refine pedestrian_yolov3_darknet.yml and vehicle_yolov3_darknet.yml in contrib (#324)

contrib/PedestrianDetection/pedestrian_yolov3_darknet.yml

 architecture: YOLOv3
-train_feed: YoloTrainFeed
-eval_feed: YoloEvalFeed
-test_feed: YoloTestFeed
 use_gpu: true
 max_iters: 200000
 log_smooth_window: 20
@@ -11,6 +8,7 @@ metric: COCO
 pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar
 weights: https://paddlemodels.bj.bcebos.com/object_detection/pedestrian_yolov3_darknet.tar
 num_classes: 1
+use_fine_grained_loss: false
 
 YOLOv3:
   backbone: DarkNet
@@ -27,8 +25,7 @@ YOLOv3Head:
             [30, 61], [62, 45], [59, 119],
             [116, 90], [156, 198], [373, 326]]
   norm_decay: 0.
-  ignore_thresh: 0.7
-  label_smooth: true
+  yolo_loss: YOLOv3Loss
   nms:
     background_label: -1
     keep_top_k: 100
@@ -37,6 +34,11 @@ YOLOv3Head:
     normalized: false
     score_threshold: 0.01
 
+YOLOv3Loss:
+  batch_size: 8
+  ignore_thresh: 0.7
+  label_smooth: false
+
 LearningRate:
   base_lr: 0.001
   schedulers:
@@ -57,26 +59,28 @@ OptimizerBuilder:
     factor: 0.0005
     type: L2
 
-YoloTrainFeed:
+_READER_: '../../configs/yolov3_reader.yml'
+TrainReader:
   batch_size: 8
   dataset:
+    !COCODataSet
       dataset_dir: dataset/pedestrian
-    annotation: annotations/instances_train2017.json
+      anno_path: annotations/instances_train2017.json
       image_dir: train2017
-  num_workers: 8
-  bufsize: 128
-  use_process: true
+      with_background: false
 
-YoloEvalFeed:
+EvalReader:
   batch_size: 8
-  image_shape: [3, 608, 608]
   dataset:
+    !COCODataSet
       dataset_dir: dataset/pedestrian
-    annotation: annotations/instances_val2017.json
+      anno_path: annotations/instances_val2017.json
       image_dir: val2017
+      with_background: false
 
-YoloTestFeed:
+TestReader:
   batch_size: 1
-  image_shape: [3, 608, 608]
   dataset:
-    annotation: contrib/PedestrianDetection/pedestrian.json
+    !ImageFolder
+      anno_path: contrib/PedestrianDetection/pedestrian.json
+      with_background: false

contrib/VehicleDetection/vehicle_yolov3_darknet.yml

 architecture: YOLOv3
-train_feed: YoloTrainFeed
-eval_feed: YoloEvalFeed
-test_feed: YoloTestFeed
 use_gpu: true
 max_iters: 120000
 log_smooth_window: 20
@@ -27,8 +24,7 @@ YOLOv3Head:
             [23, 33], [40, 25], [54, 50],
             [101, 80], [139, 145], [253, 224]]
   norm_decay: 0.
-  ignore_thresh: 0.7
-  label_smooth: false
+  yolo_loss: YOLOv3Loss
   nms:
     background_label: -1
     keep_top_k: 100
@@ -37,6 +33,11 @@ YOLOv3Head:
     normalized: false
     score_threshold: 0.005
 
+YOLOv3Loss:
+  batch_size: 8
+  ignore_thresh: 0.7
+  label_smooth: false
+
 LearningRate:
   base_lr: 0.001
   schedulers:
@@ -57,26 +58,28 @@ OptimizerBuilder:
     factor: 0.0005
     type: L2
 
-YoloTrainFeed:
+_READER_: '../../configs/yolov3_reader.yml'
+TrainReader:
   batch_size: 8
   dataset:
+    !COCODataSet
       dataset_dir: dataset/vehicle
-    annotation: annotations/instances_train2017.json
+      anno_path: annotations/instances_train2017.json
       image_dir: train2017
-  num_workers: 8
-  bufsize: 128
-  use_process: true
+      with_background: false
 
-YoloEvalFeed:
+EvalReader:
   batch_size: 8
-  image_shape: [3, 608, 608]
   dataset:
+    !COCODataSet
       dataset_dir: dataset/vehicle
-    annotation: annotations/instances_val2017.json
+      anno_path: annotations/instances_val2017.json
       image_dir: val2017
+      with_background: false
 
-YoloTestFeed:
+TestReader:
   batch_size: 1
-  image_shape: [3, 608, 608]
   dataset:
-    annotation: contrib/VehicleDetection/vehicle.json
+    !ImageFolder
+      anno_path: contrib/VehicleDetection/vehicle.json
+      with_background: false