Update app.py

app.py

@@ -32,7 +32,7 @@ parsed_descriptions_queue = deque()
 
 # Usage limits
 MAX_DESCRIPTIONS = 30
-MAX_IMAGES = 3
+MAX_IMAGES = 1  # Generate only 1 image
 
 def initialize_diffusers():
     from optimum.quanto import freeze, qfloat8, quantize
@@ -88,7 +88,7 @@ def parse_descriptions(text):
     return descriptions
 
 @spaces.GPU
-def generate_descriptions(user_prompt, seed_words_input, batch_size=100, max_iterations=2):
+def generate_descriptions(user_prompt, seed_words_input, batch_size=100, max_iterations=1):  # Set max_iterations to 1
     descriptions = []
     description_queue = deque()
     iteration_count = 0
@@ -128,8 +128,8 @@ def generate_descriptions(user_prompt, seed_words_input, batch_size=100, max_ite
 
     return list(parsed_descriptions_queue)
 
-@spaces.GPU(duration=120)
-def generate_images(parsed_descriptions, max_iterations=3):
+@spaces.GPU
+def generate_images(parsed_descriptions, max_iterations=2):  # Set max_iterations to 1
     pipe = initialize_diffusers()
 
     if len(parsed_descriptions) < MAX_IMAGES:
@@ -139,7 +139,7 @@ def generate_images(parsed_descriptions, max_iterations=3):
 
     images = []
     for prompt in prompts:
-        images.extend(pipe(prompt, num_images=1, num_inference_steps=max_iterations, height=1024, width=1024).images)  # Define the resolution here
+        images.extend(pipe(prompt, num_images=1, num_inference_steps=max_iterations, height=512, width=512).images)  # Set resolution to 512 x 512
 
     return images
 
@@ -161,4 +161,4 @@ if __name__ == '__main__':
         allow_flagging='never'  # Disable flagging
     )
 
-    interface.launch(share=True)
+    interface.launch(share=True)