updated model to all model

app.py

@@ -8,16 +8,14 @@ import mediapipe as mp
 import numpy as np
 from PIL import Image
 
-feature_extractor = ViTImageProcessor.from_pretrained('ArdyL/ViT_SIBI_Kata')
-model = AutoModelForImageClassification.from_pretrained('ArdyL/ViT_SIBI_Kata')
+feature_extractor = ViTImageProcessor.from_pretrained('ArdyL/VIT_SIBI_ALL')
+model = AutoModelForImageClassification.from_pretrained('ArdyL/VIT_SIBI_ALL')
 
 
 mp_drawing_styles = mp.solutions.drawing_styles
 mp_holistic = mp.solutions.holistic
 mp_pose = mp.solutions.pose
 mp_drawing = mp.solutions.drawing_utils
-examples_dir = './'
-example_files = glob.glob(os.path.join(examples_dir, '*.jpg'))
 
 
 def preprocess(im):
@@ -82,13 +80,12 @@ def classify_image(image):
     return label  # confidences
 
 
-with gr.Blocks(title=">ViT - SIBI Classifier",
-               css=".gradio-container {background:mintcream;}"
+with gr.Blocks(title=">ViT - SIBI Classifier"
                ) as demo:
     # gr.HTML("""<div style="font-family:'Times New Roman', 'Serif'; font-size:16pt; font-weight:bold; text-align:center; color:royalblue;">ViT - SIBI Classifier</div>""")
 
     # txt_2 = gr.Textbox(label="Input 2", visible=False)
-    with gr.Tab("Upload Image", id='upload-image'):
+    with gr.Tab("Upload Image", id='upload-image', ):
         with gr.Row():
             uploadImage = gr.Image(
                 type="numpy", image_mode="RGB", shape=(224, 224))