Update app.py

app.py

@@ -8,7 +8,7 @@ from tqdm import tqdm, trange
 from PIL import Image
 
 
-def random_clip(x, min=-1.5, max=1.5):
+def random_clip(x, min=-1.3, max=1.3):
     if isinstance(x, np.ndarray):
         return np.clip(x, min, max)
     elif isinstance(x, torch.Tensor):
@@ -221,12 +221,14 @@ class DDIMSampler(Sampler):
                                    axis=0)
         else:
             # 均匀取子集
+            # print(noise_steps, 1, step)
             steps = np.linspace(noise_steps, 1, step)
+            # print("steps", len(steps))
+
         steps = np.floor(steps)
-        steps = np.concatenate((steps, steps[-1:]), axis=0)
+        # steps = np.concatenate((steps, steps[-1:]), axis=0)
 
         x_t = torch.tile(noised_latents, (batch_size, 1, 1, 1)).to(self.device)  # 32, 32
-        print("sample", steps)
         for i in trange(len(steps) - 1):
             x_t = self.sample(model, x_t, steps[i], steps[i + 1], eta)
 
@@ -499,8 +501,15 @@ def init_webui(unet, vae, normal_t):
                                                  batch_size,
                                                  step_value,
                                                  eta=1.)
+        # print(step_value)
+        ss = 0
         for i in progress.tqdm(range(1, step_value + 1)):
-            output = next(looper)
+            try:
+                output = next(looper)
+                ss += 1
+            except StopIteration:
+                # print("StopIteration", ss)
+                break
 
         output = sampler.decode_img(vae, output)
         output = np.clip(output, 0, 255)
@@ -534,11 +543,11 @@ def init_webui(unet, vae, normal_t):
             # 创建输出组件
             output_images_u = gr.Gallery(show_label=False, height=400, columns=5)
             gr.Examples(
-                examples=[[40, 2, "DDIM", 256, 255395]],
+                examples=[[60, 4, "DDIM", 256, 255392]],  # 255392
                 inputs=[step_u, batch_size_u, sampler_name_u, img_size_u, ramdom_seed_u],
                 outputs=output_images_u,
                 fn=process_image_u,
-                cache_examples=False,
+                cache_examples=True,
             )
         with gr.Tab(label="image to image"):
             with gr.Column():
@@ -566,7 +575,7 @@ def init_webui(unet, vae, normal_t):
                 inputs=[input_image, noise_step, step, batch_size, sampler_name, img_size, ramdom_seed],
                 outputs=output_images,
                 fn=process_image,
-                cache_examples=False,
+                cache_examples=True,
             )
 
         start_button.click(process_image,