merge develop (#859)

merge develop into reg

README_cn.md

@@ -58,6 +58,7 @@
         - [车辆识别](./docs/zh_CN/application/vehicle_fine_grained_classfication.md)
         - [车辆ReID](./docs/zh_CN/application/vehicle_reid.md)
         - [logo识别](./docs/zh_CN/application/logo_recognition.md)
+        - [动漫人物识别](./docs/zh_CN/application/cartoon_character_recognition.md)
     - [向量检索](./deploy/vector_search/README.md)
 - 模型训练/评估
     - [图像分类任务](./docs/zh_CN/tutorials/getting_started.md)

docs/en/extension/VisualDL_en.md

@@ -10,7 +10,7 @@ Now PaddleClas support use VisualDL to visualize the changes of learning rate, l
 You only need to set the `vdl_dir` field in train config:
 
 ```yaml
-# confit.txt
+# config.yaml
 vdl_dir: "./vdl.log"
 ```
 
@@ -19,7 +19,7 @@ vdl_dir: "./vdl.log"
 Then normal start training:
 
 ```shell
-python3 tools/train.py -c config.txt
+python3 tools/train.py -c config.yaml
 ```
 
 ### Start VisualDL

docs/en/tutorials/getting_started_en.md

@@ -246,7 +246,7 @@ Among them, the `--model` parameter is used to specify the model name, `--pretra
 
 **Note**:
 1. If `--output_path=./inference`, then three files will be generated in the folder `inference`, they are `inference.pdiparams`, `inference.pdmodel` and `inference.pdiparams.info`.
-2. You can specify the `shape` of the model input image by setting the parameter `--img_size`, the default is `224`, which means the shape of input image is `224*224`.
+2. You can specify the `shape` of the model input image by setting the parameter `--img_size`, the default is `224`, which means the shape of input image is `224*224`. If you want to use `Transformer series models`, such as `DeiT_***_384`, `ViT_***_384`, you need to set `--img_size=384`.
 
 The above command will generate the model structure file (`inference.pdmodel`) and the model weight file (`inference.pdiparams`), and then the inference engine can be used for inference:
 

docs/zh_CN/extension/VisualDL.md

@@ -10,7 +10,7 @@ VisualDL是飞桨可视化分析工具，以丰富的图表呈现训练参数变
 在PaddleClas中使用VisualDL，只需在训练配置文件（config文件）添加如下字段：
 
 ```yaml
-# confit.txt
+# config.yaml
 vdl_dir: "./vdl.log"
 ```
 `vdl_dir` 用于指定VisualDL用于保存log信息的目录。
@@ -18,7 +18,7 @@ vdl_dir: "./vdl.log"
 然后正常启动训练即可：
 
 ```shell
-python3 tools/train.py -c config.txt
+python3 tools/train.py -c config.yaml
 ```
 
 ### 启动VisualDL

docs/zh_CN/tutorials/getting_started.md

@@ -232,6 +232,10 @@ python3 tools/export_model.py \
 
 其中，`Global.pretrained_model`用于指定模型文件路径，该路径仍无需包含模型文件后缀名（如[1.3 模型恢复训练](#1.3)）。
 
+**注意**：
+1. `--output_path`表示输出的inference模型文件夹路径，若`--output_path=./inference`，则会在`inference`文件夹下生成`inference.pdiparams`、`inference.pdmodel`和`inference.pdiparams.info`文件。
+2. 可以通过设置参数`--img_size`指定模型输入图像的`shape`，默认为`224`，表示图像尺寸为`224*224`，请根据实际情况修改；如果使用`Transformer`系列模型，如`DeiT_***_384`, `ViT_***_384`等，请注意模型的输入数据尺寸，需要设置参数`img_size=384`。
+
 
 上述命令将生成模型结构文件（`inference.pdmodel`）和模型权重文件（`inference.pdiparams`），然后可以使用预测引擎进行推理：
 
@@ -249,7 +253,7 @@ python3 python/predict_cls.py \
     -o Global.infer_imgs=../dataset/flowers102/jpg/image_00001.jpg \
     -o Global.inference_model_dir=../inference/ \
     -o PostProcess.class_id_map_file=None
-    
+
 
 其中：
 + `Global.infer_imgs`：待预测的图片文件路径。
@@ -259,4 +263,6 @@ python3 python/predict_cls.py \
 + `Global.enable_mkldnn`：是否启用`MKL-DNN`加速，默认为`False`。注意`enable_mkldnn`与`use_gpu`同时为`True`时，将忽略`enable_mkldnn`，而使用GPU运行。
 + `Global.use_fp16`：是否启用`FP16`，默认为`False`。
 
+**注意**: 如果使用`Transformer`系列模型，如`DeiT_***_384`, `ViT_***_384`等，请注意模型的输入数据尺寸，需要设置参数`resize_short=384`, `resize=384`。
+
 * 如果你希望提升评测模型速度，使用gpu评测时，建议开启TensorRT加速预测，使用cpu评测时，建议开启MKL-DNN加速预测。

paddleclas.py

@@ -160,10 +160,15 @@ class ModelNameError(Exception):
 
 def print_info():
     table = PrettyTable(['Series', 'Name'])
+    try:
+        sz = os.get_terminal_size()
+        width = sz.columns - 30 if sz.columns > 50 else 10
+    except OSError:
+        width = 100
     for series in model_series:
-        names = textwrap.fill("  ".join(model_series[series]), width=100)
+        names = textwrap.fill("  ".join(model_series[series]), width=width)
         table.add_row([series, names])
-    print('Inference models that Paddle provides are listed as follows:')
+    print('Inference models that PaddleClas provides are listed as follows:')
     print(table)
 
 

tools/__init__.py

@@ -0,0 +1,15 @@
+# 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 . import infer

tools/infer/__init__.py

@@ -0,0 +1,16 @@
+# 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 .predict import Predictor
+from .utils import parse_args, create_paddle_predictor, preprocess, postprocess, get_image_list, get_image_list_from_label_file, calc_topk_acc, save_prelabel_results, b64_to_np, np_to_b64