Update app.py
Browse files
app.py
CHANGED
@@ -6,7 +6,6 @@ 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 tensorflow.keras.applications.resnet50 import ResNet50, preprocess_input, decode_predictions
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feature_extractor = SegformerFeatureExtractor.from_pretrained(
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"nvidia/segformer-b0-finetuned-cityscapes-512-1024"
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@@ -102,21 +101,12 @@ def sepia(input_img):
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fig = draw_plot(pred_img, seg)
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return fig
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custom_template = "my_custom_template.html"
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model = ResNet50()
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def classify_image(inp):
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inp = preprocess_input(inp)
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preds = model.predict(inp)
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label = decode_predictions(preds, top=1)[0][0][1]
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return label
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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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title="SWJIN11 TASK",
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description="경제학과 202211357 진성원",
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interpretation="tooltip",
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examples=["ADE_val_00000001.jpeg", "ADE_val_00001248.jpg", "image1.jpg", "image2.jpg", "image3.jpg", "image4.jpg"],
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allow_flagging='never')
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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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"nvidia/segformer-b0-finetuned-cityscapes-512-1024"
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fig = draw_plot(pred_img, seg)
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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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title="SWJIN11 TASK",
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description="경제학과 202211357 진성원",
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examples=["ADE_val_00000001.jpeg", "ADE_val_00001248.jpg", "image1.jpg", "image2.jpg", "image3.jpg", "image4.jpg"],
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allow_flagging='never')
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