3d visualization

main.py

@@ -7,7 +7,20 @@ import gradio as gr
 import numpy as np
 import cv2
 
-inferencer = MMPoseInferencer('hand', device='cuda') # 'hand'
+# inferencer = MMPoseInferencer('hand') # 'hand', 'human , device='cuda'
+# inferencer = MMPoseInferencer('human')
+
+inferencer = MMPoseInferencer(pose3d='human3d')
+# https://github.com/open-mmlab/mmpose/tree/dev-1.x/configs/body_3d_keypoint/pose_lift
+# motionbert_ft_h36m-d80af323_20230531.pth
+# simple3Dbaseline_h36m-f0ad73a4_20210419.pth
+# videopose_h36m_243frames_fullconv_supervised_cpn_ft-88f5abbb_20210527.pth
+# videopose_h36m_81frames_fullconv_supervised-1f2d1104_20210527.pth
+# videopose_h36m_27frames_fullconv_supervised-fe8fbba9_20210527.pth
+# videopose_h36m_1frame_fullconv_supervised_cpn_ft-5c3afaed_20210527.pth
+
+# https://github.com/open-mmlab/mmpose/blob/main/mmpose/apis/inferencers/pose3d_inferencer.py
+
 print("[INFO]: Downloaded models!")
 
 
@@ -17,6 +30,7 @@ def poses(photo):
                                   return_vis=True,
                                   thickness=2)
     
+    
 
     # Prepare to save video
     output_file = os.path.join("output.mp4")
@@ -31,8 +45,6 @@ def poses(photo):
 
     for result in result_generator:
         frame = result["visualization"]
-        print(frame)
-        print(type(frame))
         out_writer.write(cv2.cvtColor(frame[0], cv2.COLOR_BGR2RGB))
 
     print(os.listdir())