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Update app.py
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app.py
CHANGED
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@@ -38,9 +38,12 @@ def get_complementary_color(rgb_color):
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complementary_h = (h + 0.5) % 1.0
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r, g, b = colorsys.hsv_to_rgb(complementary_h, s, v)
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complementary_color = closest_color((r, g, b))
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# Get shades or tones of the complementary color
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return complementary_color, complementary_palette
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@@ -71,14 +74,7 @@ def predict(image):
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garment_recommendation = get_outfit_recommendation(pred_class)
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# Construct output string
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output = f"For your {pred_class.lower()}, consider pairing with {garment_recommendation.lower()} in {complementary_color}."
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# Handle monochromatic options
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monochromatic_options = set(complementary_palette) # Use a set to avoid duplicates
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monochromatic_options.discard(complementary_color.lower()) # Remove the complementary color
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if len(monochromatic_options) > 0:
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output += f"\nMonochromatic options: {', '.join(monochromatic_options)}."
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return output # Return the formatted output
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complementary_h = (h + 0.5) % 1.0
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r, g, b = colorsys.hsv_to_rgb(complementary_h, s, v)
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complementary_color = closest_color((r, g, b))
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complementary_palette = []
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# Get shades or tones of the complementary color
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complementary_colors = get_monochromatic_palette(complementary_color)
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for color in complementary_colors:
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if closest_color(color)!=complementary_color:
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complementary_palette.append(closest_color(color))
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return complementary_color, complementary_palette
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garment_recommendation = get_outfit_recommendation(pred_class)
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# Construct output string
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output = f"For your {pred_class.lower()}, consider pairing with {garment_recommendation.lower()} in {complementary_color}, {complementary_palette}."
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return output # Return the formatted output
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