Update app.py

app.py

@@ -1,36 +1,36 @@
 import numpy as np
 import gradio as gr
 from PIL import Image
-import rasterio
+import scipy.misc
 
 def cargar_imagen_tif(tifile):
     try:
-        with rasterio.open(tifile, "r") as src:
-            data = src.read()
-        image = rasterio.image.fromarray(data[0])  # Convertir el arreglo raster a una imagen Rasterio
-        return convertir_a_blanco_y_negro(image)  # Captura el valor de retorno de la función
+        with open(tifile, 'rb') as f:
+            data = scipy.misc.imread(f, mode='L')
+        tuki = Image.fromarray(data)  # Convertir el arreglo raster a una imagen PIL
+        return convertir_a_blanco_y_negro(tuki)  # Captura el valor de retorno de la función
     except Exception as e:
         return f"Error al cargar la imagen TIFF: {str(e)}"
 
-def convertir_a_blanco_y_negro(input_image):
+def convertir_a_blanco_y_negro(input_img):
     try:
-        image_array = np.array(input_image)
+        img_array = np.array(input_img)
 
-        binary_image = np.zeros_like(image_array)
+        binary_img = np.zeros_like(img_array)
 
         color_threshold = 50
 
-        for i in range(image_array.shape[0]):
-            for j in range(image_array.shape[1]):
-                pixel_color = image_array[i, j]
+        for i in range(img_array.shape[0]):
+            for j in range(img_array.shape[1]):
+                pixel_color = img_array[i, j]
                 if np.all(pixel_color <= color_threshold):
-                    binary_image[i, j] = 0
+                    binary_img[i, j] = 0
                 else:
-                    binary_image[i, j] = 255
+                    binary_img[i, j] = 255
 
-        binary_image = Image.fromarray(np.uint8(binary_image))
+        binary_img = Image.fromarray(np.uint8(binary_img))
 
-        return binary_image, "Hecho"
+        return binary_img, "Hecho"
     except Exception as e:
         return f"Error al convertir a blanco y negro: {str(e)}"