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39 lines
1.0 KiB
Python
39 lines
1.0 KiB
Python
import fastdeploy as fd
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from fastdeploy.serving.server import SimpleServer
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import os
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import logging
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logging.getLogger().setLevel(logging.INFO)
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# Configurations
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model_dir = 'PP_LiteSeg_B_STDC2_cityscapes_with_argmax_infer'
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device = 'cpu'
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use_trt = False
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# Prepare model
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model_file = os.path.join(model_dir, "model.pdmodel")
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params_file = os.path.join(model_dir, "model.pdiparams")
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config_file = os.path.join(model_dir, "deploy.yaml")
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# Setup runtime option to select hardware, backend, etc.
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option = fd.RuntimeOption()
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if device.lower() == 'gpu':
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option.use_gpu()
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if use_trt:
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option.use_trt_backend()
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option.set_trt_cache_file('pp_lite_seg.trt')
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# Create model instance
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model_instance = fd.vision.segmentation.PaddleSegModel(
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model_file=model_file,
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params_file=params_file,
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config_file=config_file,
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runtime_option=option)
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# Create server, setup REST API
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app = SimpleServer()
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app.register(
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task_name="fd/ppliteseg",
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model_handler=fd.serving.handler.VisionModelHandler,
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predictor=model_instance)
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