Spaces:
Runtime error
Runtime error
Update app.py
#1
by
adfly450
- opened
app.py
CHANGED
@@ -1,68 +1,68 @@
|
|
1 |
import gradio as gr
|
2 |
from refacer import Refacer
|
3 |
import argparse
|
4 |
-
import
|
|
|
5 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
6 |
parser = argparse.ArgumentParser(description='Refacer')
|
7 |
parser.add_argument("--max_num_faces", type=int, help="Max number of faces on UI", default=5)
|
8 |
parser.add_argument("--force_cpu", help="Force CPU mode", default=False, action="store_true")
|
9 |
parser.add_argument("--share_gradio", help="Share Gradio", default=False, action="store_true")
|
10 |
parser.add_argument("--server_name", type=str, help="Server IP address", default="127.0.0.1")
|
11 |
parser.add_argument("--server_port", type=int, help="Server port", default=7860)
|
12 |
-
parser.add_argument("--colab_performance", help="Use in colab for better performance", default=False,action="store_true")
|
13 |
-
parser.add_argument("--ngrok", type=str, help="Use ngrok", default=None)
|
14 |
-
parser.add_argument("--ngrok_region", type=str, help="ngrok region", default="us")
|
15 |
args = parser.parse_args()
|
16 |
|
17 |
-
|
18 |
-
|
19 |
-
num_faces=args.max_num_faces
|
20 |
-
|
21 |
-
# Connect to ngrok for ingress
|
22 |
-
def connect(token, port, options):
|
23 |
-
account = None
|
24 |
-
if token is None:
|
25 |
-
token = 'None'
|
26 |
-
else:
|
27 |
-
if ':' in token:
|
28 |
-
# token = authtoken:username:password
|
29 |
-
token, username, password = token.split(':', 2)
|
30 |
-
account = f"{username}:{password}"
|
31 |
-
|
32 |
-
# For all options see: https://github.com/ngrok/ngrok-py/blob/main/examples/ngrok-connect-full.py
|
33 |
-
if not options.get('authtoken_from_env'):
|
34 |
-
options['authtoken'] = token
|
35 |
-
if account:
|
36 |
-
options['basic_auth'] = account
|
37 |
-
|
38 |
-
|
39 |
-
try:
|
40 |
-
public_url = ngrok.connect(f"127.0.0.1:{port}", **options).url()
|
41 |
-
except Exception as e:
|
42 |
-
print(f'Invalid ngrok authtoken? ngrok connection aborted due to: {e}\n'
|
43 |
-
f'Your token: {token}, get the right one on https://dashboard.ngrok.com/get-started/your-authtoken')
|
44 |
-
else:
|
45 |
-
print(f'ngrok connected to localhost:{port}! URL: {public_url}\n'
|
46 |
-
'You can use this link after the launch is complete.')
|
47 |
|
|
|
48 |
|
|
|
49 |
def run(*vars):
|
50 |
-
video_path=vars[0]
|
51 |
-
origins=vars[1:(num_faces+1)]
|
52 |
-
destinations=vars[(num_faces+1):(num_faces*2)+1]
|
53 |
-
thresholds=vars[(num_faces*2)+1:]
|
54 |
|
55 |
faces = []
|
56 |
-
for k in range(0,num_faces):
|
57 |
if origins[k] is not None and destinations[k] is not None:
|
58 |
faces.append({
|
59 |
-
'origin':origins[k],
|
60 |
-
'destination':destinations[k],
|
61 |
-
'threshold':thresholds[k]
|
62 |
})
|
63 |
|
64 |
-
|
|
|
|
|
|
|
|
|
65 |
|
|
|
66 |
origin = []
|
67 |
destination = []
|
68 |
thresholds = []
|
@@ -71,23 +71,21 @@ with gr.Blocks() as demo:
|
|
71 |
with gr.Row():
|
72 |
gr.Markdown("# Refacer")
|
73 |
with gr.Row():
|
74 |
-
video=gr.Video(label="Original video",format="mp4")
|
75 |
-
video2=gr.Video(label="Refaced video",interactive=False,format="mp4")
|
76 |
|
77 |
-
for i in range(0,num_faces):
|
78 |
with gr.Tab(f"Face #{i+1}"):
|
79 |
with gr.Row():
|
80 |
origin.append(gr.Image(label="Face to replace"))
|
81 |
destination.append(gr.Image(label="Destination face"))
|
82 |
with gr.Row():
|
83 |
-
thresholds.append(gr.Slider(label="Threshold",minimum=0.0,maximum=1.0,value=0.2))
|
|
|
84 |
with gr.Row():
|
85 |
-
button=gr.Button("Reface", variant="primary")
|
86 |
|
87 |
-
button.click(fn=run,inputs=[video]+origin+destination+thresholds,outputs=[video2])
|
88 |
-
|
89 |
-
|
90 |
-
|
91 |
-
|
92 |
-
#demo.launch(share=True,server_name="0.0.0.0", show_error=True)
|
93 |
-
demo.queue().launch(show_error=True,share=args.share_gradio,server_name=args.server_name,server_port=args.server_port)
|
|
|
1 |
import gradio as gr
|
2 |
from refacer import Refacer
|
3 |
import argparse
|
4 |
+
import os
|
5 |
+
import requests
|
6 |
|
7 |
+
# Hugging Face URL to download the model
|
8 |
+
model_url = "https://huggingface.co/ofter/4x-UltraSharp/resolve/main/inswapper_128.onnx"
|
9 |
+
model_path = "./inswapper_128.onnx"
|
10 |
+
|
11 |
+
# Function to download the model
|
12 |
+
def download_model():
|
13 |
+
if not os.path.exists(model_path):
|
14 |
+
print("Downloading inswapper_128.onnx...")
