import mmpose
import os
from mmpose.apis import MMPoseInferencer

inferencer = MMPoseInferencer('human')
print("[INFO]: Imported modules!")

import gradio as gr

def greet(photo):
    print("[INFO]: Downloaded models!")
    result_generator = inferencer(photo)

    print("[INFO]: Visualizing results!")
    result = next(result_generator)
    print(os.listdir())
    print(result['visualization'])
    return result['visualization']

# # specify detection model by alias
# # the available aliases include 'human', 'hand', 'face', 'animal',
# # as well as any additional aliases defined in mmdet
# inferencer = MMPoseInferencer(
#     # suppose the pose estimator is trained on custom dataset
#     pose2d='custom_human_pose_estimator.py',
#     pose2d_weights='custom_human_pose_estimator.pth',
#     det_model='human'
# )
    
def run():
    demo = gr.Interface(fn=greet, 
                        inputs=gr.Image(source="webcam"),
                        outputs=gr.Image())


    demo.launch(server_name="0.0.0.0", server_port=7860)


if __name__ == "__main__":
    run()