Update app.py

app.py

@@ -1,5 +1,5 @@
 from diffusers import AutoPipelineForText2Image, StableDiffusionImg2ImgPipeline
-import torch.nn.functional as F
+from PIL import Image
 import gradio as gr
 import random
 import torch
@@ -18,18 +18,16 @@ css = """
 def generate(prompt, samp_steps, seed, progress=gr.Progress(track_tqdm=True)):
     if seed < 0:
         seed = random.randint(1,999999)
-    latent = txt2img(
+    image = txt2img(
         prompt,
         num_inference_steps=1,
         guidance_scale=0.0,
         generator=torch.manual_seed(seed),
-        output_type="latent"
     ).images[0]
-    latent = latent.unsqueeze(0)
-    upscaled_latent = F.interpolate(latent, scale_factor=2)
+    upscaled_image = image.resize((1024,1024), 1)
     final_image = img2img(
         prompt,
-        upscaled_latent,
+        upscaled_image,
         num_inference_steps=int(samp_steps*2),
         guidance_scale=5,
         strength=0.5,