Update SegCloth.py

SegCloth.py

@@ -1,5 +1,5 @@
 from transformers import pipeline
-from PIL import Image, ImageChops, ImageOps
+from PIL import Image, ImageChops
 import numpy as np
 from io import BytesIO
 import base64
@@ -12,6 +12,22 @@ def encode_image_to_base64(image):
     image.save(buffered, format="PNG")
     return base64.b64encode(buffered.getvalue()).decode('utf-8')
 
+def is_image_significant(image, threshold=0.01):
+    """
+    Vérifie si une image contient suffisamment de contenu non transparent.
+    :param image: L'image PIL à vérifier.
+    :param threshold: Seuil de pourcentage de pixels non transparents pour considérer l'image comme significative.
+    :return: True si l'image est significative, sinon False.
+    """
+    np_image = np.array(image)
+    # Compte le nombre de pixels non transparents
+    non_transparent_pixels = np.sum(np_image[:, :, 3] > 0)
+    # Calcul du pourcentage de pixels non transparents
+    total_pixels = np_image.shape[0] * np_image.shape[1]
+    non_transparent_percentage = non_transparent_pixels / total_pixels
+    
+    return non_transparent_percentage > threshold
+
 def segment_clothing(img, clothes=["Hat", "Upper-clothes", "Skirt", "Pants", "Dress", "Belt", "Left-shoe", "Right-shoe", "Scarf"], margin=10):
     # Segmentation de l'image
     segments = segmenter(img)
@@ -49,9 +65,10 @@ def segment_clothing(img, clothes=["Hat", "Upper-clothes", "Skirt", "Pants", "Dr
                 # Recadrer l'image à la taille du masque avec la marge
                 cropped_image = empty_image.crop((left, top, right, bottom))
                 
-                # Encodage de l'image recadrée en base64
-                imageBase64 = encode_image_to_base64(cropped_image)
-                #result_images.append((s['label'], imageBase64))
-                result_images.append(imageBase64)
+                # Vérifier si l'image recadrée est significative
+                if is_image_significant(cropped_image):
+                    # Encodage de l'image recadrée en base64
+                    imageBase64 = encode_image_to_base64(cropped_image)
+                    result_images.append(imageBase64)
 
     return result_images