add rpc service

python/examples/imagenet/READEMR.md

+# Image Classification Service
+
+model : ResNet50_vd
+
+
+## Prepare model
+
+```
+sh get_model.sh
+```
+
+## Start web service
+```
+python image_classification_service.py serving_server_model/ workdir/ 9393
+```
+
+## Prediction 
+```
+python image_http_client.py
+```
+
+## Start rpc service
+
+```
+python image_server.py serving_server_model/ 9393
+```
+
+## Prediction
+```
+python image_rpc_client.py serving_client_conf/serving_client_conf.prototxt
+```

python/examples/imagenet/get_model.sh

+wget https://paddle-serving.bj.bcebos.com/imagenet-example/conf_and_model.tar.gz
+tar -xzvf conf_and_model.tar.gz

python/examples/imagenet/image_classification_service.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from paddle_serving_server.web_service import WebService
+import sys
+import cv2
+import base64
+import numpy as np
+from image_reader import ImageReader
+
+
+class ImageService(WebService):
+    def preprocess(self, feed={}, fetch=[]):
+        reader = ImageReader()
+        if "image" not in feed:
+            raise ("feed data error!")
+        sample = base64.b64decode(feed["image"])
+        img = reader.process_image(sample)
+        res_feed = {}
+        res_feed["image"] = img.reshape(-1)
+        return res_feed, fetch
+
+
+image_service = ImageService(name="image")
+image_service.load_model_config(sys.argv[1])
+image_service.prepare_server(
+    workdir=sys.argv[2], port=int(sys.argv[3]), device="cpu")
+image_service.run_server()

python/examples/imagenet/image_http_client.py

@@ -14,32 +14,15 @@
 
 import requests
 import base64
-import sys
-import cv2
 import json
-import os
-import numpy as np
 
 
 def predict(image_path, server):
-    image = open(image_path).read()
-    image = base64.b64encode(image)
-
-    req = {}
-    req["image"] = image
-    req["fetch"] = ["score"]
-
-    req = json.dumps(req)
-    url = server
-    headers = {"Content-Type": "application/json"}
-    r = requests.post(url, data=req, headers=headers)
-    if r.status_code == requests.codes.ok:
-        score = r.json()["score"]
-        score = np.array(score)
-        print("picture {} max score : {} class {}".format(
-            image_path, np.max(score), np.argmax(score)))
-    else:
-        print("predict {} error".format(image_path))
+    image = base64.b64encode(open(image_path).read())
+    req = json.dumps({"image": image, "fetch": ["score"]})
+    r = requests.post(
+        server, data=req, headers={"Content-Type": "application/json"})
+    print(r.json()["score"])
 
 
 if __name__ == "__main__":

python/examples/imagenet/image_classifcation_service.py → python/examples/imagenet/image_reader.py

@@ -12,15 +12,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from paddle_serving_server.web_service import WebService
-import sys
 import cv2
-import base64
 import numpy as np
 
 
-class ImageService(WebService):
-    def set_param(self):
+class ImageReader():
+    def __init__(self):
         self.image_mean = [0.485, 0.456, 0.406]
         self.image_std = [0.229, 0.224, 0.225]
         self.image_shape = [3, 224, 224]
@@ -100,19 +97,3 @@ class ImageService(WebService):
         img -= img_mean
         img /= img_std
         return img
-
-    def preprocess(self, feed={}, fetch=[]):
-        self.set_param()
-        if "image" not in feed:
-            raise ("feed data error!")
-        sample = base64.b64decode(feed["image"])
-        img = self.process_image(sample)
-        res_feed = {}
-        res_feed["image"] = img.reshape(-1)
-        return res_feed, fetch
-
-
-image_service = ImageService(name="image")
-image_service.load_model_config(sys.argv[1])
-image_service.prepare_server(workdir=sys.argv[2], port=9393, device="cpu")
-image_service.run_server()

python/examples/imagenet/image_rpc_client.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import sys
+from image_reader import ImageReader
+from paddle_serving_client import Client
+
+client = Client()
+client.load_client_config(sys.argv[1])
+client.connect(["127.0.0.1:9393"])
+reader = ImageReader()
+with open("./data/n01440764_10026.JPEG") as f:
+    img = f.read()
+
+img = reader.process_image(img).reshape(-1)
+fetch_map = client.predict(feed={"image": img}, fetch=["score"])
+
+print(fetch_map["score"])