import gradio as gr
from PIL import Image

demo_inf_ofa = gr.Interface.load(name="spaces/ICML2022/OFA") #"spaces/freddyaboulton/blocks_inputs")
#demo_inf_lama = gr.Interface.load(name="spaces/CVPR/lama-example")  #gr.Blocks.load
#img = gr.Interface.load("spaces/multimodalart/latentdiffusion")(ent[0],'50','256','256','1',10)[0] 

#assert demo_inf("Foo", "bar") == "Foo bar"

def get_lama(img1, img2):
  Img1 = Image.open(img1)
  Img2 = Image.open(img2)
  img, mask = gr.Interface.load(name="spaces/CVPR/lama-example")(Img1, Img2, "automatic (U2net)")
  return img
  
#def txt_fun(txt1, txt2):
#  return demo_inf(txt1, txt2)

#original = Image.open("./c4.jpg")
#output_img_path = demo_inf("./c4.jpg", fn_index=1)
#output = Image.open(output_img_path)
#assert original.size == output.size

def img_fun1(img_in):
  return demo_inf(img_in) #, fn_index=1)

#original = Image.open("./c4.jpg")
#output_img_path = demo_inf("./c4.jpg", fn_index=1)
#output = Image.open(output_img_path)
#assert original.size == output.size

def img_fun(img_in):
  original = Image.open("./c4.jpg")
  print("after line1")
  output_img_path = demo_inf("./c4.jpg", fn_index=1)
  print("after line1")
  output = Image.open(output_img_path)
  print("after line1")
  return output
  
demo = gr.Blocks()

with demo:
  gr.Markdown("<h1><center>Testing</center></h1>")
  gr.Markdown(
        """Testing Inference for Gradio. Work in Progress."""
        )
  with gr.Row():
    in_image = gr.Image(type='file') #(visible=False) type='numpy'
    in_image_mask = gr.Image(type='file') #, source="canvas") #, visible=False) #type='numpy',
    out_image = gr.outputs.Image(type='file') #(type='file')
    
    #in_text1 = gr.Textbox()
    #in_text2 = gr.Textbox()
    #out_text = gr.Textbox()
    
  b1 = gr.Button("Image Button")
  #b2 = gr.Button("Text Button") 

  b1.click(get_lama,inputs=[in_image, in_image_mask], outputs=out_image) 
  #b2.click(txt_fun, inputs=[in_text1, in_text2], outputs=out_text)
  #examples=examples 

demo.launch(enable_queue=True, debug=True)