|
15 |
+
response = requests.get(model_url)
|
16 |
+
if response.status_code == 200:
|
17 |
+
with open(model_path, 'wb') as f:
|
18 |
+
f.write(response.content)
|
19 |
+
print("Model downloaded successfully!")
|
20 |
+
else:
|
21 |
+
raise Exception(f"Failed to download the model. Status code: {response.status_code}")
|
22 |
+
else:
|
23 |
+
print("Model already exists.")
|
24 |
+
|
25 |
+
# Download the model when the script runs
|
26 |
+
download_model()
|
27 |
+
|
28 |
+
# Argument parser
|
29 |
parser = argparse.ArgumentParser(description='Refacer')
|
30 |
parser.add_argument("--max_num_faces", type=int, help="Max number of faces on UI", default=5)
|
31 |
parser.add_argument("--force_cpu", help="Force CPU mode", default=False, action="store_true")
|
32 |
parser.add_argument("--share_gradio", help="Share Gradio", default=False, action="store_true")
|
33 |
parser.add_argument("--server_name", type=str, help="Server IP address", default="127.0.0.1")
|
34 |
parser.add_argument("--server_port", type=int, help="Server port", default=7860)
|
35 |
+
parser.add_argument("--colab_performance", help="Use in colab for better performance", default=False, action="store_true")
|
|
|
|
|
36 |
args = parser.parse_args()
|
37 |
|
38 |
+
# Initialize the Refacer class
|
39 |
+
refacer = Refacer(force_cpu=args.force_cpu, colab_performance=args.colab_performance)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
40 |
|
41 |
+
num_faces = args.max_num_faces
|
42 |
|
43 |
+
# Run function for refacing video
|
44 |
def run(*vars):
|
45 |
+
video_path = vars[0]
|
46 |
+
origins = vars[1:(num_faces+1)]
|
47 |
+
destinations = vars[(num_faces+1):(num_faces*2)+1]
|
48 |
+
thresholds = vars[(num_faces*2)+1:]
|
49 |
|
50 |
faces = []
|
51 |
+
for k in range(0, num_faces):
|
52 |
if origins[k] is not None and destinations[k] is not None:
|
53 |
faces.append({
|
54 |
+
'origin': origins[k],
|
55 |
+
'destination': destinations[k],
|
56 |
+
'threshold': thresholds[k]
|
57 |
})
|
58 |
|
59 |
+
# Call refacer to process video and get file path
|
60 |
+
refaced_video_path = refacer.reface(video_path, faces) # refaced video path
|
61 |
+
print(f"Refaced video can be found at {refaced_video_path}")
|
62 |
+
|
63 |
+
return refaced_video_path # Return the file path to show in Gradio output
|
64 |
|
65 |
+
# Prepare Gradio components
|
66 |
origin = []
|
67 |
destination = []
|
68 |
thresholds = []
|
|
|
71 |
with gr.Row():
|
72 |
gr.Markdown("# Refacer")
|
73 |
with gr.Row():
|
74 |
+
video = gr.Video(label="Original video", format="mp4")
|
75 |
+
video2 = gr.Video(label="Refaced video", interactive=False, format="mp4")
|
76 |
|
77 |
+
for i in range(0, num_faces):
|
78 |
with gr.Tab(f"Face #{i+1}"):
|
79 |
with gr.Row():
|
80 |
origin.append(gr.Image(label="Face to replace"))
|
81 |
destination.append(gr.Image(label="Destination face"))
|
82 |
with gr.Row():
|
83 |
+
thresholds.append(gr.Slider(label="Threshold", minimum=0.0, maximum=1.0, value=0.2))
|
84 |
+
|
85 |
with gr.Row():
|
86 |
+
button = gr.Button("Reface", variant="primary")
|
87 |
|
88 |
+
button.click(fn=run, inputs=[video] + origin + destination + thresholds, outputs=[video2])
|
89 |
+
|
90 |
+
# Launch the Gradio app
|
91 |
+
demo.queue().launch(show_error=True, share=args.share_gradio, server_name="0.0.0.0", server_port=args.server_port)
|
|
|
|
|
|