fix feed list in inference (#1789)

fluid/PaddleCV/rcnn/eval_coco_map.py

@@ -55,7 +55,7 @@ def eval():
         add_conv_body_func=resnet.add_ResNet50_conv4_body,
         add_roi_box_head_func=resnet.add_ResNet_roi_conv5_head,
         use_pyreader=False,
-        is_train=False)
+        mode='val')
     model.build_model(image_shape)
     pred_boxes = model.eval_bbox_out()
     if cfg.MASK_ON:

fluid/PaddleCV/rcnn/infer.py

@@ -35,7 +35,7 @@ def infer():
         add_conv_body_func=resnet.add_ResNet50_conv4_body,
         add_roi_box_head_func=resnet.add_ResNet_roi_conv5_head,
         use_pyreader=False,
-        is_train=False)
+        mode='infer')
     model.build_model(image_shape)
     pred_boxes = model.eval_bbox_out()
     if cfg.MASK_ON:

fluid/PaddleCV/rcnn/models/model_builder.py

@@ -25,12 +25,12 @@ class RCNN(object):
     def __init__(self,
                  add_conv_body_func=None,
                  add_roi_box_head_func=None,
-                 is_train=True,
+                 mode='train',
                  use_pyreader=True,
                  use_random=True):
         self.add_conv_body_func = add_conv_body_func
         self.add_roi_box_head_func = add_roi_box_head_func
-        self.is_train = is_train
+        self.mode = mode
         self.use_pyreader = use_pyreader
         self.use_random = use_random
 
@@ -41,7 +41,7 @@ class RCNN(object):
         self.rpn_heads(body_conv)
         # Fast RCNN
         self.fast_rcnn_heads(body_conv)
-        if not self.is_train:
+        if self.mode != 'train':
             self.eval_bbox()
         # Mask RCNN
         if cfg.MASK_ON:
@@ -115,7 +115,9 @@ class RCNN(object):
                     name='gt_masks', shape=[2], dtype='float32', lod_level=3)
 
     def feeds(self):
-        if not self.is_train:
+        if self.mode == 'infer':
+            return [self.image, self.im_info]
+        if self.mode == 'val':
             return [self.image, self.im_info, self.im_id]
         if not cfg.MASK_ON:
             return [
@@ -213,7 +215,7 @@ class RCNN(object):
         rpn_cls_score_prob = fluid.layers.sigmoid(
             self.rpn_cls_score, name='rpn_cls_score_prob')
 
-        param_obj = cfg.TRAIN if self.is_train else cfg.TEST
+        param_obj = cfg.TRAIN if self.mode == 'train' else cfg.TEST
         pre_nms_top_n = param_obj.rpn_pre_nms_top_n
         post_nms_top_n = param_obj.rpn_post_nms_top_n
         nms_thresh = param_obj.rpn_nms_thresh
@@ -230,7 +232,7 @@ class RCNN(object):
             nms_thresh=nms_thresh,
             min_size=min_size,
             eta=eta)
-        if self.is_train:
+        if self.mode == 'train':
             outs = fluid.layers.generate_proposal_labels(
                 rpn_rois=self.rpn_rois,
                 gt_classes=self.gt_label,
@@ -267,7 +269,7 @@ class RCNN(object):
                 self.mask_int32 = mask_out[2]
 
     def fast_rcnn_heads(self, roi_input):
-        if self.is_train:
+        if self.mode == 'train':
             pool_rois = self.rois
         else:
             pool_rois = self.rpn_rois
@@ -311,7 +313,7 @@ class RCNN(object):
             bias_attr=ParamAttr(
                 name='conv5_mask_b', learning_rate=2., regularizer=L2Decay(0.)))
         act_func = None
-        if not self.is_train:
+        if self.mode != 'train':
             act_func = 'sigmoid'
         mask_fcn_logits = fluid.layers.conv2d(
             input=mask_out,
@@ -325,13 +327,13 @@ class RCNN(object):
                 learning_rate=2.,
                 regularizer=L2Decay(0.)))
 
-        if not self.is_train:
+        if self.mode != 'train':
             mask_fcn_logits = fluid.layers.lod_reset(mask_fcn_logits,
                                                      self.pred_result)
         return mask_fcn_logits
 
     def mask_rcnn_heads(self, mask_input):
-        if self.is_train:
+        if self.mode == 'train':
             conv5 = fluid.layers.gather(self.res5_2_sum,
                                         self.roi_has_mask_int32)
             self.mask_fcn_logits = self.SuffixNet(conv5)

fluid/PaddleCV/rcnn/reader.py

@@ -36,7 +36,9 @@ def roidb_reader(roidb, mode):
     im_height = np.round(roidb['height'] * im_scales)
     im_width = np.round(roidb['width'] * im_scales)
     im_info = np.array([im_height, im_width, im_scales], dtype=np.float32)
-    if mode == 'val' or mode == 'infer':
+    if mode == 'infer':
+        return im, im_info
+    if mode == 'val':
         return im, im_info, im_id
 
     gt_boxes = roidb['gt_boxes'].astype('float32')
@@ -162,8 +164,8 @@ def coco(mode,
             for roidb in roidbs:
                 if cfg.image_name not in roidb['image']:
                     continue
-                im, im_info, im_id = roidb_reader(roidb, mode)
-                batch_out = [(im, im_info, im_id)]
+                im, im_info = roidb_reader(roidb, mode)
+                batch_out = [(im, im_info)]
                 yield batch_out
 
     return reader