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Runtime error
Update app.py
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app.py
CHANGED
@@ -12,7 +12,7 @@ from io import BytesIO
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import face_recognition
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from turtle import title
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from openai import OpenAI
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from collections import
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from typing import List, Optional, Set, Dict, Any
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from transformers import pipeline
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@@ -153,7 +153,7 @@ 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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colour_labels = [f"{colour}, clothing: {category}" for colour in COLOURS_DICT.keys()]
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responses = pipe(image_urls, candidate_labels=colour_labels
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main_colour, main_score = get_most_common_label(responses)
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if main_colour not in COLOURS_DICT:
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@@ -166,7 +166,7 @@ def get_colour(image_urls, category):
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labels = [label for key, values in COLOURS_DICT.items() if key != main_colour for label in values]
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labels = [f"{label}, clothing: {category}" for label in labels]
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responses = pipe(image_urls, candidate_labels=labels
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most_common, sub_score = get_most_common_label(responses)
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sub_colours = [most_common]
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@@ -176,7 +176,7 @@ def get_colour(image_urls, category):
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sub_key = next(key for key, values in COLOURS_DICT.items() if most_common in values)
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labels = [label for key, values in COLOURS_DICT.items() if key not in {main_colour, sub_key} for label in values]
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labels = [f"{label}, clothing: {category}" for label in labels]
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responses = pipe(image_urls, candidate_labels=labels
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most_common, tertiary_score = get_most_common_label(responses)
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sub_colours.append(most_common)
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import face_recognition
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from turtle import title
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from openai import OpenAI
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from collections import defaultdict
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from typing import List, Optional, Set, Dict, Any
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from transformers import pipeline
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@spaces.GPU
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def get_colour(image_urls, category):
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colour_labels = [f"{colour}, clothing: {category}" for colour in COLOURS_DICT.keys()]
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responses = pipe(image_urls, candidate_labels=colour_labels)
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main_colour, main_score = get_most_common_label(responses)
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if main_colour not in COLOURS_DICT:
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labels = [label for key, values in COLOURS_DICT.items() if key != main_colour for label in values]
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labels = [f"{label}, clothing: {category}" for label in labels]
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responses = pipe(image_urls, candidate_labels=labels)
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most_common, sub_score = get_most_common_label(responses)
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sub_colours = [most_common]
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sub_key = next(key for key, values in COLOURS_DICT.items() if most_common in values)
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labels = [label for key, values in COLOURS_DICT.items() if key not in {main_colour, sub_key} for label in values]
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labels = [f"{label}, clothing: {category}" for label in labels]
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responses = pipe(image_urls, candidate_labels=labels)
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most_common, tertiary_score = get_most_common_label(responses)
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sub_colours.append(most_common)
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