minor modifications

Author: wizyoung

model.py

@@ -215,7 +215,6 @@ def loss_layer(self, feature_map_i, y_true, anchors):
         best_iou = tf.reduce_max(iou, axis=-1)
 
         # get_ignore_mask
-        # TODO: some explainments
         ignore_mask = tf.cast(best_iou < 0.5, tf.float32)
         # shape: [N, 13, 13, 3, 1]
         ignore_mask = tf.expand_dims(ignore_mask, -1)
@@ -321,8 +320,3 @@ def broadcast_iou(self, true_box_xy, true_box_wh, pred_box_xy, pred_box_wh):
         iou = intersect_area / (pred_box_area + true_box_area - intersect_area)
 
         return iou
-
-
-
-
-

utils/data_utils.py

@@ -15,7 +15,6 @@ def parse_line(line):
             dimension are [x_min, y_min, x_max, y_max]
     '''
     s = line.strip().split(' ')
-    # TODO: need reform
     pic_path = s[0]
     s = s[1:]
     box_cnt = len(s) / 5
@@ -75,7 +74,6 @@ def process_box(boxes, labels, img_size, class_num, anchors):
     # (width, height)
     box_sizes = boxes[:, 2:4] - boxes[:, 0:2]
 
-    # TODO: NUM_CLASS, IMAGE_SHAPE
     # [13, 13, 3, 3+num_class]
     y_true_13 = np.zeros((img_size[1] / 32, img_size[0] / 32, 3, 5 + class_num), np.float32)
     y_true_26 = np.zeros((img_size[1] / 16, img_size[0] / 16, 3, 5 + class_num), np.float32)

utils/nms_utils.py

@@ -63,7 +63,6 @@ def py_nms(boxes, scores, max_boxes=50, iou_thresh=0.5):
     x2 = boxes[:, 2]
     y2 = boxes[:, 3]
 
-    #TODO: +1?
     areas = (x2 - x1) * (y2 - y1)
     order = scores.argsort()[::-1]