v1

requirements.txt

@@ -7,4 +7,4 @@ tensorflow==2.11.0
 transformers==4.30.2
 matplotlib
 numpy
-tf-keras-vis=0.8.5
+tf-keras-vis==0.8.5

revelado/revelado.py

@@ -8,9 +8,15 @@ import re
 from PIL import Image, ImageChops, ImageEnhance
 
 def convert_to_ela_image(filename, quality=90):
+   
+     
+    
     im = Image.open(filename).convert('RGB')
+    
     resaved_im = im
+    
     ela_im = ImageChops.difference(im, resaved_im)
+    
     extrema = ela_im.getextrema()
     max_diff = max([ex[1] for ex in extrema])
     if max_diff == 0:
@@ -18,7 +24,10 @@ def convert_to_ela_image(filename, quality=90):
     scale = 255.0 / max_diff
     
     ela_im = ImageEnhance.Brightness(ela_im).enhance(scale)
+    
     return ela_im
+
+
 def calculate_ela(original_image, quality=90):
    
     # Comprimir y descomprimir la imagen
@@ -38,8 +47,16 @@ def calculate_difference_image(original_image, n):
     
     ela_image = calculate_ela(original_image)
     auto_contrast_image = apply_auto_contrast(original_image)
+
+    #output_ela_image_path = os.path.join(output_folder, f"{n}_ela.jpg")
+    #output_contrast_image_path = os.path.join(output_folder, f"{n}_contraste.jpg")
+
+    #cv2.imwrite(output_ela_image_path, ela_image)
+    #cv2.imwrite(output_contrast_image_path, auto_contrast_image)
+
     difference_image = cv2.absdiff(original_image, auto_contrast_image)
     difference_image = cv2.absdiff(difference_image, ela_image)
+
     return difference_image
 
 def apply_auto_contrast(image, clip_limit=2.0, tile_grid_size=(8, 8)):