dzmu commited on
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60f051f
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1 Parent(s): 813214c

Update app.py

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Files changed (1) hide show
  1. app.py +37 -8
app.py CHANGED
@@ -67,16 +67,45 @@ except Exception as e:
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  style_prompts = {
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  'drippy': [
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- "avant-garde streetwear", "high-fashion designer outfit", "trendsetting urban attire",
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- "luxury sneakers and chic accessories", "cutting-edge, bold style"
 
 
 
 
 
 
 
 
 
 
 
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  ],
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  'mid': [
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- "casual everyday outfit", "modern minimalistic attire", "comfortable yet stylish look",
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- "simple, relaxed streetwear", "balanced, practical fashion"
 
 
 
 
 
 
 
 
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  ],
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  'not_drippy': [
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- "disheveled outfit", "poorly coordinated fashion", "unfashionable, outdated attire",
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- "tacky, mismatched ensemble", "sloppy, uninspired look"
 
 
 
 
 
 
 
 
 
 
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  ]
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  }
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@@ -268,7 +297,7 @@ def analyze_outfit(input_img):
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  # Determine overall style category AND DEFINE score_label
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  score_label = "Style Score" # Initialize with a default/fallback
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- if drip_score > 0.41 and drip_score > mid_score and drip_score > not_score:
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  category_key = 'drippy'
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  final_score = drip_score
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  score_label = "Drip Score"
@@ -311,7 +340,7 @@ def analyze_outfit(input_img):
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  return ("<p style='color: #FF5555;'>Error during CLIP analysis.</p>",
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  None, f"Analysis Error: {e}")
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- # 4) Determine the Final Item to Mention in Response
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  final_clothing_item = "style" # Ultimate fallback generic term
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  generic_response_needed = False
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  style_prompts = {
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  'drippy': [
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+ "avant-garde streetwear",
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+ "high-fashion designer outfit",
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+ "trendsetting urban attire",
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+ "luxury sneakers and chic accessories",
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+ "cutting-edge, bold style",
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+ "tailored suit with designer shoes",
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+ "modern formalwear with flair",
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+ "sleek all-black techwear fit",
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+ "runway-ready monochrome look",
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+ "statement outerwear with luxury detailing",
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+ "elevated business casual with premium materials",
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+ "fashion-forward layering with color coordination",
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+ "comfortable yet stylish look"
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  ],
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  'mid': [
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+ "casual everyday outfit",
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+ "modern minimalistic attire",
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+ "simple, relaxed streetwear",
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+ "balanced, practical fashion",
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+ "smart casual outfit with neutral tones",
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+ "clean hoodie with jeans",
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+ "basic tee and joggers",
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+ "store-bought coordinated outfit",
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+ "mid-range branded streetwear",
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+ "plain bomber jacket and fitted pants"
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  ],
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  'not_drippy': [
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+ "disheveled outfit",
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+ "poorly coordinated fashion",
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+ "unfashionable, outdated attire",
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+ "tacky, mismatched ensemble",
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+ "sloppy, uninspired look",
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+ "wrinkled clothes with clashing colors",
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+ "oversized tee and sagging pants with slides",
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+ "random logos and no fit cohesion",
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+ "stained or ill-fitting garments",
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+ "childish graphic tee with athletic shorts",
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+ "pajama bottoms worn outside",
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+ "shoes completely unrelated to outfit"
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  ]
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  }
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  # Determine overall style category AND DEFINE score_label
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  score_label = "Style Score" # Initialize with a default/fallback
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+ if drip_score > 0.37 and drip_score > mid_score and drip_score > not_score:
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  category_key = 'drippy'
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  final_score = drip_score
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  score_label = "Drip Score"
 
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  return ("<p style='color: #FF5555;'>Error during CLIP analysis.</p>",
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  None, f"Analysis Error: {e}")
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+ # Determine the Final Item to Mention in Response
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  final_clothing_item = "style" # Ultimate fallback generic term
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  generic_response_needed = False
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