Spaces:
Running
on
Zero
Running
on
Zero
File size: 2,943 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 9bb30ce |
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() |