cheng commited on
Commit
2f73dc1
1 Parent(s): bf67113

update syntax connection

Browse files
Files changed (1) hide show
  1. clip_component.py +9 -5
clip_component.py CHANGED
@@ -6,7 +6,7 @@ import clip
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  similarity_threshold = 22.00
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  def get_token_from_clip(image):
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- text_inputs = ["apple", "banana", "lemon", "orange", "cereal", "salad", "chicken", "juice", "milk", "bread"]
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  text_tokens = clip.tokenize(text_inputs)
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  device = "cpu"
@@ -28,18 +28,22 @@ def get_token_from_clip(image):
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  similarity = text_features.cpu().numpy() @ image_feature.cpu().numpy().T
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  results = []
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- detect_food = ""
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  for i in range(similarity.shape[0]):
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  similarity_num = (100.0 * similarity[i][0])
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  text_input = text_inputs[i]
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  results.append({"text_input": text_input, "similarity": similarity_num})
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- if similarity_num >= similarity_threshold:
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- detect_food += " " + text_input + " ."
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  # print(similarity_num)
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- detect_food_list = detect_food[1:]
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  results.sort(key=lambda x: x["similarity"], reverse=True)
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  # Print the caption for each text input along with their similarity scores
 
 
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  for result in results:
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  print(f"Text input: {result['text_input']}, Similarity: {result['similarity']:.2f}")
 
 
 
 
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  return detect_food_list
 
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  similarity_threshold = 22.00
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  def get_token_from_clip(image):
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+ text_inputs = ["apple", "banana", "cereal", "milk", "lemon", "orange", "salad", "juice", "chicken", "bread"]
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  text_tokens = clip.tokenize(text_inputs)
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  device = "cpu"
 
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  similarity = text_features.cpu().numpy() @ image_feature.cpu().numpy().T
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  results = []
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+
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  for i in range(similarity.shape[0]):
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  similarity_num = (100.0 * similarity[i][0])
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  text_input = text_inputs[i]
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  results.append({"text_input": text_input, "similarity": similarity_num})
 
 
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  # print(similarity_num)
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+
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  results.sort(key=lambda x: x["similarity"], reverse=True)
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  # Print the caption for each text input along with their similarity scores
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+
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+ detect_food = ""
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  for result in results:
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  print(f"Text input: {result['text_input']}, Similarity: {result['similarity']:.2f}")
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+ if result['similarity'] >= similarity_threshold:
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+ detect_food += " " + text_input + " ."
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+
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+ detect_food_list = detect_food[1:]
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  return detect_food_list