added web

main_noweb.py

@@ -183,38 +183,7 @@ def pose2dhand(video, kpt_threshold):
    
     return "".join(out_file), "".join(kpoints)
 
-block = gr.Blocks()
-
-with block:
-    with gr.Column():       
-        with gr.Tab("Upload video"):
-            with gr.Column():
-                with gr.Row():
-                    with gr.Column():
-                        with gr.Row():
-                            video_input = gr.Video(source="upload", type="filepath", height=256, width=192)
-                            # Insert slider with kpt_thr
-                            with gr.Column():
-                                gr.Markdown("Drag the keypoint threshold to filter out lower probability keypoints:")
-                                file_kpthr = gr.Slider(0, 1, value=0.3, label='Keypoint threshold')
-                        with gr.Row():
-                            submit_pose_file = gr.Button("Make 2d pose estimation")
-                            submit_pose3d_file = gr.Button("Make 3d pose estimation")
-                            submit_hand_file = gr.Button("Make 2d hand estimation")
-
-                with gr.Row():
-                    video_output1 = gr.PlayableVideo(label = "Estimate human 2d poses", show_label=True, height=256)
-                    video_output2 = gr.PlayableVideo(label = "Estimate human 3d poses", show_label=True, height=256)
-                    video_output3 = gr.PlayableVideo(label = "Estimate human hand poses", show_label=True, height=256)
-                
-                gr.Markdown("Download the .json file that contains the keypoint positions for each frame in the video.")
-                jsonoutput = gr.File(file_types=[".json"])
-                gr.Markdown("""There are multiple ways to interact with these keypoints. 
-                            \n The example below shows how you can calulate the angle on the elbow for example.
-                            \n Copy the code into your own preferred interpreter and experiment with the keypoint file. 
-                            \n If you choose to run the code, start by installing the packages json and numpy. The complete overview of the keypoint indices can be seen in the tab 'General information'. """)
-                gr.Code(
-                    value="""
+code_example = """
                     
 # Importing packages needed  
 import json
@@ -253,7 +222,72 @@ wrist_point = data[0]['instances'][0]['keypoints'][wrist_index]
 angle = calculate_angle(shoulder_point, elbow_point, wrist_point)
 print("Angle is: ", angle)    
 
-                    """,
+                    """
+
+block = gr.Blocks()
+
+with block:
+    with gr.Column():       
+        with gr.Tab("Upload video"):
+            with gr.Column():
+                with gr.Row():
+                    with gr.Column():
+                        with gr.Row():
+                            video_input_web = gr.Video(source="webcam", height=256, width=192)
+                            # Insert slider with kpt_thr
+                            with gr.Column():
+                                gr.Markdown("Drag the keypoint threshold to filter out lower probability keypoints:")
+                                file_kpthr_web = gr.Slider(0, 1, value=0.3, label='Keypoint threshold')
+                        with gr.Row():
+                            submit_pose_file_web = gr.Button("Make 2d pose estimation")
+                            submit_pose3d_file_web = gr.Button("Make 3d pose estimation")
+                            submit_hand_file_web = gr.Button("Make 2d hand estimation")
+
+                with gr.Row():
+                    video_output1_web = gr.PlayableVideo(label = "Estimate human 2d poses", show_label=True, height=256)
+                    video_output2_web = gr.PlayableVideo(label = "Estimate human 3d poses", show_label=True, height=256)
+                    video_output3_web = gr.PlayableVideo(label = "Estimate human hand poses", show_label=True, height=256)
+                
+                gr.Markdown("Download the .json file that contains the keypoint positions for each frame in the video.")
+                jsonoutput_web = gr.File(file_types=[".json"])
+                gr.Markdown("""There are multiple ways to interact with these keypoints. 
+                            \n The example below shows how you can calulate the angle on the elbow for example.
+                            \n Copy the code into your own preferred interpreter and experiment with the keypoint file. 
+                            \n If you choose to run the code, start by installing the packages json and numpy. The complete overview of the keypoint indices can be seen in the tab 'General information'. """)
+                gr.Code(
+                    value=code_example,
+                    language="python",
+                    interactive=False,
+                    show_label=False,
+                )
+        with gr.Tab("Upload video"):
+            with gr.Column():
+                with gr.Row():
+                    with gr.Column():
+                        with gr.Row():
+                            video_input = gr.Video(source="upload", type="filepath", height=256, width=192)
+                            # Insert slider with kpt_thr
+                            with gr.Column():
+                                gr.Markdown("Drag the keypoint threshold to filter out lower probability keypoints:")
+                                file_kpthr = gr.Slider(0, 1, value=0.3, label='Keypoint threshold')
+                        with gr.Row():
+                            submit_pose_file = gr.Button("Make 2d pose estimation")
+                            submit_pose3d_file = gr.Button("Make 3d pose estimation")
+                            submit_hand_file = gr.Button("Make 2d hand estimation")
+
+                with gr.Row():
+                    video_output1 = gr.PlayableVideo(label = "Estimate human 2d poses", show_label=True, height=256)
+                    video_output2 = gr.PlayableVideo(label = "Estimate human 3d poses", show_label=True, height=256)
+                    video_output3 = gr.PlayableVideo(label = "Estimate human hand poses", show_label=True, height=256)
+                
+                gr.Markdown("Download the .json file that contains the keypoint positions for each frame in the video.")
+                jsonoutput = gr.File(file_types=[".json"])
+                gr.Markdown("""There are multiple ways to interact with these keypoints. 
+                            \n The example below shows how you can calulate the angle on the elbow for example.
+                            \n Copy the code into your own preferred interpreter and experiment with the keypoint file. 
+                            \n If you choose to run the code, start by installing the packages json and numpy. The complete overview of the keypoint indices can be seen in the tab 'General information'. """)
+                gr.Code(
+                    value=code_example,
                     language="python",
                     interactive=False,
                     show_label=False,
@@ -322,6 +356,24 @@ print("Angle is: ", angle)
                             outputs = [video_output3, jsonoutput],
                             queue=True)
         
+        # From web
+        submit_pose_file_web.click(fn=pose2d, 
+                            inputs=  [video_input_web, file_kpthr_web], 
+                            outputs = [video_output1_web, jsonoutput_web],
+                            queue=True)
+        
+        submit_pose3d_file_web.click(fn=pose3d, 
+                                inputs= [video_input_web, file_kpthr_web], 
+                                outputs = [video_output2_web, jsonoutput_web],
+                                #batch=True, 
+                                #max_batch_size=16,
+                                queue=True) # Sometimes it worked with queue false? But still slow
+        
+        submit_hand_file_web.click(fn=pose2dhand, 
+                            inputs= [video_input_web, file_kpthr_web], 
+                            outputs = [video_output3_web, jsonoutput_web],
+                            queue=True)
+        
 if __name__ == "__main__":
     block.queue(max_size=20, 
                 #concurrency_count=40, # When you increase the concurrency_count parameter in queue(), max_threads() in launch() is automatically increased as well.