Spaces:
Sleeping
Sleeping
Update pages/Entorno de Ejecución.py
Browse files
pages/Entorno de Ejecución.py
CHANGED
|
@@ -68,10 +68,12 @@ with cnn:
|
|
| 68 |
# Set the image dimensions
|
| 69 |
IMAGE_WIDTH = IMAGE_HEIGHT = 224
|
| 70 |
|
| 71 |
-
uploaded_file = st.file_uploader(label = '',type= ['jpg','png', 'jpeg', 'jfif', 'webp', 'heic'])
|
| 72 |
executed = False
|
| 73 |
|
| 74 |
with col_b:
|
|
|
|
|
|
|
|
|
|
| 75 |
if st.button('¿Hay un patacón en la imagen?'):
|
| 76 |
if len(selected_models) > 0 and ultra_flag:
|
| 77 |
st.write('Debe elegir un solo método: Ultra-Patacotrón o selección múltiple.')
|
|
@@ -90,13 +92,13 @@ with cnn:
|
|
| 90 |
else:
|
| 91 |
with st.spinner('Cargando predicción...'):
|
| 92 |
selected_models = [load_model(model_dict[model]) for model in model_choice if model not in selected_models]
|
| 93 |
-
y_gorrito =
|
| 94 |
|
| 95 |
-
if y_gorrito >= threshold:
|
| 96 |
st.success("¡Patacón Detectado!")
|
| 97 |
else:
|
| 98 |
st.error("No se considera que haya un patacón en la imagen")
|
| 99 |
-
st.caption(f'La probabilidad de que la imagen tenga un patacón es del: {y_gorrito * 100}%')
|
| 100 |
st.image(raw_img.numpy())
|
| 101 |
st.caption('Si los resultados no fueron los esperados, por favor, [haz click aquí](https://docs.google.com/forms/d/e/1FAIpQLScH0ZxAV8aSqs7TPYi86u0nkxvQG3iuHCStWNB-BoQnSW2V0g/viewform?usp=sf_link)')
|
| 102 |
else:
|
|
|
|
| 68 |
# Set the image dimensions
|
| 69 |
IMAGE_WIDTH = IMAGE_HEIGHT = 224
|
| 70 |
|
|
|
|
| 71 |
executed = False
|
| 72 |
|
| 73 |
with col_b:
|
| 74 |
+
|
| 75 |
+
uploaded_file = st.file_uploader(label = '',type= ['jpg','png', 'jpeg', 'jfif', 'webp', 'heic'])
|
| 76 |
+
|
| 77 |
if st.button('¿Hay un patacón en la imagen?'):
|
| 78 |
if len(selected_models) > 0 and ultra_flag:
|
| 79 |
st.write('Debe elegir un solo método: Ultra-Patacotrón o selección múltiple.')
|
|
|
|
| 92 |
else:
|
| 93 |
with st.spinner('Cargando predicción...'):
|
| 94 |
selected_models = [load_model(model_dict[model]) for model in model_choice if model not in selected_models]
|
| 95 |
+
y_gorrito = float(predict(selected_models, img))
|
| 96 |
|
| 97 |
+
if round(y_gorrito) >= threshold:
|
| 98 |
st.success("¡Patacón Detectado!")
|
| 99 |
else:
|
| 100 |
st.error("No se considera que haya un patacón en la imagen")
|
| 101 |
+
st.caption(f'La probabilidad de que la imagen tenga un patacón es del: {round(y_gorrito * 100, 2)}%')
|
| 102 |
st.image(raw_img.numpy())
|
| 103 |
st.caption('Si los resultados no fueron los esperados, por favor, [haz click aquí](https://docs.google.com/forms/d/e/1FAIpQLScH0ZxAV8aSqs7TPYi86u0nkxvQG3iuHCStWNB-BoQnSW2V0g/viewform?usp=sf_link)')
|
| 104 |
else:
|