CNN Face Detection with tensor as input

I am generating some face images using Conv2DTranspose. I'd like to output the 68 landmarks as the final output rather than the generated image. So, I used lambda layer to define my custom function. However, cnn_face_detection_model_v1 says it only accepts either list or array and not tensors. How Can I bring cnn_face_detection_model_v1 into my custom function? Here's the full error description:

TypeError: __call__(): incompatible function arguments. The following argument types are supported:
1. (self: dlib.cnn_face_detection_model_v1, imgs: list, upsample_num_times: int=0, batch_size: int=128) -> std::vector >,std::allocator > > >
2. (self: dlib.cnn_face_detection_model_v1, img: array, upsample_num_times: int=0) -> std::vector >

Invoked with: , , 1

Did you forget to `#include `? Or ,
, , etc. Some automatic
conversions are optional and require extra headers to be included
when compiling your pybind11 module.