提交 c9780d95 编写于 作者: M MRXLT

fix demo for py3

上级 2bae7c40
......@@ -17,10 +17,16 @@ import base64
import json
import time
import os
import sys
py_version = sys.version_info[0]
def predict(image_path, server):
image = base64.b64encode(open(image_path).read())
if py_version == 2:
image = base64.b64encode(open(image_path).read())
else:
image = base64.b64encode(open(image_path, "rb").read()).decode("utf-8")
req = json.dumps({"image": image, "fetch": ["score"]})
r = requests.post(
server, data=req, headers={"Content-Type": "application/json"})
......@@ -28,15 +34,6 @@ def predict(image_path, server):
return r
def batch_predict(image_path, server):
image = base64.b64encode(open(image_path).read())
req = json.dumps({"image": [image, image], "fetch": ["score"]})
r = requests.post(
server, data=req, headers={"Content-Type": "application/json"})
print(r.json()["result"][1]["score"][0])
return r
if __name__ == "__main__":
server = "http://127.0.0.1:9393/image/prediction"
image_list = os.listdir("./image_data/n01440764/")
......
......@@ -19,16 +19,15 @@ import time
client = Client()
client.load_client_config(sys.argv[1])
client.connect(["127.0.0.1:9295"])
client.connect(["127.0.0.1:9393"])
reader = ImageReader()
start = time.time()
for i in range(1000):
with open("./data/n01440764_10026.JPEG") as f:
with open("./data/n01440764_10026.JPEG", "rb") as f:
img = f.read()
img = reader.process_image(img).reshape(-1)
fetch_map = client.predict(feed={"image": img}, fetch=["score"])
print(i)
end = time.time()
print(end - start)
......
......@@ -19,15 +19,23 @@ import paddle
import re
import paddle.fluid.incubate.data_generator as dg
py_version = sys.version_info[0]
class IMDBDataset(dg.MultiSlotDataGenerator):
def load_resource(self, dictfile):
self._vocab = {}
wid = 0
with open(dictfile) as f:
for line in f:
self._vocab[line.strip()] = wid
wid += 1
if py_version == 2:
with open(dictfile) as f:
for line in f:
self._vocab[line.strip()] = wid
wid += 1
else:
with open(dictfile, encoding="utf-8") as f:
for line in f:
self._vocab[line.strip()] = wid
wid += 1
self._unk_id = len(self._vocab)
self._pattern = re.compile(r'(;|,|\.|\?|!|\s|\(|\))')
self.return_value = ("words", [1, 2, 3, 4, 5, 6]), ("label", [0])
......
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