Update app.py

app.py

@@ -5,21 +5,10 @@ import matplotlib.pyplot as plt
 import numpy as np
 from PIL import Image
 import tensorflow as tf
-
-# Use a pipeline as a high-level helper
-from transformers import pipeline
-
-pipe = pipeline("image-segmentation", model="mattmdjaga/segformer_b2_clothes")
-
-from transformers import AutoFeatureExtractor, SegformerForSemanticSegmentation
-
-feature_extractor = AutoFeatureExtractor.from_pretrained("mattmdjaga/segformer_b2_clothes")
-model = SegformerForSemanticSegmentation.from_pretrained("mattmdjaga/segformer_b2_clothes")
-
-'''조ㅛ from transformers import SegformerFeatureExtractor, TFSegformerForSemanticSegmentation
+from transformers import SegformerFeatureExtractor, TFSegformerForSemanticSegmentation
 
 feature_extractor = SegformerFeatureExtractor.from_pretrained("mattmdjaga/segformer_b2_clothes")
-model = TFSegformerForSemanticSegmentation.from_pretrained("mattmdjaga/segformer_b2_clothes")'''
+model = TFSegformerForSemanticSegmentation.from_pretrained("mattmdjaga/segformer_b2_clothes")
 
 def ade_palette():
     """ADE20K palette that maps each class to RGB values."""