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import sys |
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import numpy as np |
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from paddle_serving_client import Client |
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from paddle_serving_app.reader import * |
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import cv2 |
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preprocess = Sequential([ |
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File2Image(), BGR2RGB(), Resize( |
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(608, 608), interpolation=cv2.INTER_LINEAR), Div(255.0), Transpose( |
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(2, 0, 1)) |
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]) |
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postprocess = RCNNPostprocess(sys.argv[1], "output", [608, 608]) |
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client = Client() |
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client.load_client_config("serving_client/serving_client_conf.prototxt") |
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client.connect(['127.0.0.1:9393']) |
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im = preprocess(sys.argv[2]) |
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fetch_map = client.predict( |
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feed={ |
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"image": im, |
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"im_shape": np.array(list(im.shape[1:])).reshape(-1), |
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"scale_factor": np.array([1.0, 1.0]).reshape(-1), |
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}, |
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fetch=["multiclass_nms3_0.tmp_0"], |
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batch=False) |
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print(fetch_map) |
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fetch_map["image"] = sys.argv[2] |
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postprocess(fetch_map) |
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