Update app.py

app.py

@@ -10,6 +10,11 @@ from inversion_utils import *
 from torch import autocast, inference_mode
 import re
 
+def randomize_seed_fn(seed, randomize_seed):
+    if randomize_seed:
+        seed = random.randint(0, np.iinfo(np.int32).max)
+    torch.manual_seed(seed)
+    return seed
 
 def invert(x0, prompt_src="", num_diffusion_steps=100, cfg_scale_src = 3.5, eta = 1):
 
@@ -151,25 +156,20 @@ with gr.Blocks(css='style.css') as demo:
             seed = 0,
             randomized_seed = True):
 
-        if randomized_seed:
-            seed = random.randint(0, np.iinfo(np.int32).max)
+        # if randomized_seed:
+        #     seed = random.randint(0, np.iinfo(np.int32).max)
             
-        torch.manual_seed(seed)
-         # offsets=(0,0,0,0)
+        # torch.manual_seed(seed)
+        #  # offsets=(0,0,0,0)
         x0 = load_512(input_image, device=device)
     
-        if do_inversion:
-            # invert and retrieve noise maps and latent
+        if do_inversion or randomized_seed:
             zs_tensor, wts_tensor = invert(x0 =x0 , prompt_src=src_prompt, num_diffusion_steps=steps, cfg_scale_src=cfg_scale_src)
-            # xt = gr.State(value=wts[skip])
-            # zs = gr.State(value=zs[skip:])
             wts = gr.State(value=wts_tensor)
             zs = gr.State(value=zs_tensor)
             do_inversion = False
         
-        # output = sample(zs.value, xt.value, prompt_tar=tar_prompt, cfg_scale_tar=cfg_scale_tar)
-        output = sample(zs.value, wts.value, prompt_tar=tar_prompt, skip=skip, cfg_scale_tar=cfg_scale_tar)
-    
+        output = sample(zs.value, wts.value, prompt_tar=tar_prompt, skip=skip, cfg_scale_tar=cfg_scale_tar)    
         return output, wts, zs, do_inversion
     
     gr.HTML(intro)
@@ -204,10 +204,13 @@ with gr.Blocks(css='style.css') as demo:
                 skip = gr.Slider(minimum=0, maximum=40, value=36, step = 1, label="Skip Steps", interactive=True)
                 cfg_scale_tar = gr.Slider(minimum=7, maximum=18,value=15, label=f"Target Guidance Scale", interactive=True)
                 seed = gr.Number(value=0, precision=0, label="Seed", interactive=True)
-                randomize_seed = gr.Checkbox(label='Randomize seed', value=True)
+                randomize_seed = gr.Checkbox(label='Randomize seed', value=False)
             
 
     edit_button.click(
+        fn = randomize_seed_fn,
+        inputs = [seed, randomize_seed],
+        outputs = [seed]).then(
         fn=edit,
         inputs=[input_image,
                 do_inversion, wts, zs, 
@@ -217,8 +220,7 @@ with gr.Blocks(css='style.css') as demo:
             cfg_scale_src,
             cfg_scale_tar,
             skip,
-            seed,
-            randomize_seed
+            seed,randomized_seed
         ],
         outputs=[output_image, wts, zs, do_inversion],
     )