Added command line arguments for --share_gradio #7. Implemented multithreaded parallel processing and CoreML optimization, still pending CUDA optimization #5.

app.py

@@ -1,20 +1,25 @@
 import gradio as gr
 from refacer import Refacer
+import argparse
 
-MAX_NUM_OF_FACES=8
+parser = argparse.ArgumentParser(description='Refacer')
+parser.add_argument("--max_num_faces", help="Max number of faces on UI", default=5)
+parser.add_argument("--force_cpu", help="Force CPU mode", default=False,action="store_true")
+parser.add_argument("--share_gradio", help="Share Gradio", default=False,action="store_true")
+args = parser.parse_args()
 
-refacer = Refacer()
+refacer = Refacer(force_cpu=args.force_cpu)
 
-n=MAX_NUM_OF_FACES
+num_faces=args.max_num_faces
 
 def run(*vars):
     video_path=vars[0]
-    origins=vars[1:(n+1)]
-    destinations=vars[(n+1):(n*2)+1]
-    thresholds=vars[(n*2)+1:]
+    origins=vars[1:(num_faces+1)]
+    destinations=vars[(num_faces+1):(num_faces*2)+1]
+    thresholds=vars[(num_faces*2)+1:]
 
     faces = []
-    for k in range(0,n):
+    for k in range(0,num_faces):
         if origins[k] is not None and destinations[k] is not None:
             faces.append({
                 'origin':origins[k],
@@ -35,7 +40,7 @@ with gr.Blocks() as demo:
         video=gr.Video(label="Original video")
         video2=gr.Video(label="Refaced video",interactive=False)
 
-    for i in range(0,MAX_NUM_OF_FACES):
+    for i in range(0,num_faces):
         with gr.Tab(f"Face #{i+1}"):
             with gr.Row():
                 origin.append(gr.Image(label="Face to replace"))
@@ -48,4 +53,4 @@ with gr.Blocks() as demo:
     button.click(fn=run,inputs=[video]+origin+destination+thresholds,outputs=[video2])
 
 #demo.launch(share=True,server_name="0.0.0.0", show_error=True)
-demo.queue().launch(show_error=True,share=True)
+demo.queue().launch(show_error=True,share=args.share_gradio)