Update doc.

fluid/object_detection/README.md

@@ -14,60 +14,87 @@ You can use [PASCAL VOC dataset](http://host.robots.ox.ac.uk/pascal/VOC/) or [MS
 
 #### PASCAL VOC Dataset
 
-Download the PASCAL VOC dataset, skip this step if you already have one.
+If you want to train model on PASCAL VOC dataset, please download datset at first, skip this step if you already have one.
 
 ```bash
-cd data/
-# Download the data.
-wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar
-wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar
-wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtest_06-Nov-2007.tar
-# Extract the data.
-tar -xvf VOCtrainval_11-May-2012.tar
-tar -xvf VOCtrainval_06-Nov-2007.tar
-tar -xvf VOCtest_06-Nov-2007.tar
+cd data/pascalvoc
+./download.sh
 ```
+
+The command `download.sh` also will create training and testing file lists.
+
 #### MS-COCO Dataset
 
+If you want to train model on MS-COCO dataset, please download datset at first, skip this step if you already have one.
+
 ```
+cd data/coco
+./download.sh
 ```
+
 ### Train
 
-1. Train on one device (/GPU).
+#### Download the Pre-trained Model.
 
-```python
-env CUDA_VISIABLE_DEVICES=0 python train.py \
-    --paralle=Fale \
-    --batch_size=32 --use_gpu=Ture --data='voc'
-```
+We provide two pre-trained models. The one is MobileNet-v1 SSD trained on COCO dataset, but removed the convolutional predictors for COCO dataset. This model can be used to initialize the models when training other dataset, like PASCAL VOC. Then other pre-trained model is MobileNet v1 trained on ImageNet 2012 dataset, but removed the last weights and bias in Fully-Connected layer.
 
-2. Train on multi devices (GPU).
+Declaration: the MobileNet-v1 SSD model is converted by [TensorFlow model](https://github.com/tensorflow/models/blob/f87a58cd96d45de73c9a8330a06b2ab56749a7fa/research/object_detection/g3doc/detection_model_zoo.md). The MobileNet v1 model is converted [Caffe](https://github.com/shicai/MobileNet-Caffe).
 
-```python
-env CUDA_VISIABLE_DEVICES=0,1,2,3 python train.py \
-    --paralle=Ture --batch_size=64 \
-    --use_gpu=Ture --data='voc'
-```
+  - Download MobileNet-v1 SSD:
+    ```
+    ./pretrained/download_coco.sh
+    ```
+  - Download MobileNet-v1:
+    ```
+    ./pretrained/download_imagenet.sh
+    ```
+
+#### Train on PASCAL VOC
+  - Train on one device (/GPU).
+  ```python
+  env CUDA_VISIABLE_DEVICES=0 python -u train.py --parallel=False --data='pascalvoc' --pretrained_model='pretrained/ssd_mobilenet_v1_coco/'
+  ```
+  - Train on multi devices (/GPUs).
+
+  ```python
+  env CUDA_VISIABLE_DEVICES=0,1 python -u train.py --batch_size=64 --data='pascalvoc' --pretrained_model='pretrained/ssd_mobilenet_v1_coco/'
+  ```
+
+#### Train on MS-COCO
+  - Train on one device (/GPU).
+  ```python
+  env CUDA_VISIABLE_DEVICES=0 python -u train.py --parallel=False --data='coco' --pretrained_model='pretrained/mobilenet_imagenet/'
+  ```
+  - Train on multi devices (/GPUs).
+  ```python
+  env CUDA_VISIABLE_DEVICES=0,1 python -u train.py --batch_size=64 --data='coco' --pretrained_model='pretrained/mobilenet_imagenet/'
+  ```
+
+TBD
 
 ### Evaluate
 
 ```python
-env CUDA_VISIABLE_DEVICES=0,1,2,3 python eval.py \
-    --paralle=Ture --batch_size=64 --use_gpu=Ture \
-    --data='voc' --model='model/90'
+env CUDA_VISIABLE_DEVICES=0 python eval.py --model='model/90' --test_list=''
 ```
 
+TBD
+
 ### Infer and Visualize
+
 ```python
-env CUDA_VISIABLE_DEVICES=0 python infer.py \
-    --paralle=False --batch_size=2 \
-    --use_gpu=Ture --model='model/90'
+env CUDA_VISIABLE_DEVICES=0 python infer.py --batch_size=2 --model='model/90' --test_list=''
 ```
+
+TBD
+
 ### Released Model
 
 
-| Model                 | Pre-trained Model  | Training data    | Test data    | mAP |
-|:---------------------:|:------------------:|:----------------:|:------------:|:----:|
-|MobileNet-SSD 300x300  | COCO MobileNet SSD | VOC07+12 trainval| VOC07 test   | xx%  |
-|MobileNet-SSD 300x300  | ImageNet MobileNet | VOC07+12 trainval| VOC07 test   | xx%  |
-|MobileNet-SSD 300x300  | ImageNet MobileNet | MS-COCO trainval | MS-COCO test | xx%  |
+| Model                    | Pre-trained Model  | Training data    | Test data    | mAP |
+|:------------------------:|:------------------:|:----------------:|:------------:|:----:|
+|MobileNet-v1-SSD 300x300  | COCO MobileNet SSD | VOC07+12 trainval| VOC07 test   | xx%  |
+|MobileNet-v1-SSD 300x300  | ImageNet MobileNet | VOC07+12 trainval| VOC07 test   | xx%  |
+|MobileNet-v1-SSD 300x300  | ImageNet MobileNet | MS-COCO trainval | MS-COCO test | xx%  |
+
+TBD