ManishThota commited on
Commit
69344b8
1 Parent(s): 2c37e20

Update app.py

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Files changed (1) hide show
  1. app.py +17 -3
app.py CHANGED
@@ -5,6 +5,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
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  import cv2
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  import numpy as np
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  import ast
 
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  # # Ensure GPU usage if available
@@ -98,10 +99,23 @@ def predict_answer(video, image, question):
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  answer = tokenizer.decode(output_ids[input_ids.shape[1]:], skip_special_tokens=True).strip()
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  answers.append(answer)
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- return ast.literal_eval(answers[0])
 
 
 
 
 
 
 
 
 
 
 
 
 
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- else:
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- return "Unsupported file type. Please upload an image or video."
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  promt_cat_dog = """
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  Annotate this image with this schema:
 
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  import cv2
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  import numpy as np
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  import ast
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+ from collections import Counter
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  # # Ensure GPU usage if available
 
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  answer = tokenizer.decode(output_ids[input_ids.shape[1]:], skip_special_tokens=True).strip()
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  answers.append(answer)
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+
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+ # Modify this logic based on your specific needs
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+ most_common_answer = Counter(answers).most_common(1)[0][0]
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+
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+ # Safely evaluate the most common answer assuming it's a string representation of a Python literal
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+ try:
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+ evaluated_answer = ast.literal_eval(most_common_answer)
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+ except (ValueError, SyntaxError):
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+ # Handle malformed answer string
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+ evaluated_answer = f"Error evaluating answer: {most_common_answer}"
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+
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+ return evaluated_answer
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+
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+ # return ast.literal_eval(answers[0])
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+ # else:
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+ # return "Unsupported file type. Please upload an image or video."
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  promt_cat_dog = """
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  Annotate this image with this schema: