Merge pull request #238 from MRXLT/general-server-imagenet

add imagenet demo

python/examples/imagenet/README.md

+## 图像分类示例
+
+示例中采用ResNet50_vd模型执行imagenet 1000分类任务。
+
+### 模型及配置文件获取
+```
+sh get_model.sh
+```
+### 执行wb service预测服务
+
+启动server端
+```
+python image_classification_service.py conf_and_model/serving_server_model workdir 9393
+```
+
+client端进行预测
+```
+python image_http_client.py
+```
+### 执行rpc service预测服务
+
+启动server端
+```
+python image_server.py conf_and_model/serving_server_model workdir 9393
+```
+
+client端进行预测
+```
+python image_rpc_client.py conf_and_model/serving_client_conf/serving_client_conf.prototxt
+```
+*server端示例中服务端口为9393端口，client端示例中数据来自./data文件夹，server端地址为本地9393端口，可根据实际情况更改脚本。*

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

+# 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 requests
+import base64
+import json
+
+
+def predict(image_path, server):
+    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__":
+    server = "http://127.0.0.1:9393/image/prediction"
+    image_path = "./data/n01440764_10026.JPEG"
+    predict(image_path, server)

python/examples/imagenet/image_reader.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 cv2
+import numpy as np
+
+
+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]
+        self.resize_short_size = 256
+        self.interpolation = None
+
+    def resize_short(self, img, target_size, interpolation=None):
+        """resize image
+
+        Args:
+            img: image data
+            target_size: resize short target size
+            interpolation: interpolation mode
+
+        Returns:
+            resized image data
+        """
+        percent = float(target_size) / min(img.shape[0], img.shape[1])
+        resized_width = int(round(img.shape[1] * percent))
+        resized_height = int(round(img.shape[0] * percent))
+        if interpolation:
+            resized = cv2.resize(
+                img, (resized_width, resized_height),
+                interpolation=interpolation)
+        else:
+            resized = cv2.resize(img, (resized_width, resized_height))
+        return resized
+
+    def crop_image(self, img, target_size, center):
+        """crop image
+
+        Args:
+            img: images data
+            target_size: crop target size
+            center: crop mode
+
+        Returns:
+            img: cropped image data
+        """
+        height, width = img.shape[:2]
+        size = target_size
+        if center == True:
+            w_start = (width - size) // 2
+            h_start = (height - size) // 2
+        else:
+            w_start = np.random.randint(0, width - size + 1)
+            h_start = np.random.randint(0, height - size + 1)
+        w_end = w_start + size
+        h_end = h_start + size
+        img = img[h_start:h_end, w_start:w_end, :]
+        return img
+
+    def process_image(self, sample):
+        """ process_image """
+        mean = self.image_mean
+        std = self.image_std
+        crop_size = self.image_shape[1]
+
+        data = np.fromstring(sample, np.uint8)
+        img = cv2.imdecode(data, cv2.IMREAD_COLOR)
+
+        if img is None:
+            print("img is None, pass it.")
+            return None
+
+        if crop_size > 0:
+            target_size = self.resize_short_size
+            img = self.resize_short(
+                img, target_size, interpolation=self.interpolation)
+            img = self.crop_image(img, target_size=crop_size, center=True)
+
+        img = img[:, :, ::-1]
+
+        img = img.astype('float32').transpose((2, 0, 1)) / 255
+        img_mean = np.array(mean).reshape((3, 1, 1))
+        img_std = np.array(std).reshape((3, 1, 1))
+        img -= img_mean
+        img /= img_std
+        return img

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"])