Update app.py

app.py

@@ -1,93 +1,33 @@
-# -*- 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 gradio_client import Client, handle_file
+
+# Создаем клиента для API
+client = Client("tuan2308/face-swap")
+
+def swap_face_api(source_img, target_img, doFaceEnhancer):
+    try:
+        result = client.predict(
+            source_file=handle_file(source_img),
+            target_file=handle_file(target_img),
+            doFaceEnhancer=doFaceEnhancer,
+            api_name="/predict"
+        )
+        return result
+    except Exception as e:
+        print(f"Ошибка при вызове API: {e}")
+        return None  # Или какое-то изображение-заглушку
+
+# Создаем интерфейс
+iface = gr.Interface(
+    fn=swap_face_api,
+    inputs=[
+        gr.Image(type="filepath", label="Source Image"),
+        gr.Image(type="filepath", label="Target Image"),
+        gr.Checkbox(label="Face Enhancer?")
+    ],
+    outputs=gr.Image(label="Output Image"),
+    title="Face Swap via API"
 )
-from roop.processors.frame.core import get_frame_processors_modules
-from roop.utilities import normalize_output_path
-import os
-import random
-from PIL import Image
-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_dir = "temp"  # Sử dụng thư mục cố định
-    os.makedirs(session_dir, exist_ok=True)
-
-    # Tạo tên file ngẫu nhiên
-    source_filename = f"source_{random.randint(1000, 9999)}.jpg"
-    target_filename = f"target_{random.randint(1000, 9999)}.jpg"
-    output_filename = f"output_{random.randint(1000, 9999)}.jpg"
-
-    source_path = os.path.join(session_dir, source_filename)
-    target_path = os.path.join(session_dir, target_filename)
-
-    # Сохранение изображений
-    Image.fromarray(source_file).save(source_path)
-    Image.fromarray(target_file).save(target_path)
-
-    print("source_path: ", source_path)
-    print("target_path: ", target_path)
-
-    # Проверка наличия лица на изображении источника
-    source_face = get_one_face(cv2.imread(source_path))
-    if source_face is None:
-        raise gradio.exceptions.Error("No face in source path detected.")
 
-    # Проверка наличия лица на изображении целевого изображения
-    target_face = get_one_face(cv2.imread(target_path))
-    if target_face is None:
-        raise gradio.exceptions.Error("No face in target path detected.")
+iface.launch()
 
-    output_path = os.path.join(session_dir, output_filename)
-    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 = decode_execution_providers(['cpu'])
-    roop.globals.reference_face_position = 0
-    roop.globals.similar_face_distance = 0.6
-    roop.globals.max_memory = 60
-    roop.globals.execution_threads = 8
-    
-    start()
-
-    # Возвращаем изображение как массив байтов
-    with open(normalized_output_path, "rb") as image_file:
-        return image_file.read()
-
-app = gr.Interface(
-    fn=swap_face, 
-    inputs=[
-        gr.Image(type="numpy"), 
-        gr.Image(type="numpy"), 
-        gr.Checkbox(label="Face Enhancer?", info="Do face enhancement?")
-    ], 
-    outputs="image"
-)
-app.launch()