introdyced state

main_noweb.py

@@ -1,5 +1,4 @@
 # Pose inferencing
-import mmpose
 from mmpose.apis import MMPoseInferencer
 
 import torch
@@ -9,7 +8,6 @@ import gradio as gr
 import moviepy.editor as moviepy
 
 
-
 # System and files
 import os
 import glob
@@ -33,6 +31,7 @@ os.system("nvidia-smi")
 print("[INFO]: Imported modules!")
 human = MMPoseInferencer("simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192") # simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192 dekr_hrnet-w32_8xb10-140e_coco-512x512
 hand = MMPoseInferencer("hand")
+#model3d = gr.State()
 
 #"https://github.com/open-mmlab/mmpose/blob/main/configs/body_3d_keypoint/pose_lift/h36m/pose-lift_simplebaseline3d_8xb64-200e_h36m.py", 
                            #"https://download.openmmlab.com/mmpose/body3d/simple_baseline/simple3Dbaseline_h36m-f0ad73a4_20210419.pth") # pose3d="human3d"
@@ -94,11 +93,13 @@ def check_extension(video):
 def pose3d(video, kpt_threshold):
     video = check_extension(video)
     print(device)
+    
+    #human3d = MMPoseInferencer(device=device,   pose3d="human3d",  scope="mmpose")#"pose-lift_videopose3d-243frm-supv-cpn-ft_8xb128-200e_h36m")
 
-    human3d = MMPoseInferencer(device=device, 
+    human3d = gr.State(value=MMPoseInferencer(device=device, 
                                pose3d="human3d", 
-                               scope="mmpose")#"pose-lift_videopose3d-243frm-supv-cpn-ft_8xb128-200e_h36m")
-
+                               scope="mmpose"))
+    
     # Define new unique folder
     add_dir = str(uuid.uuid4())
     vis_out_dir = os.path.join("/".join(video.split("/")[:-1]), add_dir)
@@ -304,13 +305,10 @@ print("Angle is: ", angle)
                             16: Right Ankle 
                             ```
 
-                            \n Below, you can see a visualization of the poses of the 2 and 3d keypoint locations:
-                            <img src="./cocoposes.png" width="200">
-
-                            \n And the hand keypoints are as follows:
-                            <img src="./cocohand.png" width="200">
-
-                            """)
+                            \n Below, you can see a visualization of the poses of the 2d, 3d and hand keypoint locations: """)
+                gr.Image("./cocoposes.png", width="200")
+                gr.Image("./cocohand.png", width="200")
+                            
 
                 
 
@@ -340,7 +338,7 @@ if __name__ == "__main__":
                 #max_size=25, # Maximum number of requests that the queue processes
                 api_open = False # When creating a Gradio demo, you may want to restrict all traffic to happen through the user interface as opposed to the programmatic API that is automatically created for your Gradio demo.  
                     ).launch(
-                 max_threads=31,
+                 # max_threads=31,
                  server_name="0.0.0.0", 
                  server_port=7860,
                  auth=("novouser", "bstad2023")