Update app.py

app.py

@@ -133,7 +133,12 @@ def model_fn(x_t, ts, **kwargs):
     eps = th.cat([half_eps, half_eps], dim=0)
     return th.cat([eps, rest], dim=1)
 
-
+def to_base64(pil_image, size=(64, 64)):
+    pil_image.thumbnail(size, Image.ANTIALIAS)
+    buffered = BytesIO()
+    pil_image.save(buffered, format="JPEG")
+    return base64.b64encode(buffered.getvalue())
+    
 # @app.get("/")
 def read_root():
     return {"glide!"}
@@ -232,15 +237,11 @@ def sample(prompt):
     # Show the output
     image = get_images(up_samples)
     image = to_base64(image)
-    return {"image": image}
+    #return {"image": image}
     return image
 
 
-def to_base64(pil_image, size=(64, 64)):
-    pil_image.thumbnail(size, Image.ANTIALIAS)
-    buffered = BytesIO()
-    pil_image.save(buffered, format="JPEG")
-    return base64.b64encode(buffered.getvalue())
+
 
 title = "Interactive demo: glide-text2im dermoscopic image generator"
 description = "Demo for the Finetuned version of OpenAI's GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. Please be aware that generation of the image will take up to 20 minutes, as CPU is used for the generation. Please cite our research paper with the title -Finetuning of GLIDE stable diffusion model for AI-based text-conditional image synthesis of dermoscopic images-"