            if not isinstance(img, (PIL.Image.Image, torch.Tensor)):  # Check if it's an image
-                print(f"Error: Expected an image, but got {type(img)}")
-                raise ValueError("Expected an image, but got a non-image value.")
+            print(f"Debug: Yielding image of type {type(img)}")  # Debugging: Check image type
+            if isinstance(img, float):
+                print("Error: A float was returned instead of an image.")  # Log if img is a float
+                raise ValueError("Expected an image, but got a float.")  # Raise error if a float is found
             yield img
             final_image = img  # Update final_image with the current image
         return final_image
-
+        
+def generate_image_to_image(prompt_mash, image_input_path, image_strength, steps, cfg_scale, width, height, seed):
+    pipe_i2i.to("cuda")
+    generator = torch.Generator(device="cuda").manual_seed(seed)
+    image_input = load_image(image_input_path)
+    final_image = pipe_i2i(
+        prompt=prompt_mash,
+        image=image_input,
+        strength=image_strength,
+        num_inference_steps=steps,
+        guidance_scale=cfg_scale,
+        width=width,
+        height=height,
+        generator=generator,
+        joint_attention_kwargs={"scale": 1.0},
+        output_type="pil",
+    ).images[0]
+    return final_image
 
 @spaces.GPU(duration=75)
 def run_lora(prompt, cfg_scale, steps, selected_info_1, selected_info_2, selected_info_3, selected_info_4, selected_indices, lora_scale_1, lora_scale_2, lora_scale_3, lora_scale_4, randomize_seed, seed, width, height, loras_state, image_input=None, progress=gr.Progress(track_tqdm=True)):