Update app.py

app.py

@@ -36,7 +36,7 @@ summarizer = pipeline(
     "summarization", 
     model="sshleifer/distilbart-cnn-6-6"
 )
-@spaces.GPU
+
 def detect_objects(image):
     yolo_model.to('cuda')
     image_array = np.array(image)  # Μετατροπή PIL → NumPy
@@ -48,7 +48,7 @@ def detect_objects(image):
             label = yolo_model.names[class_id]
             detected_objects.append(label)
     return detected_objects
-@spaces.GPU
+
 def generate_story(detected_objects):
     story_prompt = f"Write a short story based on the following objects: {', '.join(detected_objects)}"
     response = client.chat.completions.create(
@@ -57,12 +57,12 @@ def generate_story(detected_objects):
         max_tokens=200
     )
     return response.choices[0].message.content.strip()
-@spaces.GPU
+
 def summarize_story(story):
     summary = summarizer(story, max_length=100, do_sample=False)[0]['summary_text']
     scenes = sent_tokenize(summary)
     return scenes
-@spaces.GPU
+
 def generate_images(story):
     scenes = summarize_story(story)
     images = []
@@ -90,7 +90,7 @@ def generate_images(story):
             continue
             
     return images
-@spaces.GPU
+
 def text_to_speech(story):
     tts = gTTS(text=story, lang="en", slow=False)
     audio_file_path = "story_audio.mp3"