Update app.py

app.py

@@ -7,7 +7,6 @@ from time import time, ctime
 from PIL import Image, ImageColor
 from diffusers import DDPMPipeline
 from diffusers import DDIMScheduler
-from tqdm import tqdm
 
 device = (
     "mps"
@@ -44,10 +43,11 @@ def generate():
     return show_images_save(x)
 
 def generate_g(color, guidance_loss_scale):
+    print('--V2--')
     target_color = ImageColor.getcolor(color, "RGBA")  # Target color as RGB
     target_color = [a / 255 for a in target_color]  # Rescale from (0, 255) to (0, 1)
     x = torch.randn(8, 4, 64, 64).to(device)
-    for i, t in tqdm(enumerate(scheduler.timesteps)):
+    for i, t in enumerate(scheduler.timesteps):
         model_input = scheduler.scale_model_input(x, t)
         with torch.no_grad():
             noise_pred = image_pipe.unet(model_input, t)["sample"]