Update app.py

app.py

@@ -5,21 +5,47 @@ from transformers import ViTForImageClassification, ViTModel, ViTImageProcessor
 from PIL import Image
 from sklearn.preprocessing import LabelEncoder
 import pandas as pd
+from PIL import Image, ExifTags
 
 # 中文問候函數
 def greet(name):
     return f"你好，{name}!!"
 
 # 圖像預處理
+from PIL import Image, ExifTags
+
 def preprocess_image(image):
+    """
+    將輸入圖像轉換為模型可接受的 tensor
+    支援 iPhone 圖片自動旋轉
+    """
+    # 轉成 PIL Image
     if isinstance(image, np.ndarray):
         image = Image.fromarray(np.uint8(image))
     elif not isinstance(image, Image.Image):
         image = Image.open(image)
     
+    # 修正 iPhone EXIF 方向
+    try:
+        for orientation in ExifTags.TAGS.keys():
+            if ExifTags.TAGS[orientation]=='Orientation':
+                break
+        exif=dict(image._getexif().items())
+        if exif[orientation] == 3:
+            image=image.rotate(180, expand=True)
+        elif exif[orientation] == 6:
+            image=image.rotate(270, expand=True)
+        elif exif[orientation] == 8:
+            image=image.rotate(90, expand=True)
+    except:
+        # 沒有 EXIF 資訊就直接跳過
+        pass
+
+    # 轉成 RGB
     if image.mode != 'RGB':
         image = image.convert('RGB')
 
+    # 使用 feature extractor
     inputs = feature_extractor(images=[image])
     image_tensor = torch.tensor(inputs['pixel_values'][0], dtype=torch.float32)