Fixed YOLOv3-tiny version to use minimal anchor boxes in anchor files. qqwweee#503

Author: tfukumori

yolo3/model.py

@@ -193,7 +193,7 @@ def yolo_eval(yolo_outputs,
               iou_threshold=.5):
     """Evaluate YOLO model on given input and return filtered boxes."""
     num_layers = len(yolo_outputs)
-    anchor_mask = [[6,7,8], [3,4,5], [0,1,2]] if num_layers==3 else [[3,4,5], [1,2,3]] # default setting
+    anchor_mask = [[6,7,8], [3,4,5], [0,1,2]] if num_layers==3 else [[3,4,5], [0,1,2]] # default setting
     input_shape = K.shape(yolo_outputs[0])[1:3] * 32
     boxes = []
     box_scores = []
@@ -247,7 +247,7 @@ def preprocess_true_boxes(true_boxes, input_shape, anchors, num_classes):
     '''
     assert (true_boxes[..., 4]<num_classes).all(), 'class id must be less than num_classes'
     num_layers = len(anchors)//3 # default setting
-    anchor_mask = [[6,7,8], [3,4,5], [0,1,2]] if num_layers==3 else [[3,4,5], [1,2,3]]
+    anchor_mask = [[6,7,8], [3,4,5], [0,1,2]] if num_layers==3 else [[3,4,5], [0,1,2]]
 
     true_boxes = np.array(true_boxes, dtype='float32')
     input_shape = np.array(input_shape, dtype='int32')
@@ -361,7 +361,7 @@ def yolo_loss(args, anchors, num_classes, ignore_thresh=.5, print_loss=False):
     num_layers = len(anchors)//3 # default setting
     yolo_outputs = args[:num_layers]
     y_true = args[num_layers:]
-    anchor_mask = [[6,7,8], [3,4,5], [0,1,2]] if num_layers==3 else [[3,4,5], [1,2,3]]
+    anchor_mask = [[6,7,8], [3,4,5], [0,1,2]] if num_layers==3 else [[3,4,5], [0,1,2]]
     input_shape = K.cast(K.shape(yolo_outputs[0])[1:3] * 32, K.dtype(y_true[0]))
     grid_shapes = [K.cast(K.shape(yolo_outputs[l])[1:3], K.dtype(y_true[0])) for l in range(num_layers)]
     loss = 0