File size: 2,953 Bytes
205b8f5
1f6a041
e496964
1f6a041
51a3166
205b8f5
1f6a041
 
 
 
 
 
 
 
 
3aff737
28ae202
205b8f5
 
51a3166
705287f
a39ec9f
3aff737
 
 
 
 
 
1f6a041
 
 
 
 
 
9bb30ce
 
1f6a041
205b8f5
 
 
 
 
 
 
 
 
 
3aff737
42b1f81
1f6a041
42b1f81
decc5b1
1f6a041
42b1f81
1f6a041
438e3e2
205b8f5
1f6a041
42b1f81
 
 
 
9bb30ce
 
 
 
 
 
 
 
 
 
 
 
 
1f6a041
205b8f5
1f6a041
 
438e3e2
 
 
 
 
 
 
1f6a041
3538116
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
# -*- coding:UTF-8 -*-
# !/usr/bin/env python
import spaces
import numpy as np
import gradio as gr
import gradio.exceptions
import roop.globals
from roop.core import (
    start,
    decode_execution_providers,
)
from roop.processors.frame.core import get_frame_processors_modules
from roop.utilities import normalize_output_path
import os
from PIL import Image
import uuid
import onnxruntime as ort
import cv2
from roop.face_analyser import get_one_face

@spaces.GPU
def swap_face(source_file, target_file, doFaceEnhancer):
    session_id = str(uuid.uuid4())  # Tạo một UUID duy nhất cho mỗi phiên làm việc
    session_dir = f"temp/{session_id}"
    os.makedirs(session_dir, exist_ok=True)

    source_path = os.path.join(session_dir, "input.jpg")
    target_path = os.path.join(session_dir, "target.jpg")

    source_image = Image.fromarray(source_file)
    source_image.save(source_path)
    target_image = Image.fromarray(target_file)
    target_image.save(target_path)

    print("source_path: ", source_path)
    print("target_path: ", target_path)

    # Check if a face is detected in the source image
    source_face = get_one_face(cv2.imread(source_path))
    if source_face is None:
        raise gradio.exceptions.Error("No face in source path detected.")

    # Check if a face is detected in the target image
    target_face = get_one_face(cv2.imread(target_path))
    if target_face is None:
        raise gradio.exceptions.Error("No face in target path detected.")

    output_path = os.path.join(session_dir, "output.jpg")
    normalized_output_path = normalize_output_path(source_path, target_path, output_path)

    frame_processors = ["face_swapper", "face_enhancer"] if doFaceEnhancer else ["face_swapper"]


    for frame_processor in get_frame_processors_modules(frame_processors):
        if not frame_processor.pre_check():
            print(f"Pre-check failed for {frame_processor}")
            raise gradio.exceptions.Error(f"Pre-check failed for {frame_processor}")

    roop.globals.source_path = source_path
    roop.globals.target_path = target_path
    roop.globals.output_path = normalized_output_path
    roop.globals.frame_processors = frame_processors
    roop.globals.headless = True
    roop.globals.keep_fps = True
    roop.globals.keep_audio = True
    roop.globals.keep_frames = False
    roop.globals.many_faces = False
    roop.globals.video_encoder = "libx264"
    roop.globals.video_quality = 18
    roop.globals.execution_providers = ["CUDAExecutionProvider"]
    roop.globals.reference_face_position = 0
    roop.globals.similar_face_distance = 0.6
    roop.globals.max_memory = 60
    roop.globals.execution_threads = 50
    
    start()
    return normalized_output_path

app = gr.Interface(
    fn=swap_face, 
    inputs=[
        gr.Image(), 
        gr.Image(), 
        gr.Checkbox(label="Face Enhancer?", info="Do face enhancement?")
    ], 
    outputs="image"
)
app.launch(share=True)