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Update app.py
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app.py
CHANGED
@@ -8,166 +8,8 @@ from matplotlib import gridspec
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import matplotlib.pyplot as plt
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import onnxruntime as ort
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"""ADE20K palette that maps each class to RGB values."""
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return [
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[120, 120, 120],
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[180, 120, 120],
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[6, 230, 230],
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[80, 50, 50],
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[4, 200, 3],
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[120, 120, 80],
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[140, 140, 140],
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[204, 5, 255],
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[230, 230, 230],
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[4, 250, 7],
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[224, 5, 255],
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[235, 255, 7],
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[150, 5, 61],
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[120, 120, 70],
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[8, 255, 51],
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[255, 6, 82],
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[143, 255, 140],
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[204, 255, 4],
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[255, 51, 7],
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[204, 70, 3],
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[0, 102, 200],
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[61, 230, 250],
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[255, 6, 51],
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[11, 102, 255],
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[255, 7, 71],
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[255, 9, 224],
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[9, 7, 230],
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[220, 220, 220],
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[255, 9, 92],
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[112, 9, 255],
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[8, 255, 214],
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[7, 255, 224],
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[255, 184, 6],
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[10, 255, 71],
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[255, 41, 10],
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[7, 255, 255],
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[224, 255, 8],
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[102, 8, 255],
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[255, 61, 6],
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[255, 194, 7],
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[255, 122, 8],
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[0, 255, 20],
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[255, 8, 41],
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[255, 5, 153],
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[6, 51, 255],
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[235, 12, 255],
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[160, 150, 20],
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[0, 163, 255],
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[140, 140, 140],
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[250, 10, 15],
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[20, 255, 0],
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[31, 255, 0],
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[255, 31, 0],
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[255, 224, 0],
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[153, 255, 0],
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[0, 0, 255],
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[255, 71, 0],
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[0, 235, 255],
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[0, 173, 255],
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[31, 0, 255],
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[11, 200, 200],
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[255, 82, 0],
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[0, 255, 245],
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[0, 61, 255],
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[0, 255, 112],
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[0, 255, 133],
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[255, 0, 0],
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[255, 163, 0],
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[255, 102, 0],
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[194, 255, 0],
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[0, 143, 255],
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[51, 255, 0],
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[0, 82, 255],
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[0, 255, 41],
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[0, 255, 173],
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[10, 0, 255],
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[173, 255, 0],
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[0, 255, 153],
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[255, 92, 0],
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[255, 0, 255],
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[255, 0, 245],
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[255, 0, 102],
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[255, 173, 0],
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[255, 0, 20],
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[255, 184, 184],
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[0, 31, 255],
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[0, 255, 61],
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[0, 71, 255],
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[255, 0, 204],
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[0, 255, 194],
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[0, 255, 82],
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[0, 10, 255],
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[0, 112, 255],
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[51, 0, 255],
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[0, 194, 255],
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[0, 122, 255],
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[0, 255, 163],
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[255, 153, 0],
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[0, 255, 10],
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[255, 112, 0],
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[143, 255, 0],
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[82, 0, 255],
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[163, 255, 0],
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[255, 235, 0],
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[8, 184, 170],
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[133, 0, 255],
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[0, 255, 92],
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[184, 0, 255],
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[255, 0, 31],
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[0, 184, 255],
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[0, 214, 255],
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[255, 0, 112],
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[92, 255, 0],
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[0, 224, 255],
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[112, 224, 255],
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[70, 184, 160],
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[163, 0, 255],
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[153, 0, 255],
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[71, 255, 0],
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[255, 0, 163],
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[255, 204, 0],
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[255, 0, 143],
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[0, 255, 235],
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[133, 255, 0],
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[255, 0, 235],
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[245, 0, 255],
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[255, 0, 122],
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[255, 245, 0],
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[10, 190, 212],
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[214, 255, 0],
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[0, 204, 255],
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[20, 0, 255],
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[255, 255, 0],
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[0, 153, 255],
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[0, 41, 255],
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[0, 255, 204],
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[41, 0, 255],
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[41, 255, 0],
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[173, 0, 255],
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[0, 245, 255],
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[71, 0, 255],
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[122, 0, 255],
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[0, 255, 184],
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[0, 92, 255],
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[184, 255, 0],
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[0, 133, 255],
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[255, 214, 0],
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[25, 194, 194],
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[102, 255, 0],
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[92, 0, 255],
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]
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labels_list = []
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colormap = np.asarray(ade_palette())
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model_filename = 'segformer-b5-finetuned-ade-640-640.onnx'
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sess = ort.InferenceSession(model_filename)
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csv.field_size_limit(sys.maxsize)
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@@ -175,6 +17,17 @@ with open(r'labels.txt', 'r') as fp:
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for line in fp:
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labels_list.append(line[:-1])
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def label_to_color_image(label):
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if label.ndim != 2:
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raise ValueError("Expect 2-D input label")
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import matplotlib.pyplot as plt
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import onnxruntime as ort
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ade_palette = []
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labels_list = []
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csv.field_size_limit(sys.maxsize)
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for line in fp:
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labels_list.append(line[:-1])
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with open(r'ade_palette.txt', 'r') as fp:
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for line in fp:
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tmp_list = list(map(int, line[:-1].strip('][').split(', ')))
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ade_palette.append(tmp_list)
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colormap = np.asarray(ade_palette)
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model_filename = 'segformer-b5-finetuned-ade-640-640.onnx'
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sess = ort.InferenceSession(model_filename)
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def label_to_color_image(label):
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if label.ndim != 2:
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raise ValueError("Expect 2-D input label")
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