visualization

main.py

@@ -6,18 +6,20 @@ print("[INFO]: Imported modules!")
 
 import gradio as gr
 
-def greet(photo):
+def poses(photo):
     inferencer = MMPoseInferencer('human')
 
     print("[INFO]: Downloaded models!")
     print(photo)
-    result_generator = inferencer(photo, show=False)
+    result_generator = inferencer(photo, 
+                                  out_dir =".")
 
     print("[INFO]: Visualizing results!")
     # The MMPoseInferencer API employs a lazy inference approach,
     # creating a prediction generator when given input
     result = next(result_generator)
-    print(result)
+    print(type(result))
+    print(result.shape)
     return result['visualization']
 
 # # specify detection model by alias
@@ -32,7 +34,7 @@ def greet(photo):
     
 def run():
     #https://github.com/open-mmlab/mmpose/blob/main/docs/en/user_guides/inference.md
-    demo = gr.Interface(fn=greet, 
+    demo = gr.Interface(fn=poses, 
                         inputs=gr.Image(source="webcam"),
                         outputs=gr.Image())