RanM commited on
Commit
6449f8f
·
verified ·
1 Parent(s): 0e8d00a

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +6 -6
app.py CHANGED
@@ -11,19 +11,19 @@ model = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo")
11
 
12
  def generate_image(prompt):
13
  try:
14
- # Generate the image
15
  output = model(prompt=prompt, num_inference_steps=1, guidance_scale=0.0)
16
  print(f"Model output: {output}")
17
 
18
- # The model returns a PIL image
19
- if output:
20
- image = output[0] # Extract the PIL image from the output
21
  buffered = BytesIO()
22
  image.save(buffered, format="JPEG")
23
  image_bytes = buffered.getvalue()
24
  return image_bytes
25
  else:
26
- raise Exception("No image returned by the model.")
27
 
28
  except Exception as e:
29
  print(f"Error generating image: {e}")
@@ -37,7 +37,7 @@ def inference(sentence_mapping, character_dict, selected_style):
37
  # Generate prompts for each paragraph
38
  for paragraph_number, sentences in sentence_mapping.items():
39
  combined_sentence = " ".join(sentences)
40
- prompt= generate_prompt(combined_sentence, sentence_mapping, character_dict, selected_style)
41
  prompts.append((paragraph_number, prompt))
42
  print(f"Generated prompt for paragraph {paragraph_number}: {prompt}")
43
 
 
11
 
12
  def generate_image(prompt):
13
  try:
14
+ # Truncate prompt if necessary
15
  output = model(prompt=prompt, num_inference_steps=1, guidance_scale=0.0)
16
  print(f"Model output: {output}")
17
 
18
+ # Check if the model returned images
19
+ if isinstance(output.images, list) and len(output.images) > 0:
20
+ image = output.images[0]
21
  buffered = BytesIO()
22
  image.save(buffered, format="JPEG")
23
  image_bytes = buffered.getvalue()
24
  return image_bytes
25
  else:
26
+ raise Exception("No images returned by the model.")
27
 
28
  except Exception as e:
29
  print(f"Error generating image: {e}")
 
37
  # Generate prompts for each paragraph
38
  for paragraph_number, sentences in sentence_mapping.items():
39
  combined_sentence = " ".join(sentences)
40
+ prompt = generate_prompt(combined_sentence, sentence_mapping, character_dict, selected_style)
41
  prompts.append((paragraph_number, prompt))
42
  print(f"Generated prompt for paragraph {paragraph_number}: {prompt}")
43