Time in seconds

app.py

@@ -1,6 +1,7 @@
 from diffusers import StableDiffusionXLInpaintPipeline
 import gradio as gr
 import numpy as np
+import time
 import math
 import random
 import imageio
@@ -19,6 +20,7 @@ def noise_color(color, noise):
     return color + random.randint(- noise, noise)
 
 def predict(source_img, enlarge_top, enlarge_right, enlarge_bottom, enlarge_left, prompt, negative_prompt, denoising_steps, num_inference_steps, guidance_scale, randomize_seed, seed, debug_mode, progress=gr.Progress()):
+    start = time.time()
     progress(0, desc = "Preparing data...")
 
     if source_img is None:
@@ -115,9 +117,10 @@ def predict(source_img, enlarge_top, enlarge_right, enlarge_bottom, enlarge_left
         enlarged_image = None
         mask_image = None
 
+    end = time.time()
     return [
         output_image,
-        "Start again to get a different result. The new image is " + str(output_width) + " pixels large and " + str(output_height) + " pixels high, so an image of " + str(output_width * output_height) + " pixels." + limitation,
+        "Start again to get a different result. The new image is " + str(output_width) + " pixels large and " + str(output_height) + " pixels high, so an image of " + str(output_width * output_height) + " pixels. The image have been generated in " + str(end - start) + " seconds." + limitation,
         input_image,
         enlarged_image,
         mask_image
@@ -141,7 +144,7 @@ gr.Interface(fn = predict, inputs = [
     gr.Checkbox(label = "Debug mode", value = True, info = "Show intermediate results")
 ], outputs = [
     gr.Image(label = "Uncropped image"),
-    gr.Label(),
+    gr.Label(label = "Information"),
     gr.Image(label = "Original image"),
     gr.Image(label = "Enlarged image"),
     gr.Image(label = "Mask image")