Update app.py
Browse files
app.py
CHANGED
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# -*- coding:UTF-8 -*-
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# !/usr/bin/env python
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import spaces
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import numpy as np
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import gradio as gr
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import
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)
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from roop.processors.frame.core import get_frame_processors_modules
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from roop.utilities import normalize_output_path
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import os
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import random
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from PIL import Image
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import onnxruntime as ort
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import cv2
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from roop.face_analyser import get_one_face
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@spaces.GPU
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def swap_face(source_file, target_file, doFaceEnhancer):
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session_dir = "temp" # Sử dụng thư mục cố định
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os.makedirs(session_dir, exist_ok=True)
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# Tạo tên file ngẫu nhiên
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source_filename = f"source_{random.randint(1000, 9999)}.jpg"
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target_filename = f"target_{random.randint(1000, 9999)}.jpg"
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output_filename = f"output_{random.randint(1000, 9999)}.jpg"
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source_path = os.path.join(session_dir, source_filename)
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target_path = os.path.join(session_dir, target_filename)
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# Сохранение изображений
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Image.fromarray(source_file).save(source_path)
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Image.fromarray(target_file).save(target_path)
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print("source_path: ", source_path)
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print("target_path: ", target_path)
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# Проверка наличия лица на изображении источника
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source_face = get_one_face(cv2.imread(source_path))
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if source_face is None:
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raise gradio.exceptions.Error("No face in source path detected.")
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target_face = get_one_face(cv2.imread(target_path))
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if target_face is None:
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raise gradio.exceptions.Error("No face in target path detected.")
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output_path = os.path.join(session_dir, output_filename)
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normalized_output_path = normalize_output_path(source_path, target_path, output_path)
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frame_processors = ["face_swapper", "face_enhancer"] if doFaceEnhancer else ["face_swapper"]
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for frame_processor in get_frame_processors_modules(frame_processors):
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if not frame_processor.pre_check():
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print(f"Pre-check failed for {frame_processor}")
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raise gradio.exceptions.Error(f"Pre-check failed for {frame_processor}")
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roop.globals.source_path = source_path
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roop.globals.target_path = target_path
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roop.globals.output_path = normalized_output_path
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roop.globals.frame_processors = frame_processors
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roop.globals.headless = True
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roop.globals.keep_fps = True
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roop.globals.keep_audio = True
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roop.globals.keep_frames = False
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roop.globals.many_faces = False
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roop.globals.video_encoder = "libx264"
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roop.globals.video_quality = 18
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roop.globals.execution_providers = decode_execution_providers(['cpu'])
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roop.globals.reference_face_position = 0
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roop.globals.similar_face_distance = 0.6
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roop.globals.max_memory = 60
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roop.globals.execution_threads = 8
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start()
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# Возвращаем изображение как массив байтов
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with open(normalized_output_path, "rb") as image_file:
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return image_file.read()
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app = gr.Interface(
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fn=swap_face,
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inputs=[
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gr.Image(type="numpy"),
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gr.Image(type="numpy"),
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gr.Checkbox(label="Face Enhancer?", info="Do face enhancement?")
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],
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outputs="image"
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)
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app.launch()
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import gradio as gr
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from gradio_client import Client, handle_file
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# Создаем клиента для API
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client = Client("tuan2308/face-swap")
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def swap_face_api(source_img, target_img, doFaceEnhancer):
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try:
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result = client.predict(
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source_file=handle_file(source_img),
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target_file=handle_file(target_img),
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doFaceEnhancer=doFaceEnhancer,
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api_name="/predict"
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)
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return result
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except Exception as e:
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print(f"Ошибка при вызове API: {e}")
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return None # Или какое-то изображение-заглушку
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# Создаем интерфейс
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iface = gr.Interface(
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fn=swap_face_api,
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inputs=[
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gr.Image(type="filepath", label="Source Image"),
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gr.Image(type="filepath", label="Target Image"),
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gr.Checkbox(label="Face Enhancer?")
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],
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outputs=gr.Image(label="Output Image"),
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title="Face Swap via API"
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)
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iface.launch()
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