Update app.py

app.py

@@ -1,7 +1,31 @@
 import gradio as gr
+from diffusers import DiffusionPipeline
+import torch
+import numpy as np
+import PIL
+from google.colab.patches import cv2_imshow
+import cv2
+
+pipeline = DiffusionPipeline.from_pretrained("fusing/latent-diffusion-text2im-large")
+generator = torch.manual_seed(42)
 
 def greet(name):
     return "Hello " + name + "!!"
+    
+def genimage(prompt, iterations):
+  image = pipeline([prompt], generator=generator, eta=0.3, guidance_scale=6.0, num_inference_steps=iterations)
+
+  image_processed = image.cpu().permute(0, 2, 3, 1)
+  image_processed = image_processed  * 255.
+  image_processed = image_processed.numpy().astype(np.uint8)
+  image_pil = PIL.Image.fromarray(image_processed[0])
+
+  # save image
+  file_name = "test.png"
+  image_pil.save(file_name)
+  img = cv2.imread(file_name)
+  #cv2_imshow(img)
+  return img
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+iface = gr.Interface(fn=genimage, inputs=["text", "number"], outputs="image")
 iface.launch()