add ssd demo

demo/ssd/README.md

@@ -27,18 +27,18 @@ $ pip install --upgrade paddlepaddle
 
 ## 命令行方式预测
 
-`infer.sh`给出了使用命令行调用Module预测的示例脚本
+`cli_demo.sh`给出了使用命令行调用Module预测的示例脚本
 通过以下命令试验下效果
 
 ```shell
-$ sh infer.sh
+$ sh cli_demo.sh
 ```
 
 ## 通过python API预测
 
-`infer_by_code.py`给出了使用python API调用Module预测的示例代码
+`ssd_demo.py`给出了使用python API调用Module预测的示例代码
 通过以下命令试验下效果
 
 ```shell
-python infer_by_code.py
+python ssd_demo.py
 ```

demo/ssd/infer_by_code.py → demo/ssd/ssd_demo.py

 import os
 import paddlehub as hub
 
-
-def infer_with_input_path():
-    # get ssd module
+if __name__ == "__main__":
     ssd = hub.Module(name="ssd_mobilenet_v1_pascal")
 
     test_img_path = os.path.join("test", "test_img_bird.jpg")
@@ -19,26 +17,3 @@ def infer_with_input_path():
     results = ssd.object_detection(data=input_dict)
     for result in results:
         hub.logger.info(result)
-
-
-def infer_with_input_file():
-    # get ssd module
-    ssd = hub.Module(name="ssd_mobilenet_v1_pascal")
-
-    # get the input keys for signature 'object_detection'
-    data_format = ssd.processor.data_format(sign_name='object_detection')
-    key = list(data_format.keys())[0]
-
-    # parse input file
-    test_file = os.path.join("test", "test.txt")
-    test_images = hub.io.parser.txt_parser.parse(test_file)
-
-    # set input dict
-    input_dict = {key: test_images}
-    results = ssd.object_detection(data=input_dict)
-    for result in results:
-        hub.logger.info(result)
-
-
-if __name__ == "__main__":
-    infer_with_input_file()

demo/text-classification/run_classifier.sh

@@ -10,7 +10,7 @@ CKPT_DIR="./ckpt_${DATASET}"
 
 python -u text_classifier.py \
                    --batch_size=24 \
-                   --use_gpu=True \
+                   --use_gpu=False \
                    --dataset=${DATASET} \
                    --checkpoint_dir=${CKPT_DIR} \
                    --learning_rate=5e-5 \