fix error in app.py

app.py

@@ -5,11 +5,6 @@ from PIL import Image
 from huggingface_hub import from_pretrained_keras
 import cv2
 
-st.header("Segmentacion de partes del cuerpo humano")
-
-st.markdown("Sube una imagen o selecciona un ejemplo para segmentar las distintas partes del cuerpo humano")
-
-file_imagen = st.file_uploader("Sube aqui tu imagen", type=["png", "jpg", "jpeg"])
 
 model = from_pretrained_keras("keras-io/deeplabv3p-resnet50")
 
@@ -27,12 +22,14 @@ def read_image(image):
     image = image / 127.5 - 1
     return image
 
+
 def infer(model, image_tensor):
     predictions = model.predict(np.expand_dims((image_tensor), axis=0))
     predictions = np.squeeze(predictions)
     predictions = np.argmax(predictions, axis=2)
     return predictions
 
+
 def decode_segmentation_masks(mask, colormap, n_classes):
     r = np.zeros_like(mask).astype(np.uint8)
     g = np.zeros_like(mask).astype(np.uint8)
@@ -45,12 +42,14 @@ def decode_segmentation_masks(mask, colormap, n_classes):
     rgb = np.stack([r, g, b], axis=2)
     return rgb
 
+
 def get_overlay(image, colored_mask):
     image = tf.keras.preprocessing.image.array_to_img(image)
     image = np.array(image).astype(np.uint8)
     overlay = cv2.addWeighted(image, 0.35, colored_mask, 0.65, 0)
     return overlay
 
+
 def segmentation(input_image):
     image_tensor = read_image(input_image)
     prediction_mask = infer(image_tensor=image_tensor, model=model)
@@ -58,10 +57,16 @@ def segmentation(input_image):
     overlay = get_overlay(image_tensor, prediction_colormap)
     return (overlay, prediction_colormap)
 
+
 # i = gr.inputs.Image()
 # o = [gr.outputs.Image('pil'), gr.outputs.Image('pil')]
+st.header("Segmentacion de partes del cuerpo humano")
+
+st.markdown("Sube una imagen o selecciona un ejemplo para segmentar las distintas partes del cuerpo humano")
 
-examples = ["example_image_1.jpeg", "example_image_2.jpg", "example_image_3.jpeg"]
+file_imagen = st.file_uploader("Sube aqui tu imagen", type=["png", "jpg", "jpeg"])
+
+examples = ["example_image_1.jpg", "example_image_2.jpg", "example_image_3.jpg"]
 
 col1, col2, col3 = st.columns(3)
 with col1:
@@ -82,6 +87,9 @@ with col3:
     if st.button("Corre ejemplo 1"):
         file_imagen = examples[2]
 
+# if archivo_imagen is not None:
+
+
 article = "<div style='text-align: center;'><a href='https://keras.io/examples/vision/deeplabv3_plus/' target='_blank'>Keras example by Praveen Kaushik</a></div>"
 # gr.Interface(segmentation, i, o, examples=examples, allow_flagging=False, analytics_enabled=False,
 #   title=title, description=description, article=article).launch(enable_queue=True)