Update app.py
Browse files
app.py
CHANGED
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import gradio as gr
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import numpy as np
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from PIL import Image
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import tensorflow as tf
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from transformers import SegformerFeatureExtractor, TFSegformerForSemanticSegmentation
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from matplotlib import gridspec
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import matplotlib.pyplot as plt
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# TensorFlow ๋ฒ์ ์ถฉ๋ ํด๊ฒฐ์ ์ํด 2.0 ๋ฒ์ ์ด์์ ์ฌ์ฉ
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if tf.__version__.startswith("1."):
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tf.compat.v1.disable_v2_behavior()
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tf.compat.v1.enable_eager_execution()
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tf.compat.v1.InteractiveSession()
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tf.compat.v1.get_default_graph()
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tf.compat.v1.disable_eager_execution()
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# ๋ชจ๋ธ ๋ฐ ํน์ฑ ์ถ์ถ๊ธฐ ๋ก๋
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feature_extractor = SegformerFeatureExtractor.from_pretrained("mattmdjaga/segformer_b2_clothes")
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model = TFSegformerForSemanticSegmentation.from_pretrained("mattmdjaga/segformer_b2_clothes")
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feature_extractor = SegformerFeatureExtractor.from_pretrained(
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"mattmdjaga/segformer_b2_clothes"
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@@ -112,9 +101,11 @@ def sepia(input_img):
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return fig
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demo = gr.Interface(fn=sepia,
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inputs=gr.Image(),
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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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demo.launch()
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import gradio as gr
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from matplotlib import gridspec
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import matplotlib.pyplot as plt
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import numpy as np
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from PIL import Image
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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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"mattmdjaga/segformer_b2_clothes"
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return fig
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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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demo.launch()
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