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Update pages/Entorno de Ejecución.py
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pages/Entorno de Ejecución.py
CHANGED
@@ -97,22 +97,20 @@ with cnn:
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if not executed:
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ultraptctrn = [load_model(model_dict[model]) for model in ultraversions]
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executed = True
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-
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try:
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y_gorrito, raw_img = tf_predict(ultraptctrn,
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except:
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y_gorrito, raw_img = basic_predict(ultraptctrn,
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else:
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with st.spinner('Cargando predicción...'):
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selected_models = [load_model(model_dict[model]) for model in model_choice if model not in selected_models]
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final_weights = weight_list if len(weight_list) >= 1 else [1 for i in range(len(selected_models))]
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try:
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y_gorrito, raw_img = tf_predict(selected_models, img)
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except:
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y_gorrito, raw_img = basic_predict(selected_models, img)
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finally:
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st.write(y_gorrito, final_weights)
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if round(float(y_gorrito*100)) >= threshold:
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st.success("¡Patacón Detectado!")
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if not executed:
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ultraptctrn = [load_model(model_dict[model]) for model in ultraversions]
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executed = True
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+
final_weights = weight_list if len(weight_list) >= 1 else [1 for i in range(len(ultraptctrn))]
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try:
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y_gorrito, raw_img = tf_predict(ultraptctrn, final_weights, img)
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except:
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y_gorrito, raw_img = basic_predict(ultraptctrn, final_weights, img)
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else:
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with st.spinner('Cargando predicción...'):
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selected_models = [load_model(model_dict[model]) for model in model_choice if model not in selected_models]
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final_weights = weight_list if len(weight_list) >= 1 else [1 for i in range(len(selected_models))]
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try:
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y_gorrito, raw_img = tf_predict(selected_models, final_weights, img)
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except:
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y_gorrito, raw_img = basic_predict(selected_models, final_weights, img)
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if round(float(y_gorrito*100)) >= threshold:
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st.success("¡Patacón Detectado!")
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