Update app.py

app.py

@@ -378,7 +378,7 @@ class GuiSD:
         face_restoration_visibility,
         face_restoration_weight,
     ):
-        info_state = html_template_message("Navigating latent space...")
+        info_state = html_template_message("Processing...")
         yield info_state, gr.update(), gr.update()
 
         vae_model = vae_model if vae_model != "None" else None
@@ -562,42 +562,40 @@ class GuiSD:
 
         actual_progress = 0
         info_images = gr.update()
-        for img, [seed, image_path, metadata] in self.model(**pipe_params):
-            info_state = progress_step_bar(actual_progress, steps)
-            actual_progress += concurrency
-            if image_path:
-                info_images = f"Seeds: {str(seed)}"
-                if vae_msg:
-                    info_images = info_images + "<br>" + vae_msg
-
-                if "Cannot copy out of meta tensor; no data!" in self.model.last_lora_error:
-                    msg_ram = "Unable to process the LoRAs due to high RAM usage; please try again later."
-                    print(msg_ram)
-                    msg_lora += f"<br>{msg_ram}"
-
-                for status, lora in zip(self.model.lora_status, self.model.lora_memory):
-                    if status:
-                        msg_lora += f"<br>Loaded: {lora}"
-                    elif status is not None:
-                        msg_lora += f"<br>Error with: {lora}"
-
-                if msg_lora:
-                    info_images += msg_lora
-
-                info_images = info_images + "<br>" + "GENERATION DATA:<br>" + escape_html(metadata[-1]) + "<br>-------<br>"
-
-                download_links = "<br>".join(
-                    [
-                        f'<a href="{path.replace("/images/", "/file=/home/user/app/images/")}" download="{os.path.basename(path)}">Download Image {i + 1}</a>'
-                        for i, path in enumerate(image_path)
-                    ]
-                )
-                if save_generated_images:
-                    info_images += f"<br>{download_links}"
+        img, [seed, image_path, metadata] = self.model(**pipe_params)
+
+        info_images = f"Seeds: {str(seed)}"
+        if vae_msg:
+            info_images = info_images + "<br>" + vae_msg
+
+        if "Cannot copy out of meta tensor; no data!" in self.model.last_lora_error:
+            msg_ram = "Unable to process the LoRAs due to high RAM usage; please try again later."
+            print(msg_ram)
+            msg_lora += f"<br>{msg_ram}"
+
+        for status, lora in zip(self.model.lora_status, self.model.lora_memory):
+            if status:
+                msg_lora += f"<br>Loaded: {lora}"
+            elif status is not None:
+                msg_lora += f"<br>Error with: {lora}"
+
+        if msg_lora:
+            info_images += msg_lora
+
+        info_images = info_images + "<br>" + "GENERATION DATA:<br>" + escape_html(metadata[-1]) + "<br>-------<br>"
+
+        download_links = "<br>".join(
+            [
+                f'<a href="{path.replace("/images/", "/file=/home/user/app/images/")}" download="{os.path.basename(path)}">Download Image {i + 1}</a>'
+                for i, path in enumerate(image_path)
+            ]
+        )
+        if save_generated_images:
+            info_images += f"<br>{download_links}"
 
-                info_state = "COMPLETE"
+        info_state = "COMPLETE"
 
-            yield info_state, img, info_images
+        return info_state, img, info_images
 
 
 def dynamic_gpu_duration(func, duration, *args):