user-agent commited on
Commit
276e058
1 Parent(s): 3a0fa78

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +30 -4
app.py CHANGED
@@ -77,31 +77,57 @@ def shot(input, category, level):
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  @spaces.GPU
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  def get_colour(image_urls, category):
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  colourLabels = list(COLOURS_DICT.keys())
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  for i in range(len(colourLabels)):
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  colourLabels[i] = colourLabels[i] + " clothing: " + category
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  responses = pipe(image_urls, candidate_labels=colourLabels)
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- # Get the most common colour
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  mainColour = responses[0][0]['label'].split(" clothing:")[0]
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-
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  if mainColour not in COLOURS_DICT:
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  return None, None, None
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- # Add category to the end of each label
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  labels = COLOURS_DICT[mainColour]
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  for i in range(len(labels)):
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  labels[i] = labels[i] + " clothing: " + category
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- # Run pipeline in one go
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  responses = pipe(image_urls, candidate_labels=labels)
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  subColour = responses[0][0]['label'].split(" clothing:")[0]
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  return subColour, mainColour, responses[0][0]['score']
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  @spaces.GPU
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  def get_predicted_attributes(image_urls, category):
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  # Assuming ATTRIBUTES_DICT and pipe are defined outside this function
 
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+ # @spaces.GPU
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+ # def get_colour(image_urls, category):
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+ # colourLabels = list(COLOURS_DICT.keys())
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+ # for i in range(len(colourLabels)):
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+ # colourLabels[i] = colourLabels[i] + " clothing: " + category
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+
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+ # responses = pipe(image_urls, candidate_labels=colourLabels)
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+ # # Get the most common colour
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+ # mainColour = responses[0][0]['label'].split(" clothing:")[0]
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+
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+
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+ # if mainColour not in COLOURS_DICT:
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+ # return None, None, None
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+
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+ # # Add category to the end of each label
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+ # labels = COLOURS_DICT[mainColour]
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+ # for i in range(len(labels)):
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+ # labels[i] = labels[i] + " clothing: " + category
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+
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+ # # Run pipeline in one go
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+ # responses = pipe(image_urls, candidate_labels=labels)
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+ # subColour = responses[0][0]['label'].split(" clothing:")[0]
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+
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+ # return subColour, mainColour, responses[0][0]['score']
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  @spaces.GPU
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  def get_colour(image_urls, category):
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  colourLabels = list(COLOURS_DICT.keys())
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  for i in range(len(colourLabels)):
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  colourLabels[i] = colourLabels[i] + " clothing: " + category
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+ print("Colour Labels:", colourLabels) # Debug: Print colour labels
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+ print("Image URLs:", image_urls) # Debug: Print image URLs
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+
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  responses = pipe(image_urls, candidate_labels=colourLabels)
 
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  mainColour = responses[0][0]['label'].split(" clothing:")[0]
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  if mainColour not in COLOURS_DICT:
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  return None, None, None
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  labels = COLOURS_DICT[mainColour]
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  for i in range(len(labels)):
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  labels[i] = labels[i] + " clothing: " + category
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+ print("Labels for pipe:", labels) # Debug: Confirm labels are correct
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  responses = pipe(image_urls, candidate_labels=labels)
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  subColour = responses[0][0]['label'].split(" clothing:")[0]
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  return subColour, mainColour, responses[0][0]['score']
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+
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+
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  @spaces.GPU
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  def get_predicted_attributes(image_urls, category):
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  # Assuming ATTRIBUTES_DICT and pipe are defined outside this function