modify locustfile

@@ -28,7 +28,7 @@ class F3Classification:
 
 
         res = {
         res = {
             'label': label,
             'label': label,
-            'confidence': confidence
+            'confidence': float(confidence)
         }
         }
         return res
         return res
 
 

@@ -14,3 +14,10 @@ class QuickstartUser(HttpUser):
     @task
     @task
     def async_test(self):
     def async_test(self):
         self.client.get("/async")
         self.client.get("/async")
+
+    @tag('sync_classification')
+    @task
+    def sync_classification(self):
+        img_path = '/home/lk/MyProject/BMW_F3OCR/数据集/文件分类/营业执照/授信资料-43.jpg'
+        files=[('image', ('', open(img_path,'rb'), ''))]
+        self.client.post("/sync_classification", files=files)

-import grpc
+import os
 import cv2
 import cv2
+import grpc
 import numpy as np
 import numpy as np
 import tensorflow as tf
 import tensorflow as tf
 from tensorflow_serving.apis import prediction_service_pb2_grpc, predict_pb2
 from tensorflow_serving.apis import prediction_service_pb2_grpc, predict_pb2
@@ -8,6 +9,7 @@ from sanic import Sanic
 from sanic.response import json
 from sanic.response import json
 
 
 from classification import classifier
 from classification import classifier
+os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
 
 
 app = Sanic("async_test")
 app = Sanic("async_test")
 
 
@@ -15,7 +17,7 @@ app = Sanic("async_test")
 tf_serving_settings = {
 tf_serving_settings = {
     'servers': {
     'servers': {
         'server_1': {
         'server_1': {
-            'host': '192.168.10.191',
+            'host': 'localhost',
             'port': '8500',
             'port': '8500',
             'options': [
             'options': [
                 ('grpc.max_send_message_length', 1000 * 1024 * 1024),
                 ('grpc.max_send_message_length', 1000 * 1024 * 1024),
@@ -40,7 +42,7 @@ async def sync_handler(request):
     request = predict_pb2.PredictRequest()
     request = predict_pb2.PredictRequest()
     request.model_spec.name = classifier.model_name
     request.model_spec.name = classifier.model_name
     request.model_spec.signature_name = classifier.signature_name
     request.model_spec.signature_name = classifier.signature_name
-    stub = getattr(app.ctx, classifier.server_name)
+    stub = getattr(app, classifier.server_name)
 
 
     request.inputs['input_1'].CopyFrom(tf.make_tensor_proto(input_images))
     request.inputs['input_1'].CopyFrom(tf.make_tensor_proto(input_images))
     result = stub.Predict(request, 100.0)  # 100 secs timeout
     result = stub.Predict(request, 100.0)  # 100 secs timeout
@@ -63,7 +65,7 @@ async def set_grpc_channel(app, loop):
             '{0}:{1}'.format(server_settings['host'], server_settings['port']),
             '{0}:{1}'.format(server_settings['host'], server_settings['port']),
             options=server_settings.get('options'))
             options=server_settings.get('options'))
         stub = prediction_service_pb2_grpc.PredictionServiceStub(channel)
         stub = prediction_service_pb2_grpc.PredictionServiceStub(channel)
-        setattr(app.ctx, server_name, stub)
+        setattr(app, server_name, stub)
 
 
 
 
 if __name__ == '__main__':
 if __name__ == '__main__':