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import openai
class ImageToText:
def __init__(self, api_key, gpt_version="gpt-3.5-turbo"):
self.template = self.initialize_template()
openai.api_key = api_key
self.gpt_version = gpt_version
def initialize_template(self):
prompt_prefix_1 = """Generate only an informative and nature paragraph based on the given information(a,b,c,d):\n"""
prompt_prefix_2 = """\n a. Image Resolution: """
prompt_prefix_3 = """\n b. Image Caption: """
prompt_prefix_4 = """\n c. Dense Caption: """
prompt_prefix_5 = """\n d. Region Semantic: """
prompt_suffix = """\n There are some rules:
Show object, color and position.
Use nouns rather than coordinates to show position information of each object.
No more than 7 sentences.
Only use one paragraph.
Describe position detailedly.
Do not appear number.
"""
template = f"{prompt_prefix_1}{prompt_prefix_2}{{width}}X{{height}}{prompt_prefix_3}{{caption}}{prompt_prefix_4}{{dense_caption}}{prompt_prefix_5}{{region_semantic}}{prompt_suffix}"
return template
def paragraph_summary_with_gpt(self, caption, dense_caption, region_semantic, width, height):
question = self.template.format(width=width, height=height, caption=caption, dense_caption=dense_caption, region_semantic=region_semantic)
print('\033[1;35m' + '*' * 100 + '\033[0m')
print('\nStep4, Paragraph Summary with GPT-3:')
print('\033[1;34m' + "Question:".ljust(10) + '\033[1;36m' + question + '\033[0m')
completion = openai.ChatCompletion.create(
model=self.gpt_version,
messages = [
{"role": "user", "content" : question}]
)
print('\033[1;34m' + "ChatGPT Response:".ljust(18) + '\033[1;32m' + completion['choices'][0]['message']['content'] + '\033[0m')
print('\033[1;35m' + '*' * 100 + '\033[0m')
return completion['choices'][0]['message']['content']
def paragraph_summary_with_gpt_debug(self, caption, dense_caption, width, height):
question = self.template.format(width=width, height=height, caption=caption, dense_caption=dense_caption)
print("paragraph_summary_with_gpt_debug:")
return question
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