server2.py
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import grpc
import cv2
import numpy as np
import tensorflow as tf
from tensorflow_serving.apis import prediction_service_pb2_grpc, predict_pb2
from sanic import Sanic
from sanic.response import json
from classification import classifier
app = Sanic("async_test")
# TODO 从配置文件读取
tf_serving_settings = {
'servers': {
'server_1': {
'host': '192.168.10.191',
'port': '8500',
'options': [
('grpc.max_send_message_length', 1000 * 1024 * 1024),
('grpc.max_receive_message_length', 1000 * 1024 * 1024),
],
}
},
}
app.config.update(tf_serving_settings)
@app.post("/sync_classification")
async def sync_handler(request):
image = request.files.get("image")
img_array = np.frombuffer(image.body, np.uint8)
image = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
input_images = classifier.preprocess_input(image)
# print(type(image))
# See prediction_service.proto for gRPC request/response details.
request = predict_pb2.PredictRequest()
request.model_spec.name = classifier.model_name
request.model_spec.signature_name = classifier.signature_name
stub = getattr(app.ctx, classifier.server_name)
request.inputs['input_1'].CopyFrom(tf.make_tensor_proto(input_images))
result = stub.Predict(request, 100.0) # 100 secs timeout
outputs = tf.make_ndarray(result.outputs['output'])
res = classifier.reprocess_output(outputs)
return json(res)
# @app.get("/async")
# async def async_handler(request):
# await asyncio.sleep(2)
# return json({'code': 1})
@app.listener("before_server_start")
async def set_grpc_channel(app, loop):
for server_name, server_settings in app.config['servers'].items():
channel = grpc.insecure_channel(
'{0}:{1}'.format(server_settings['host'], server_settings['port']),
options=server_settings.get('options'))
stub = prediction_service_pb2_grpc.PredictionServiceStub(channel)
setattr(app.ctx, server_name, stub)
if __name__ == '__main__':
app.run(host='0.0.0.0', port=6699, workers=5)