# Transfer learning on yolo using keras

I am working on a project that uses object detection. I have logo images that need to be detected in a video. I am doing this in keras. I followed this blog to convert the yolo weights to a keras model.

Now I would like to train this keras model with my dataset (transfer learning). I got right dataset with xmin, ymin, xmax, and ymax.

My Approach: remove the last layer and use the sigmoid function to define the classes. However, the above link says that this keras model predicts both boundary boxes and classes. I am not sure how to achieve these boundary boxes from the model itself.

• Did you faced any issue like ValueError: If your data is in the form of symbolic tensors, you should specify the steps argument (instead of the batch_size argument, because symbolic tensors are expected to produce batches of input data) @Model.predict () – user2458922 Oct 1 '19 at 19:32