Update app.py

app.py

@@ -225,7 +225,7 @@ def infer(
     upload_to_ftp(sd35_path)
     
         # Convert the generated image to a tensor
-    generated_image_tensor = torch.tensor([np.array(sd_image).transpose(2, 0, 1)]).to('cuda') / 255.0
+    #generated_image_tensor = torch.tensor([np.array(sd_image).transpose(2, 0, 1)]).to('cuda') / 255.0
     # Encode the generated image into latents
     #with torch.no_grad():
     #    generated_latents = pipe.vae.encode(generated_image_tensor.to(torch.bfloat16)).latent_dist.sample().mul_(0.18215)