Update app.py

app.py

@@ -23,10 +23,11 @@ def ask(input_im, scale, steps, seed, images):
             images.append(image)
     return images
 
-def main(input_im, scale, steps, seed):
+def main(input_im, n_pairs, scale, steps, seed):
     
     images = []
-    for i in range(2):
+    for i in range(n_pairs):
+        print('Asking for a new pair of image [' + str(i) + '/' + str(n_pairs) + ']')
         images = ask(input_im, scale, steps, seed, images)
     #images = ask(input_im, scale, steps, seed, images)
     #images = ask(input_im, scale, steps, seed, images)
@@ -42,6 +43,7 @@ pipe = pipe.to(device)
 
 inputs = [
     gr.Image(),
+    gr.Slider(0, 3, value=2, step=1, label="Pairs of images to ask"),
     gr.Slider(0, 25, value=3, step=1, label="Guidance scale"),
     gr.Slider(5, 50, value=25, step=5, label="Steps"),
     gr.Slider(label = "Seed", minimum = 0, maximum = 2147483647, step = 1, randomize = True)
@@ -51,12 +53,14 @@ output.style(grid=2, height="")
 
 description = \
 """
-<p style='text-align: center;'>This demo is running on CPU. Working version fixed by Sylvain <a href='https://twitter.com/fffiloni' target='_blank'>@fffiloni</a>. You'll get 4 images variations. NSFW filters enabled. <img id='visitor-badge' alt='visitor badge' src='https://visitor-badge.glitch.me/badge?page_id=gradio-blocks.sd-img-variations' style='display: inline-block' /><br />
+<p style='text-align: center;'>This demo is running on CPU. Working version fixed by Sylvain <a href='https://twitter.com/fffiloni' target='_blank'>@fffiloni</a>. You'll get n pairs of images variations. <br /> 
+Asking for pairs of images instead of more than 2 images in a row helps us to avoid heavy CPU load and connection error out ;)<br />
+Waiting time (for 2 pairs): ~5/10 minutes • NSFW filters enabled • <img id='visitor-badge' alt='visitor badge' src='https://visitor-badge.glitch.me/badge?page_id=gradio-blocks.sd-img-variations' style='display: inline-block' /><br />
 Generate variations on an input image using a fine-tuned version of Stable Diffusion.<br />
 Trained by <a href='https://www.justinpinkney.com' target='_blank'>Justin Pinkney</a> (<a href='https://twitter.com/Buntworthy' target='_blank'>@Buntworthy</a>) at <a href='https://lambdalabs.com/' target='_blank'>Lambda</a><br />
 This version has been ported to 🤗 Diffusers library, see more details on how to use this version in the <a href='https://github.com/LambdaLabsML/lambda-diffusers' target='_blank'>Lambda Diffusers repo</a>.<br />
 For the original training code see <a href='https://github.com/justinpinkney/stable-diffusion' target='_blank'>this repo</a>.
-<img src='https://raw.githubusercontent.com/justinpinkney/stable-diffusion/main/assets/im-vars-thin.jpg' />
+<img src='https://raw.githubusercontent.com/justinpinkney/stable-diffusion/main/assets/im-vars-thin.jpg' style='display: inline-block;' />
 </p>
 """