How can I train custom datasets?

[blackCmd]

Thanks for your repo. It's amazing work.

I want to train custom dataset. How can I do?

[shashank-s-adsule]

hi i wanted to train this model on an custom dataset of 2835 image [FDDB dataset] for Face Detection.

how can i do so also i have some querys:

1. how create custom dataset .pkl file for this model
2. when analyzed the **wiferface.pkl** file provided on the README the meta data i got:
   1. data -> dict()
      1. keys: index [0...56922]
      2. values: -> list 
         1.  pos 0: image_buffer (N*1 array-> shape=>(vary,1))
         2.  pos 1: flag [0: -ve image, 1: +ve image]
         3.  pos 2: bbox [N*4 => number of bound  boxes] 
    so i want to know how to create image_buffer if i have got an image of np.array() from cv2

if possible please guide me through this part

[shashank-s-adsule]

hi i wanted to train this model on an custom dataset of 2835 image [FDDB dataset] for Face Detection.

how can i do so also i have some querys:

1. how create custom dataset .pkl file for this model
2. when analyzed the **wiferface.pkl** file provided on the README the meta data i got:
   1. data -> dict()
      1. keys: index [0...56922]
      2. values: -> list 
         1.  pos 0: image_buffer (N*1 array-> shape=>(vary,1))
         2.  pos 1: flag [0: -ve image, 1: +ve image]
         3.  pos 2: bbox [N*4 => number of bound  boxes] 
    so i want to know how to create image_buffer if i have got an image of np.array() from cv2

if possible please guide me through this part

the image buffer is create using cv2.imencode() function. after that the encodeed_img is reshape using: encode_img=encode_img.reshape(-1,1)