Update app.py

app.py

@@ -39,6 +39,17 @@ def get_complementary_color(rgb_color):
     r, g, b = colorsys.hsv_to_rgb(complementary_h, s, v)
     return closest_color((r, g, b))
 
+def get_monochromatic_color(rgb_color):
+    h, s, v = colorsys.rgb_to_hsv(*rgb_color)
+    light_h = h
+    dark_h = (h + 0.5) % 1.0
+    light_rgb = colorsys.hsv_to_rgb(light_h, s, v)
+    dark_rgb = colorsys.hsv_to_rgb(dark_h, s, v)
+    light_color = closest_color(light_rgb)
+    dark_color = closest_color(dark_rgb)
+    return light_color, dark_color
+
+
 def get_outfit_recommendation(pred_class):
     if pred_class == 'top':
         return 'Jeans'
@@ -48,11 +59,13 @@ def get_outfit_recommendation(pred_class):
         return 'Item'
 
 def predict(image):
-    pred_class, _, _ = learn.predict(image)
+    pred_class, pred_idx, outputs = learn.predict(image)
+    pred_class = class_names[pred_idx]  # Convert index to class name
     dominant_color = get_dominant_color(image)
     complementary_color = get_complementary_color(dominant_color)
+    mono_light_color, mono_dark_color = get_monochromatic_color(dominant_color)
     garment_recommendation = get_outfit_recommendation(pred_class)
-    return f"Complementary item: {garment_recommendation} in {complementary_color}"
+    return f"Complementary item: {garment_recommendation} in {complementary_color}. Monochromatic options: {mono_light_color} or {mono_dark_color}."
 
 def gradio_predict(image):
     if isinstance(image, np.ndarray):