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han-byeol commited on
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1 Parent(s): dba5369

Update app.py

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  1. app.py +4 -136
app.py CHANGED
@@ -8,10 +8,10 @@ import tensorflow as tf
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  from transformers import SegformerFeatureExtractor, TFSegformerForSemanticSegmentation
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  feature_extractor = SegformerFeatureExtractor.from_pretrained(
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- "nvidia/segformer-b5-finetuned-ade-640-640"
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  )
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  model = TFSegformerForSemanticSegmentation.from_pretrained(
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- "nvidia/segformer-b5-finetuned-ade-640-640"
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  )
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  def ade_palette():
@@ -34,139 +34,7 @@ def ade_palette():
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  [200, 56, 123],
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  [87, 92, 204],
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  [120, 56, 123],
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- [45, 78, 123],
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- [156, 200, 56],
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- [32, 90, 210],
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- [56, 123, 67],
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- [180, 56, 123],
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- [123, 67, 45],
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- [45, 134, 200],
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- [67, 56, 123],
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- [78, 123, 67],
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- [32, 210, 90],
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- [45, 56, 189],
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- [123, 56, 123],
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- [56, 156, 200],
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- [189, 56, 45],
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- [112, 200, 56],
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- [56, 123, 45],
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- [200, 32, 90],
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- [123, 45, 78],
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- [200, 156, 56],
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- [45, 67, 123],
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- [56, 45, 78],
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- [45, 56, 123],
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- [123, 67, 56],
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- [56, 78, 123],
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- [210, 90, 32],
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- [123, 56, 189],
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- [45, 200, 134],
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- [67, 123, 56],
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- [123, 45, 67],
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- [90, 32, 210],
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- [200, 45, 78],
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- [32, 210, 90],
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- [45, 123, 67],
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- [165, 42, 87],
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- [72, 145, 167],
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- [15, 158, 75],
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- [209, 89, 40],
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- [32, 21, 121],
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- [184, 20, 100],
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- [56, 135, 15],
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- [128, 92, 176],
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- [1, 119, 140],
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- [220, 151, 43],
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- [41, 97, 72],
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- [148, 38, 27],
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- [107, 86, 176],
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- [21, 26, 136],
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- [174, 27, 90],
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- [91, 96, 204],
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- [108, 50, 107],
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- [27, 45, 136],
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- [168, 200, 52],
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- [7, 102, 27],
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- [42, 93, 56],
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- [140, 52, 112],
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- [92, 107, 168],
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- [17, 118, 176],
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- [59, 50, 174],
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- [206, 40, 143],
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- [44, 19, 142],
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- [23, 168, 75],
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- [54, 57, 189],
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- [144, 21, 15],
100
- [15, 176, 35],
101
- [107, 19, 79],
102
- [204, 52, 114],
103
- [48, 173, 83],
104
- [11, 120, 53],
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- [206, 104, 28],
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- [20, 31, 153],
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- [27, 21, 93],
108
- [11, 206, 138],
109
- [112, 30, 83],
110
- [68, 91, 152],
111
- [153, 13, 43],
112
- [25, 114, 54],
113
- [92, 27, 150],
114
- [108, 42, 59],
115
- [194, 77, 5],
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- [145, 48, 83],
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- [7, 113, 19],
118
- [25, 92, 113],
119
- [60, 168, 79],
120
- [78, 33, 120],
121
- [89, 176, 205],
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- [27, 200, 94],
123
- [210, 67, 23],
124
- [123, 89, 189],
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- [225, 56, 112],
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- [75, 156, 45],
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- [172, 104, 200],
128
- [15, 170, 197],
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- [240, 133, 65],
130
- [89, 156, 112],
131
- [214, 88, 57],
132
- [156, 134, 200],
133
- [78, 57, 189],
134
- [200, 78, 123],
135
- [106, 120, 210],
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- [145, 56, 112],
137
- [89, 120, 189],
138
- [185, 206, 56],
139
- [47, 99, 28],
140
- [112, 189, 78],
141
- [200, 112, 89],
142
- [89, 145, 112],
143
- [78, 106, 189],
144
- [112, 78, 189],
145
- [156, 112, 78],
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- [28, 210, 99],
147
- [78, 89, 189],
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- [189, 78, 57],
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- [112, 200, 78],
150
- [189, 47, 78],
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- [205, 112, 57],
152
- [78, 145, 57],
153
- [200, 78, 112],
154
- [99, 89, 145],
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- [200, 156, 78],
156
- [57, 78, 145],
157
- [78, 57, 99],
158
- [57, 78, 145],
159
- [145, 112, 78],
160
- [78, 89, 145],
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- [210, 99, 28],
162
- [145, 78, 189],
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- [57, 200, 136],
164
- [89, 156, 78],
165
- [145, 78, 99],
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- [99, 28, 210],
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- [189, 78, 47],
168
- [28, 210, 99],
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- [78, 145, 57],
170
  ]
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172
  labels_list = []
@@ -235,7 +103,7 @@ def sepia(input_img):
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  demo = gr.Interface(fn=sepia,
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  inputs=gr.Image(shape=(400, 600)),
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  outputs=['plot'],
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- examples=["ADE_val_00000001.jpeg", "ADE_val_00001159.jpg", "ADE_val_00001248.jpg", "ADE_val_00001472.jpg"],
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  allow_flagging='never')
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241
 
 
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  from transformers import SegformerFeatureExtractor, TFSegformerForSemanticSegmentation
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  feature_extractor = SegformerFeatureExtractor.from_pretrained(
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+ "mattmdjaga/segformer_b2_clothes"
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  )
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  model = TFSegformerForSemanticSegmentation.from_pretrained(
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+ "mattmdjaga/segformer_b2_clothes"
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  )
16
 
17
  def ade_palette():
 
34
  [200, 56, 123],
35
  [87, 92, 204],
36
  [120, 56, 123],
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+ [45, 78, 123]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ]
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  labels_list = []
 
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  demo = gr.Interface(fn=sepia,
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  inputs=gr.Image(shape=(400, 600)),
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  outputs=['plot'],
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+ examples=["person-1.jpg", "person-2.jpg", "person-3.jpg", "person-4.jpg", "person-5.jpg"],
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  allow_flagging='never')
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