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Update app.py
Browse files
app.py
CHANGED
@@ -86,7 +86,6 @@ def parse_descriptions(text):
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seed_words = []
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used_words = set()
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paused = False
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# Queue to store parsed descriptions
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parsed_descriptions_queue = deque()
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@@ -97,7 +96,6 @@ MAX_IMAGES = 12
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@spaces.GPU
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def generate_descriptions(user_prompt, seed_words_input, batch_size=100, max_iterations=50):
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global paused
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descriptions = []
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description_queue = deque()
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iteration_count = 0
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@@ -114,9 +112,6 @@ def generate_descriptions(user_prompt, seed_words_input, batch_size=100, max_ite
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seed_words.extend(re.findall(r'"(.*?)"', seed_words_input))
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while iteration_count < max_iterations and len(parsed_descriptions_queue) < MAX_DESCRIPTIONS:
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if paused:
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break
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# Select a subject that has not been used
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available_subjects = [word for word in seed_words if word not in used_words]
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if not available_subjects:
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@@ -169,7 +164,8 @@ def combined_function(user_prompt, seed_words_input):
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return images
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if __name__ == '__main__':
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interface = gr.Interface(
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fn=combined_function,
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seed_words = []
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used_words = set()
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# Queue to store parsed descriptions
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parsed_descriptions_queue = deque()
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@spaces.GPU
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def generate_descriptions(user_prompt, seed_words_input, batch_size=100, max_iterations=50):
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descriptions = []
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description_queue = deque()
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iteration_count = 0
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seed_words.extend(re.findall(r'"(.*?)"', seed_words_input))
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while iteration_count < max_iterations and len(parsed_descriptions_queue) < MAX_DESCRIPTIONS:
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# Select a subject that has not been used
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available_subjects = [word for word in seed_words if word not in used_words]
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if not available_subjects:
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return images
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if __name__ == '__main__':
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# Ensure CUDA is initialized correctly
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torch.cuda.init()
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interface = gr.Interface(
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fn=combined_function,
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