devanshsrivastav commited on
Commit
2b3e3f0
1 Parent(s): 3b1e528

capitalize to title

Browse files
Files changed (1) hide show
  1. app.py +9 -3
app.py CHANGED
@@ -109,6 +109,7 @@ if submit:
109
  predicted_probabilities_HS = response_HS[0]
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  predicted_probabilities_SD = response_SD[0]
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  ED, _, HS, __, SD = st.columns([4,1,2,1,2])
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  with ED:
@@ -126,11 +127,16 @@ if submit:
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  vertical_spacing=0.4)
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  for i, emotion in enumerate(top_emotions):
 
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  category = emotion['label']
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  color = color_map[category]
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  value = normalized_scores[i]
 
 
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  row = i // 2 + 1
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  col = i % 2 + 1
 
 
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  fig.add_trace(go.Indicator(
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  domain={'x': [0, 1], 'y': [0, 1]},
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  value=value,
@@ -148,10 +154,10 @@ if submit:
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  'thickness': 0.5,
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  'value': 50}}), row=row, col=col)
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-
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- # Update layout
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  fig.update_layout(height=400, margin=dict(t=50, b=5, l=0, r=0))
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  # Display gauge charts
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  st.text("")
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  st.text("")
@@ -186,7 +192,7 @@ if submit:
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  st.text("")
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  st.subheader("Sexism Detection")
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  st.text("")
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- label_SD = predicted_probabilities_SD[0]['label'].capitalize()
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  st.image(f"assets/{label_SD}.jpg", width=200)
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  st.text("")
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  st.text("")
 
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  predicted_probabilities_HS = response_HS[0]
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  predicted_probabilities_SD = response_SD[0]
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+ # Creating columns to visualize the results
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  ED, _, HS, __, SD = st.columns([4,1,2,1,2])
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  with ED:
 
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  vertical_spacing=0.4)
128
 
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  for i, emotion in enumerate(top_emotions):
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+ # Get the emotion category, color, and normalized score for the current emotion
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  category = emotion['label']
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  color = color_map[category]
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  value = normalized_scores[i]
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+
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+ # Calculate the row and column position for adding the trace to the subplots
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  row = i // 2 + 1
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  col = i % 2 + 1
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+
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+ # Add a gauge chart trace for the current emotion category
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  fig.add_trace(go.Indicator(
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  domain={'x': [0, 1], 'y': [0, 1]},
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  value=value,
 
154
  'thickness': 0.5,
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  'value': 50}}), row=row, col=col)
156
 
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+ # Update the layout of the figure
 
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  fig.update_layout(height=400, margin=dict(t=50, b=5, l=0, r=0))
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+
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  # Display gauge charts
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  st.text("")
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  st.text("")
 
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  st.text("")
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  st.subheader("Sexism Detection")
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  st.text("")
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+ label_SD = predicted_probabilities_SD[0]['label'].title()
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  st.image(f"assets/{label_SD}.jpg", width=200)
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  st.text("")
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  st.text("")