Add advices

app.py

@@ -60,7 +60,10 @@ def check(
     ):
         raise gr.Error("At least one border must be enlarged.")
 
-def predict(
+def queue():
+    return []
+
+def uncrop(
     source_img,
     enlarge_top,
     enlarge_right,
@@ -76,6 +79,22 @@ def predict(
     seed,
     debug_mode,
     progress = gr.Progress()):
+    check(
+        source_img,
+        enlarge_top,
+        enlarge_right,
+        enlarge_bottom,
+        enlarge_left,
+        prompt,
+        negative_prompt,
+        smooth_border,
+        denoising_steps,
+        num_inference_steps,
+        guidance_scale,
+        randomize_seed,
+        seed,
+        debug_mode
+    )
     start = time.time()
     progress(0, desc = "Preparing data...")
 
@@ -208,10 +227,12 @@ with gr.Blocks() as interface:
         🚀 Powered by <i>SDXL 1.0</i> artificial intellingence
         <br/>
         <ul>
-        <li>If you need to change the <b>view angle</b> of your image, I recommend you to use <i>Zero123</i>,</li>
-        <li>If you need to <b>upscale</b> your image, I recommend you to use <i>Ilaria Upscaler</i>,</li>
-        <li>If you need to <b>slightly change</b> your image, I recommend you to use <i>Image-to-Image SDXL</i>,</li>
-        <li>If you need to change <b>one detail</b> on your image, I recommend you to use <i>Inpaint SDXL</i>.</li>
+        <li>To change the <b>view angle</b> of your image, I recommend to use <i>Zero123</i>,</li>
+        <li>To <b>upscale</b> your image, I recommend to use <i>Ilaria Upscaler</i>,</li>
+        <li>To <b>slightly change</b> your image, I recommend to use <i>Image-to-Image SDXL</i>,</li>
+        <li>To change <b>one detail</b> on your image, I recommend to use <i>Inpaint SDXL</i>,</li>
+        <li>To make a <b>tile</b> of your image, I recommend to use <i>Make My Image Tiling</i>,</li>
+        <li>To modify <b>anything else</b> on your image, I recommend to use <i>Instruct Pix2Pix</i>, available on terrapretapermaculture's <i>ControlNet-v1-1</i> space (last tab) or on <i>Dezgo</i> site.</li>
         </ul>
         <br/>
         🐌 Slow process... ~20 min with 20 inference steps, ~6 hours with 25 inference steps.<br>You can duplicate this space on a free account, it works on CPU.<br/>
@@ -267,8 +288,11 @@ with gr.Blocks() as interface:
     with gr.Row():
         mask_image = gr.Image(label = "Mask image", visible = False)
 
-    submit.click(toggle_debug, debug_mode, [original_image, enlarged_image, mask_image], queue = False,
-                     show_progress = False).then(check, inputs = [
+    submit.click(toggle_debug, debug_mode, [
+        original_image,
+        enlarged_image,
+        mask_image
+    ], queue = False, show_progress = False).then(check, inputs = [
         source_img,
         enlarge_top,
         enlarge_right,
@@ -284,7 +308,7 @@ with gr.Blocks() as interface:
         seed,
         debug_mode
     ], outputs = [], queue = False,
-                     show_progress = False).success(predict, inputs = [
+                     show_progress = False).success(fn = queue, inputs = [], outputs = [], queue = True, show_progress = False).then(uncrop, inputs = [
         source_img,
         enlarge_top,
         enlarge_right,